INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96454, 2014, 'bmc', 'Pathomx: an interactive workflow-based tool for the analysis of metabolomic data', 'Fitzpatrick, Martin A|McGrath, Catherine M|Young, Stephen P', 'Rheumatology Research Group, Centre for Translational Inflammation Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2WD, UK. mxf793@bham.ac.uk.|Rheumatology Research Group, Centre for Translational Inflammation Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2WD, UK. c.m.mcgrath@bham.ac.uk.|Rheumatology Research Group, Centre for Translational Inflammation Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2WD, UK. s.p.young@bham.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Cells, Cultured|Computational Biology|Databases, Factual|Humans|Macrophages|Magnetic Resonance Spectroscopy|Metabolic Networks and Pathways|Metabolomics|Reproducibility of Results|Software|Workflow', 'Journal Article', '10.1186/s12859-014-0396-9', '25490956', 'Metabolomics is a systems approach to the analysis of cellular processes through small-molecule metabolite profiling. Standardisation of sample handling and acquisition approaches has contributed to reproducibility. However, the development of robust methods for the analysis of metabolomic data is a work-in-progress. The tools that do exist are often not well integrated, requiring manual data handling and custom scripting on a case-by-case basis. Furthermore, existing tools often require experience with programming environments such as MATLAB® or R to use, limiting accessibility. Here we present Pathomx, a workflow-based tool for the processing, analysis and visualisation of metabolomic and associated data in an intuitive and extensible environment.'),
(96455, 2014, 'bmc', 'Integrating protein structural dynamics and evolutionary analysis with Bio3D', 'Skjærven, Lars|Yao, Xin-Qiu|Scarabelli, Guido|Grant, Barry J', 'Department of Biomedicine, University of Bergen, Bergen, Norway. lars.skjarven@biomed.uib.no.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA. xinqyao@umich.edu.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA. guidos@umich.edu.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA. bjgrant@umich.edu.', 'Norway|United States|United States|United States', 148, 'Computational Biology|Escherichia coli|Evolution, Molecular|Heterotrimeric GTP-Binding Proteins|Humans|Molecular Dynamics Simulation|Molecular Structure|Protein Conformation|Software|Tetrahydrofolate Dehydrogenase', 'Journal Article', '10.1186/s12859-014-0399-6', '25491031', 'Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how observed displacements and predicted motions from these traditionally separate analyses relate to each other, as well as to the evolution of sequence, structure and function within large protein families, remains a considerable challenge. This is in part due to the general lack of tools that integrate information of molecular structure, dynamics and evolution.'),
(96456, 2014, 'bmc', 'MCMC implementation of the optimal Bayesian classifier for non-Gaussian models: model-based RNA-Seq classification', 'Knight, Jason M|Ivanov, Ivan|Dougherty, Edward R', 'Department of Electrical Engineering in Texas A&M University, 3128 TAMU, College Station, 77843, TX, USA. jknight@tamu.edu.|Department of Veterinary Physiology and Pharmacology in Texas A&M University, 3128 TAMU, College Station, 77843, TX, USA. iivanov@cvm.tamu.edu.|Department of Electrical Engineering in Texas A&M University, 3128 TAMU, College Station, 77843, TX, USA. edward@ece.tamu.edu.', 'United States|United States|United States', 0, 'Adenocarcinoma|Bayes Theorem|Carcinoma, Squamous Cell|Computational Biology|High-Throughput Nucleotide Sequencing|Humans|Lung Neoplasms|Markov Chains|Models, Statistical|Monte Carlo Method|RNA', 'Journal Article', '10.1186/s12859-014-0401-3', '25491122', 'Sequencing datasets consist of a finite number of reads which map to specific regions of a reference genome. Most effort in modeling these datasets focuses on the detection of univariate differentially expressed genes. However, for classification, we must consider multiple genes and their interactions.'),
(96457, 2014, 'bmc', 'Comparative structural analysis of haemagglutinin proteins from type A influenza viruses: conserved and variable features', 'Righetto, Irene|Milani, Adelaide|Cattoli, Giovanni|Filippini, Francesco', 'Molecular Biology and Bioinformatics Unit (MOLBINFO), Department of Biology, University of Padua, via U. Bassi 58/B, 35131, Padova, Italy. irene.righetto@bio.unipd.it.|FAO-OIE and National Reference Laboratory for Newcastle Disease and Avian Influenza, Istituto Zooprofilattico delle Venezie (IZSVe), viale dellUniversità 10, 35020, Legnaro, Italy. amilani@izsvenezie.it.|FAO-OIE and National Reference Laboratory for Newcastle Disease and Avian Influenza, Istituto Zooprofilattico delle Venezie (IZSVe), viale dellUniversità 10, 35020, Legnaro, Italy. gcattoli@izsvenezie.it.|Molecular Biology and Bioinformatics Unit (MOLBINFO), Department of Biology, University of Padua, via U. Bassi 58/B, 35131, Padova, Italy. francesco.filippini@unipd.it.', 'Italy|Italy|Italy|Italy', 7, 'Biological Evolution|Hemagglutinin Glycoproteins, Influenza Virus|Humans|Influenza A Virus, H5N1 Subtype|Influenza, Human|Neuraminidase|Phylogeny|Protein Conformation|Protein Structure, Tertiary|Receptors, Virus|Serologic Tests|Static Electricity', 'Comparative Study', '10.1186/s12859-014-0363-5', '25492298', 'Genome variation is very high in influenza A viruses. However, viral evolution and spreading is strongly influenced by immunogenic features and capacity to bind host cells, depending in turn on the two major capsidic proteins. Therefore, such viruses are classified based on haemagglutinin and neuraminidase types, e.g. H5N1. Current analyses of viral evolution are based on serological and primary sequence comparison, however, comparative structural analysis of capsidic proteins can provide functional insights on surface regions possibly crucial to antigenicity and cell binding.'),
(96458, 2014, 'bmc', 'A fixed-point algorithm for estimating amplification efficiency from a polymerase chain reaction dilution series', 'Jones, Michael E|Mayne, George C|Wang, Tingting|Watson, David I|Hussey, Damian J', 'Department of Anaesthesia and Pain Management, and Department of Anatomy, Flinders University, Bedford Park SA, 5042, Australia. michael.e.jones@flinders.edu.au.|Department of Surgery, Flinders University, Bedford Park SA, 5042, Australia. mayn0020@flinders.edu.au.|Department of Surgery, Flinders University, Bedford Park SA, 5042, Australia. tingting.wang@flinders.edu.au.|Department of Surgery, Flinders University, Bedford Park SA, 5042, Australia. david.watson@flinders.edu.au.|Department of Surgery, Flinders University, Bedford Park SA, 5042, Australia. damian.hussey@flinders.edu.au.', 'Australia|Australia|Australia|Australia|Australia', 6, 'Algorithms|Calibration|DNA|Fluorescence|Humans|Indicator Dilution Techniques|Nucleic Acid Amplification Techniques|Real-Time Polymerase Chain Reaction|Regression Analysis', 'Journal Article', '10.1186/s12859-014-0372-4', '25492416', 'The polymerase chain reaction amplifies and quantifies small amounts of DNA. It is a cyclic process, during each cycle of which each strand of template DNA is copied with probability approaching one: the amount of DNA approximately doubles and this amount can be estimated fluorimetrically each cycle, producing a set of fluorescence values hereafter referred to as the amplification curve. Commonly the biological question of relevance is one of the ratio of DNA concentrations in two samples: a ratio that is deduced by comparing the two amplification curves, usually by way of a plot of fluorescence against cycle number. Central to this analysis is measuring the extent to which one amplification curve is shifted relative to the other, a measurement often accomplished by defining a threshold or quantification cycle, C q , for each curve: the fractional cycle number at which fluorescence reaches some threshold or at which some other criterion (maximum slope, maximum rate of change of slope) is satisfied. We propose an alternative where position is measured relative to a reference curve, position equates to the cycle shift which maximizes the correlation between the reference and the observed fluorescence sequence. A key parameter of the reference curve is obtained by fixed-point convergence.'),
(96459, 2014, 'bmc', 'Identifying and quantifying metabolites by scoring peaks of GC-MS data', 'Aggio, Raphael B M|Mayor, Arno|Reade, Sophie|Probert, Chris S J|Ruggiero, Katya', 'The University of Auckland, 3A Symonds Street, Auckland, 1142, New Zealand. ragg005@aucklanduni.ac.nz.|Department of Gastroenterology, Institute of Translational Medicine, University of Liverpool, Nuffield Building, Crown Street, L693BX Liverpool, UK. arnom@liverpool.ac.uk.|Department of Gastroenterology, Institute of Translational Medicine, University of Liverpool, Nuffield Building, Crown Street, L693BX Liverpool, UK. S.Reade@student.liverpool.ac.uk.|Department of Gastroenterology, Institute of Translational Medicine, University of Liverpool, Nuffield Building, Crown Street, L693BX Liverpool, UK. Chris.Probert@liverpool.ac.uk.|The University of Auckland, 3A Symonds Street, Auckland, 1142, New Zealand. k.ruggiero@auckland.ac.nz.', 'New Zealand|United Kingdom|United Kingdom|United Kingdom|New Zealand', 0, 'Algorithms|Animals|Feces|Female|Gas Chromatography-Mass Spectrometry|Male|Metabolome|Metabolomics|Mice|Mice, Inbred C57BL|Reference Standards|Software|Volatile Organic Compounds', 'Journal Article', '10.1186/s12859-014-0374-2', '25492550', 'Metabolomics is one of most recent omics technologies. It has been applied on fields such as food science, nutrition, drug discovery and systems biology. For this, gas chromatography-mass spectrometry (GC-MS) has been largely applied and many computational tools have been developed to support the analysis of metabolomics data. Among them, AMDIS is perhaps the most used tool for identifying and quantifying metabolites. However, AMDIS generates a high number of false-positives and does not have an interface amenable for high-throughput data analysis. Although additional computational tools have been developed for processing AMDIS results and to perform normalisations and statistical analysis of metabolomics data, there is not yet a single free software or package able to reliably identify and quantify metabolites analysed by GC-MS.'),
(96460, 2014, 'bmc', 'Efficient prediction of human protein-protein interactions at a global scale', 'Schoenrock, Andrew|Samanfar, Bahram|Pitre, Sylvain|Hooshyar, Mohsen|Jin, Ke|Phillips, Charles A|Wang, Hui|Phanse, Sadhna|Omidi, Katayoun|Gui, Yuan|Alamgir, Md|Wong, Alex|Barrenäs, Fredrik|Babu, Mohan|Benson, Mikael|Langston, Michael A|Green, James R|Dehne, Frank|Golshani, Ashkan', 'School of Computer Science, Carleton University, Ottawa, Canada. aschoenr@scs.carleton.ca.|Department of Biology, Carleton University, Ottawa, Canada. bahramsamanfar@gmail.com.|School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com.|Department of Biology, Carleton University, Ottawa, Canada. mohsen.hooshyar@gmail.com.|Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada. jin@utoronto.ca.|Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Tennessee, USA. cphillip@eecs.utk.edu.|Department of Pediatrics, Gothenburg University, Gothenburg, Sweden. hui.wang@gu.se.|Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada. srphanse@gmail.com.|Department of Biology, Carleton University, Ottawa, Canada. katayoun10@yahoo.com.|Department of Biology, Carleton University, Ottawa, Canada. yuangui2@hotmail.com.|Department of Biology, Carleton University, Ottawa, Canada. md_alamgir@yahoo.com.|Department of Biology, Carleton University, Ottawa, Canada. alex_wong@carleton.ca.|Department of Pediatrics, Gothenburg University, Gothenburg, Sweden. fredrik.barrenas@pediat.gu.se.|Department of Biochemistry, Research and Innovation Centre, University of Regina, Regina, Saskatchewan, Canada. mohanbabu_r@yahoo.com.|Department of Pediatrics, Gothenburg University, Gothenburg, Sweden. mikael.benson@liu.se.|Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Tennessee, USA. langston@eecs.utk.edu.|Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada. jrgreen@sce.carleton.ca.|School of Computer Science, Carleton University, Ottawa, Canada. frank@dehne.net.|Department of Biology, Carleton University, Ottawa, Canada. ashkan_golshani@carleton.ca.', 'Canada|Canada|Canada|Canada|Canada|United States|Sweden|Canada|Canada|Canada|Canada|Canada|Sweden|Canada|Sweden|', 0, 'Computational Biology|Genome, Human|Humans|Protein Interaction Mapping|Proteins|Proteome|Software', 'Journal Article', '10.1186/s12859-014-0383-1', '25492630', 'Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods.'),
(96461, 2014, 'bmc', 'COMBINE archive and OMEX format: one file to share all information to reproduce a modeling project', 'Bergmann, Frank T|Adams, Richard|Moodie, Stuart|Cooper, Jonathan|Glont, Mihai|Golebiewski, Martin|Hucka, Michael|Laibe, Camille|Miller, Andrew K|Nickerson, David P|Olivier, Brett G|Rodriguez, Nicolas|Sauro, Herbert M|Scharm, Martin|Soiland-Reyes, Stian|Waltemath, Dagmar|Yvon, Florent|Le Novère, Nicolas', 'Modelling of Biological Processes, BioQUANT/COS, University of Heidelberg, INF 267, Heidelberg, 69120, Germany. fbergman@caltech.edu.|ResearchSpace, 24 Fountainhall Road, Edinburgh, EH9 2LW, UK. ra22597@gmail.com.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. stuart.moodie@eightpillars.uk.com.|Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, Oxford, OX1 3QD, UK. jonathan.cooper@cs.ox.ac.uk.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. mglont@ebi.ac.uk.|HITS gGmbH, Schloss-Wolfsbrunnenweg 35, D-69118, Heidelberg, Germany. martin.golebiewski@h-its.org.|Computing and Mathematical sciences, California Institute of Technology, Pasadena, CA, 91125, USA. mhucka@caltech.edu.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. laibe@ebi.ac.uk.|Auckland Bioengineering Institute, University of Auckland, Private Bag 92019, Auckland Mail Centre, Auckland, 1142, New Zealand. ak.miller@auckland.ac.nz.|Auckland Bioengineering Institute, University of Auckland, Private Bag 92019, Auckland Mail Centre, Auckland, 1142, New Zealand. david.nickerson@gmail.com.|Systems Bioinformatics, VU University Amsterdam, Amsterdam, 1081 HV, The Netherlands. b.g.olivier@vu.nl.|Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK. nicolas.rodriguez@babraham.ac.uk.|Department of Bioengineering, University of Washington, Seattle, 98195, WA, USA. hsauro@u.washington.edu.|Systems Biology and Bioinformatics, University of Rostock, Ulmenstrasse 69, Rostock, 18057, Germany. martin.scharm@uni-rostock.de.|School of Computer Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK. soiland-reyes@cs.manchester.ac.uk.|Systems Biology and Bioinformatics, University of Rostock, Ulmenstrasse 69, Rostock, 18057, Germany. dagmar.waltemath@uni-rostock.de.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. florent@ebi.ac.uk.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. lenov@babraham.ac.uk.', 'Germany|United Kingdom|United Kingdom|United Kingdom|United Kingdom|Germany|United Kingdom|United Kingdom|New Zealand|New Zealand|Netherlands|United Kingdom|United Kingdom|Germany|United Kingdom|Germany|United Kingdom|United Kingdom', 35, 'Archives|Computational Biology|Computer Simulation|Databases, Nucleic Acid|Humans|Information Storage and Retrieval|Internet|Software', 'Journal Article', '10.1186/s12859-014-0369-z', '25494900', 'With the ever increasing use of computational models in the biosciences, the need to share models and reproduce the results of published studies efficiently and easily is becoming more important. To this end, various standards have been proposed that can be used to describe models, simulations, data or other essential information in a consistent fashion. These constitute various separate components required to reproduce a given published scientific result.'),
(96462, 2014, 'bmc', 'Masking as an effective quality control method for next-generation sequencing data analysis', 'Yun, Sajung|Yun, Sijung', 'European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. lenov@babraham.ac.uk.|Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA. yuns@mail.nih.gov.', 'United Kingdom|United Kingdom', 0, 'Animals|Caenorhabditis elegans|High-Throughput Nucleotide Sequencing|INDEL Mutation|Polymorphism, Single Nucleotide|Quality Control|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-014-0382-2', '25494997', 'Next generation sequencing produces base calls with low quality scores that can affect the accuracy of identifying simple nucleotide variation calls, including single nucleotide polymorphisms and small insertions and deletions. Here we compare the effectiveness of two data preprocessing methods, masking and trimming, and the accuracy of simple nucleotide variation calls on whole-genome sequence data from Caenorhabditis elegans. Masking substitutes low quality base calls with Ns (undetermined bases), whereas trimming removes low quality bases that results in a shorter read lengths.'),
(96463, 2014, 'bmc', 'AKE - the Accelerated k-mer Exploration web-tool for rapid taxonomic classification and visualization', 'Langenkämper, Daniel|Goesmann, Alexander|Nattkemper, Tim Wilhelm', 'Biodata Mining, Bielefeld University, Universitätsstraße 15, Bielefeld, Germany. dlangenk@cebitec.uni-bielefeld.de.|Bioinformatik und Systembiologie, Justus Liebig University, Düsternbrooker Weg 20, Gießen, Germany. Alexander.Goesmann@computational.bio.uni-giessen.de.|Biodata Mining, Bielefeld University, Universitätsstraße 15, Bielefeld, Germany. tim.nattkemper@uni-bielefeld.de.', 'Germany|Germany|Germany', 5, 'Algorithms|Animals|Artificial Intelligence|Cattle|Classification|Computational Biology|Computer Graphics|Humans|Macular Degeneration|Rumen', 'Journal Article', '10.1186/s12859-014-0384-0', '25495116', 'With the advent of low cost, fast sequencing technologies metagenomic analyses are made possible. The large data volumes gathered by these techniques and the unpredictable diversity captured in them are still, however, a challenge for computational biology.'),
(96464, 2014, 'bmc', 'Gene network inference using continuous time Bayesian networks: a comparative study and application to Th17 cell differentiation', 'Acerbi, Enzo|Zelante, Teresa|Narang, Vipin|Stella, Fabio', 'Singapore Immunology Network (SIgN), A*STAR, 8A Biomedical Grove, Immunos Building, Level 4 138648, Singapore. enzoace@gmail.com.|Singapore Immunology Network (SIgN), A*STAR, 8A Biomedical Grove, Immunos Building, Level 4 138648, Singapore. enzoace@gmail.com.|Singapore Immunology Network (SIgN), A*STAR, 8A Biomedical Grove, Immunos Building, Level 4 138648, Singapore. enzoace@gmail.com.|Singapore Immunology Network (SIgN), A*STAR, 8A Biomedical Grove, Immunos Building, Level 4 138648, Singapore. enzoace@gmail.com.', 'Singapore|Singapore|Singapore|Singapore', 18, 'Animals|Bayes Theorem|Cell Differentiation|Gene Regulatory Networks|Interleukin-23|Interleukin-6|Mice|Th17 Cells|Transforming Growth Factor beta1', 'Journal Article', '10.1186/s12859-014-0387-x', '25495206', 'Dynamic aspects of gene regulatory networks are typically investigated by measuring system variables at multiple time points. Current state-of-the-art computational approaches for reconstructing gene networks directly build on such data, making a strong assumption that the system evolves in a synchronous fashion at fixed points in time. However, nowadays omics data are being generated with increasing time course granularity. Thus, modellers now have the possibility to represent the system as evolving in continuous time and to improve the models expressiveness.'),
(96465, 2014, 'bmc', 'SPoRE: a mathematical model to predict double strand breaks and axis protein sites in meiosis', 'Champeimont, Raphaël|Carbone, Alessandra', 'Singapore Immunology Network (SIgN), A*STAR, 8A Biomedical Grove, Immunos Building, Level 4 138648, Singapore. enzoace@gmail.com.|Sorbonne Universités, UPMC Univ Paris 06, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative, Paris F-75006, France. Alessandra.Carbone@lip6.fr.', 'Singapore|France', 0, 'Base Composition|Chromosomes|DNA Breaks, Double-Stranded|Genomics|Meiosis|Models, Biological|Recombination, Genetic|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Yeasts', 'Journal Article', '10.1186/s12859-014-0391-1', '25495332', 'Meiotic recombination between homologous chromosomes provides natural combinations of genetic variations and is a main driving force of evolution. It is initiated via programmed DNA double-strand breaks (DSB) and involves a specific axial chromosomal structure. So far, recombination regions have been mainly determined by experiments, both expensive and time-consuming.'),
(96466, 2014, 'bmc', 'MPAgenomics: an R package for multi-patient analysis of genomic markers', 'Grimonprez, Quentin|Celisse, Alain|Blanck, Samuel|Cheok, Meyling|Figeac, Martin|Marot, Guillemette', 'MODAL team, Inria Lille-Nord Europe, Villeneuve-dAscq, France. quentin.grimonprez@inria.fr.|MODAL team, Inria Lille-Nord Europe, Villeneuve-dAscq, France. quentin.grimonprez@inria.fr.|MODAL team, Inria Lille-Nord Europe, Villeneuve-dAscq, France. quentin.grimonprez@inria.fr.|MODAL team, Inria Lille-Nord Europe, Villeneuve-dAscq, France. quentin.grimonprez@inria.fr.|MODAL team, Inria Lille-Nord Europe, Villeneuve-dAscq, France. quentin.grimonprez@inria.fr.|MODAL team, Inria Lille-Nord Europe, Villeneuve-dAscq, France. quentin.grimonprez@inria.fr.', 'France|France|France|France|France|France', 2, 'DNA Copy Number Variations|Genetic Markers|High-Throughput Nucleotide Sequencing|Humans|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-014-0394-y', '25495450', 'Last generations of Single Nucleotide Polymorphism (SNP) arrays allow to study copy-number variations in addition to genotyping measures.'),
(96467, 2014, 'bmc', 'solGS: a web-based tool for genomic selection', 'Tecle, Isaak Y|Edwards, Jeremy D|Menda, Naama|Egesi, Chiedozie|Rabbi, Ismail Y|Kulakow, Peter|Kawuki, Robert|Jannink, Jean-Luc|Mueller, Lukas A', 'Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, USA. iyt2@cornell.edu.|Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, USA. iyt2@cornell.edu.|Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, USA. iyt2@cornell.edu.|Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, USA. iyt2@cornell.edu.|Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, USA. iyt2@cornell.edu.|Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, USA. iyt2@cornell.edu.|Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, USA. iyt2@cornell.edu.|Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, USA. iyt2@cornell.edu.|Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, USA. iyt2@cornell.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Breeding|Genomics|Internet|Manihot|Quantitative Trait Loci|Software', 'Journal Article', '10.1186/s12859-014-0398-7', '25495537', 'Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders.'),
(96468, 2014, 'bmc', 'Exact reconstruction of gene regulatory networks using compressive sensing', 'Chang, Young Hwan|Gray, Joe W|Tomlin, Claire J', 'Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, 94720, CA, USA. yhchang@berkeley.edu.|Department of Biomedical Engineering and the Center for Spatial Systems Biomedicine, Oregon Health and Science University, Portland, OR, USA. grayjo@ohsu.edu.|Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, 94720, CA, USA. tomlin@eecs.berkeley.edu.', 'United States|United States|United States', 23, 'Algorithms|Breast Neoplasms|Computational Biology|Female|Gene Expression Profiling|Gene Regulatory Networks|Humans|Models, Biological|Signal Transduction|Time Factors', 'Journal Article', '10.1186/s12859-014-0400-4', '25495633', 'We consider the problem of reconstructing a gene regulatory network structure from limited time series gene expression data, without any a priori knowledge of connectivity. We assume that the network is sparse, meaning the connectivity among genes is much less than full connectivity. We develop a method for network reconstruction based on compressive sensing, which takes advantage of the networks sparseness.'),
(96469, 2014, 'bmc', 'QUDeX-MS: hydrogen/deuterium exchange calculation for mass spectra with resolved isotopic fine structure', 'Salisbury, Joseph P|Liu, Qian|Agar, Jeffrey N', 'Departments of Chemistry and Chemical Biology and Pharmaceutical Sciences and Barnett Institute of Chemical and Biological Analysis, Northeastern University, 360 Huntington Avenue, Boston, MA, 02115, USA. j.salisbury@neu.edu.|Departments of Chemistry and Chemical Biology and Pharmaceutical Sciences and Barnett Institute of Chemical and Biological Analysis, Northeastern University, 360 Huntington Avenue, Boston, MA, 02115, USA. qianl2008@gmail.com.|Departments of Chemistry and Chemical Biology and Pharmaceutical Sciences and Barnett Institute of Chemical and Biological Analysis, Northeastern University, 360 Huntington Avenue, Boston, MA, 02115, USA. j.agar@neu.edu.', 'United States|United States|United States', 9, 'Carbon Isotopes|Deuterium|Deuterium Exchange Measurement|Humans|Hydrogen|Isotope Labeling|Mass Spectrometry|Peptide Fragments|Proteins|Software', 'Journal Article', '10.1186/s12859-014-0403-1', '25495703', 'Hydrogen/deuterium exchange (HDX) coupled to mass spectrometry permits analysis of structure, dynamics, and molecular interactions of proteins. HDX mass spectrometry is confounded by deuterium exchange-associated peaks overlapping with peaks of heavy, natural abundance isotopes, such as carbon-13. Recent studies demonstrated that high-performance mass spectrometers could resolve isotopic fine structure and eliminate this peak overlap, allowing direct detection and quantification of deuterium incorporation.'),
(96470, 2014, 'bmc', 'Methodology for the inference of gene function from phenotype data', 'Ascensao, Joao A|Dolan, Mary E|Hill, David P|Blake, Judith A', 'The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, USA. Joao.Ascensao@rice.edu.|The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, USA. Mary.Dolan@jax.org.|The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, USA. David.Hill@jax.org.|The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, USA. Judith.Blake@jax.org.', 'United States|United States|United States|United States', 0, 'Algorithms|Animals|Databases, Factual|Gene Regulatory Networks|Mice|Molecular Sequence Annotation|Phenotype', 'Journal Article', '10.1186/s12859-014-0405-z', '25495798', 'Biomedical ontologies are increasingly instrumental in the advancement of biological research primarily through their use to efficiently consolidate large amounts of data into structured, accessible sets. However, ontology development and usage can be hampered by the segregation of knowledge by domain that occurs due to independent development and use of the ontologies. The ability to infer data associated with one ontology to data associated with another ontology would prove useful in expanding information content and scope. We here focus on relating two ontologies: the Gene Ontology (GO), which encodes canonical gene function, and the Mammalian Phenotype Ontology (MP), which describes non-canonical phenotypes, using statistical methods to suggest GO functional annotations from existing MP phenotype annotations. This work is in contrast to previous studies that have focused on inferring gene function from phenotype primarily through lexical or semantic similarity measures.'),
(96471, 2014, 'bmc', 'CLAST: CUDA implemented large-scale alignment search tool', 'Yano, Masahiro|Mori, Hiroshi|Akiyama, Yutaka|Yamada, Takuji|Kurokawa, Ken', 'Department of Biological Information, Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, 2-12-1 M6-3, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan. masayano@bio.titech.ac.jp.|Department of Biological Information, Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, 2-12-1 M6-3, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan. hmori@bio.titech.ac.jp.|Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan. akiyama@cs.titech.ac.jp.|Department of Biological Information, Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, 2-12-1 M6-3, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan. takuji@bio.titech.ac.jp.|Department of Biological Information, Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, 2-12-1 M6-3, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan. ken@bio.titech.ac.jp.', 'Japan|Japan|Japan|Japan|Japan', 7, 'Algorithms|Computers|Databases, Nucleic Acid|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Metagenomics|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/s12859-014-0406-y', '25495907', 'Metagenomics is a powerful methodology to study microbial communities, but it is highly dependent on nucleotide sequence similarity searching against sequence databases. Metagenomic analyses with next-generation sequencing technologies produce enormous numbers of reads from microbial communities, and many reads are derived from microbes whose genomes have not yet been sequenced, limiting the usefulness of existing sequence similarity search tools. Therefore, there is a clear need for a sequence similarity search tool that can rapidly detect weak similarity in large datasets.'),
(96472, 2014, 'bmc', 'A statistical approach to quantification of genetically modified organisms (GMO) using frequency distributions', 'Gerdes, Lars|Busch, Ulrich|Pecoraro, Sven', 'Bavarian Health and Food Safety Authority (LGL), Veterinaerstr. 2, 85764, Oberschleissheim, Germany. lars.gerdes@lgl.bayern.de.|Bavarian Health and Food Safety Authority (LGL), Veterinaerstr. 2, 85764, Oberschleissheim, Germany. ulrich.busch@lgl.bayern.de.|Bavarian Health and Food Safety Authority (LGL), Veterinaerstr. 2, 85764, Oberschleissheim, Germany. sven.pecoraro@lgl.bayern.de.', 'Germany|Germany|Germany', 3, 'DNA, Plant|Genome, Plant|Organisms, Genetically Modified|Real-Time Polymerase Chain Reaction|Reference Standards|Transgenes|Zea mays', 'Journal Article', '10.1186/s12859-014-0407-x', '25496015', 'According to Regulation (EU) No 619/2011, trace amounts of non-authorised genetically modified organisms (GMO) in feed are tolerated within the EU if certain prerequisites are met. Tolerable traces must not exceed the so-called minimum required performance limit (MRPL), which was defined according to the mentioned regulation to correspond to 0.1% mass fraction per ingredient. Therefore, not yet authorised GMO (and some GMO whose approvals have expired) have to be quantified at very low level following the qualitative detection in genomic DNA extracted from feed samples. As the results of quantitative analysis can imply severe legal and financial consequences for producers or distributors of feed, the quantification results need to be utterly reliable.'),
(96473, 2014, 'bmc', 'Kiwi: a tool for integration and visualization of network topology and gene-set analysis', 'Väremo, Leif|Gatto, Francesco|Nielsen, Jens', 'Bavarian Health and Food Safety Authority (LGL), Veterinaerstr. 2, 85764, Oberschleissheim, Germany. sven.pecoraro@lgl.bayern.de.|Bavarian Health and Food Safety Authority (LGL), Veterinaerstr. 2, 85764, Oberschleissheim, Germany. sven.pecoraro@lgl.bayern.de.|Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg 412 96, Sweden. nielsenj@chalmers.se.', 'Germany|Germany|Sweden', 8, 'Adenocarcinoma|Adenocarcinoma of Lung|Animals|Gene Regulatory Networks|Genomics|Heterografts|Humans|Lung|Lung Neoplasms|Metabolic Networks and Pathways|Mice|Neoplasm Transplantation|Software|ras Proteins', 'Journal Article', '10.1186/s12859-014-0408-9', '25496126', 'The analysis of high-throughput data in biology is aided by integrative approaches such as gene-set analysis. Gene-sets can represent well-defined biological entities (e.g. metabolites) that interact in networks (e.g. metabolic networks), to exert their function within the cell. Data interpretation can benefit from incorporating the underlying network, but there are currently no optimal methods that link gene-set analysis and network structures.'),
(96474, 2014, 'bmc', 'Comparisons of computational methods for differential alternative splicing detection using RNA-seq in plant systems', 'Liu, Ruolin|Loraine, Ann E|Dickerson, Julie A', 'Department of Electrical and Computational Engineering, Iowa State University, Howe Hall, Ames, 50011-3060, USA. ruolin@iastate.edu.|Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, North Carolina Research Campus, 600 Laureate Way, Kannapolis, 28081, NC, USA. Ann.Loraine@uncc.edu.|Department of Electrical and Computational Engineering, Iowa State University, Howe Hall, Ames, 50011-3060, USA. julied@iastate.edu.', 'United States|United States|United States', 46, 'Alternative Splicing|Animals|Arabidopsis|Computational Biology|Genome, Plant|High-Throughput Nucleotide Sequencing|Humans|Introns|Mice|Polymerase Chain Reaction|RNA, Plant|Sequence Analysis, RNA|Software', 'Comparative Study', '10.1186/s12859-014-0364-4', '25511303', 'Alternative Splicing (AS) as a post-transcription regulation mechanism is an important application of RNA-seq studies in eukaryotes. A number of software and computational methods have been developed for detecting AS. Most of the methods, however, are designed and tested on animal data, such as human and mouse. Plants genes differ from those of animals in many ways, e.g., the average intron size and preferred AS types. These differences may require different computational approaches and raise questions about their effectiveness on plant data. The goal of this paper is to benchmark existing computational differential splicing (or transcription) detection methods so that biologists can choose the most suitable tools to accomplish their goals.'),
(96475, 2014, 'bmc', 'Identification of metabolites from 2D (1)H-(13)C HSQC NMR using peak correlation plots', 'Öman, Tommy|Tessem, May-Britt|Bathen, Tone F|Bertilsson, Helena|Angelsen, Anders|Hedenström, Mattias|Andreassen, Trygve', 'Department of Chemistry, Umeå University, Umeå, Sweden. tommy.oman@ltu.se.|MI Lab, Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway. may-britt.tessem@ntnu.no.|MI Lab, Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway. tone.f.bathen@ntnu.no.|Department of Urology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway. helena.bertilsson@ntnu.no.|Department of Urology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway. anders.angelsen@ntnu.no.|Department of Chemistry, Umeå University, Umeå, Sweden. mattias.hedenstrom@chem.umu.se.|MR Core Facility, Department of Circulation and Medical Imaging, NTNU, Trondheim, Norway. trygve.andreassen@ntnu.no.', 'Sweden|Norway|Norway|Norway|Norway|Sweden|Norway', 0, 'Carbon Isotopes|Databases, Chemical|Humans|Magnetic Resonance Spectroscopy|Male|Metabolomics|Palpation|Prostate|Urinalysis', 'Journal Article', '10.1186/s12859-014-0413-z', '25511422', 'Identification of individual components in complex mixtures is an important and sometimes daunting task in several research areas like metabolomics and natural product studies. NMR spectroscopy is an excellent technique for analysis of mixtures of organic compounds and gives a detailed chemical fingerprint of most individual components above the detection limit. For the identification of individual metabolites in metabolomics, correlation or covariance between peaks in (1)H NMR spectra has previously been successfully employed. Similar correlation of 2D (1)H-(13)C Heteronuclear Single Quantum Correlation spectra was recently applied to investigate the structure of heparine. In this paper, we demonstrate how a similar approach can be used to identify metabolites in human biofluids (post-prostatic palpation urine).'),
(96476, 2014, 'bmc', 'DFBAlab: a fast and reliable MATLAB code for dynamic flux balance analysis', 'Gomez, Jose A|Höffner, Kai|Barton, Paul I', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. jagomezr@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. hoeffner@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States', 0, 'Algorithms|Bacteria|Bioreactors|Biotechnology|Computer Simulation|Metabolic Networks and Pathways|Models, Theoretical|Systems Biology', 'Journal Article', '10.1186/s12859-014-0409-8', '25519981', 'Dynamic Flux Balance Analysis (DFBA) is a dynamic simulation framework for biochemical processes. DFBA can be performed using different approaches such as static optimization (SOA), dynamic optimization (DOA), and direct approaches (DA). Few existing simulators address the theoretical and practical challenges of nonunique exchange fluxes or infeasible linear programs (LPs). Both are common sources of failure and inefficiencies for these simulators.'),
(96477, 2014, 'bmc', 'InCoB2014: bioinformatics to tackle the data to knowledge challenge Introduction', 'Ranganathan, Shoba|Tan, Tin|Schönbach, Christian', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States', 0, 'Biomedical Research|Computational Biology|Congresses as Topic|Databases, Factual|Humans|Informatics|Knowledge|Proteome|Software', 'Introductory Journal Article', '10.1186/1471-2105-15-S16-I1', '25521055', 'Since 2006, the International Conference on Bioinformatics (InCoB) has been publishing selected papers in BMC Bioinformatics. Papers within the scope of the journal from the 13th InCoB July 31-2 August, 2014 in Sydney, Australia have been compiled in this supplement. These span protein and proteome informatics, structural bioinformatics, software development and bioimaging to pharmacoinformatics and disease informatics, representing the breadth of bioinformatics research in the Asia-Pacific. '),
(96478, 2014, 'bmc', 'Combining spatial and chemical information for clustering pharmacophores', 'Zhou, Lingxiao|Griffith, Renate|Gaeta, Bruno', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States', 0, 'Antigen-Antibody Complex|Binding Sites|Cluster Analysis|Databases, Chemical|Globulins|Humans|Models, Molecular|Molecular Structure|Phylogeny|Protein Binding|Steroids', 'Journal Article', '10.1186/1471-2105-15-S16-S5', '25521061', 'A pharmacophore model consists of a group of chemical features arranged in three-dimensional space that can be used to represent the biological activities of the described molecules. Clustering of molecular interactions of ligands on the basis of their pharmacophore similarity provides an approach for investigating how diverse ligands can bind to a specific receptor site or different receptor sites with similar or dissimilar binding affinities. However, efficient clustering of pharmacophore models in three-dimensional space is currently a challenge.'),
(96479, 2014, 'bmc', 'FMAj: a tool for high content analysis of muscle dynamics in Drosophila metamorphosis', 'Kuleesha, Yadav|Puah, Wee Choo|Lin, Feng|Wasser, Martin', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States|United States', 8, 'Animals|Autophagy-Related Proteins|Cell Nucleus|Drosophila Proteins|Drosophila melanogaster|Female|Gene Expression Regulation, Developmental|Image Processing, Computer-Assisted|Imaging, Three-Dimensional|Larva|Male|Membrane Proteins|Metamorphosis, Biological|Microscopy, Confocal|Muscle Development|Muscle, Skeletal|Phenotype|RNA Interference|RNA, Small Interfering|Software', 'Journal Article', '10.1186/1471-2105-15-S16-S6', '25521203', 'During metamorphosis in Drosophila melanogaster, larval muscles undergo two different developmental fates, one population is removed by cell death, while the other persistent subset undergoes morphological remodeling and survives to adulthood. Thanks to the ability to perform live imaging of muscle development in transparent pupae and the power of genetics, metamorphosis in Drosophila can be used as a model to study the regulation of skeletal muscle mass. However, time-lapse microscopy generates sizeable image data that require new tools for high throughput image analysis.'),
(96480, 2014, 'bmc', 'Characterization and identification of protein O-GlcNAcylation sites with substrate specificity', 'Wu, Hsin-Yi|Lu, Cheng-Tsung|Kao, Hui-Ju|Chen, Yi-Ju|Chen, Yu-Ju|Lee, Tzong-Yi', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States|United States|United States|United States', 0, 'Acetylglucosamine|Amino Acid Motifs|Computational Biology|Glycosylation|Humans|Mass Spectrometry|Models, Molecular|Phosphorylation|Protein Processing, Post-Translational|Proteins|Proteomics|Signal Transduction|Substrate Specificity|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-15-S16-S1', '25521204', 'Protein O-GlcNAcylation, involving the attachment of single N-acetylglucosamine (GlcNAc) to the hydroxyl group of serine or threonine residues. Elucidation of O-GlcNAcylation sites on proteins is required in order to decipher its crucial roles in regulating cellular processes and aid in drug design. With an increasing number of O-GlcNAcylation sites identified by mass spectrometry (MS)-based proteomics, several methods have been proposed for the computational identification of O-GlcNAcylation sites. However, no development that focuses on the investigation of O-GlcNAcylated substrate motifs has existed. Thus, we were motivated to design a new method for the identification of protein O-GlcNAcylation sites with the consideration of substrate site specificity.'),
(96481, 2014, 'bmc', 'Bhageerath-H: a homology/ab initio hybrid server for predicting tertiary structures of monomeric soluble proteins', 'Jayaram, B|Dhingra, Priyanka|Mishra, Avinash|Kaushik, Rahul|Mukherjee, Goutam|Singh, Ankita|Shekhar, Shashank', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States|United States|United States|United States|United States', 26, 'Computational Biology|Humans|Models, Theoretical|Protein Structure, Tertiary|Proteins|Quantum Theory|Software', 'Journal Article', '10.1186/1471-2105-15-S16-S7', '25521245', 'The advent of human genome sequencing project has led to a spurt in the number of protein sequences in the databanks. Success of structure based drug discovery severely hinges on the availability of structures. Despite significant progresses in the area of experimental protein structure determination, the sequence-structure gap is continually widening. Data driven homology based computational methods have proved successful in predicting tertiary structures for sequences sharing medium to high sequence similarities. With dwindling similarities of query sequences, advanced homology/ ab initio hybrid approaches are being explored to solve structure prediction problem. Here we describe Bhageerath-H, a homology/ ab initio hybrid software/server for predicting protein tertiary structures with advancing drug design attempts as one of the goals.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96482, 2014, 'bmc', 'iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation', 'Yang, Tzu-Hsien|Chang, Hong-Tsun|Hsiao, Eric Sl|Sun, Juo-Ling|Wang, Chung-Ching|Wu, Hsin-Yi|Liao, Pao-Chi|Wu, Wei-Sheng', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States', 4, 'Adenocarcinoma|Alkaline Phosphatase|Chromatography, Liquid|Dasatinib|Humans|Immunoprecipitation|Lung Neoplasms|Phosphopeptides|Protein Kinase Inhibitors|Proteome|Proteomics|Pyrimidines|Signal Transduction|Software|Tandem Mass Spectrometry|Thiazoles|Tumor Cells, Cultured', 'Comparative Study', '10.1186/1471-2105-15-S16-S10', '25521246', 'Comprehensive characterization of the phosphoproteome in living cells is critical in signal transduction research. But the low abundance of phosphopeptides among the total proteome in cells remains an obstacle in mass spectrometry-based proteomic analysis. To provide a solution, an alternative analytic strategy to confidently identify phosphorylated peptides by using the alkaline phosphatase (AP) treatment combined with high-resolution mass spectrometry was provided. While the process is applicable, the key integration along the pipeline was mostly done by tedious manual work.'),
(96483, 2014, 'bmc', 'Protein inter-domain linker prediction using Random Forest and amino acid physiochemical properties', 'Shatnawi, Maad|Zaki, Nazar|Yoo, Paul D', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Amino Acids|Chemical Phenomena|Datasets as Topic|Humans|Hydrophobic and Hydrophilic Interactions|Models, Statistical|Molecular Sequence Data|Proteins|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-15-S16-S8', '25521329', 'Protein chains are generally long and consist of multiple domains. Domains are distinct structural units of a protein that can evolve and function independently. The accurate prediction of protein domain linkers and boundaries is often regarded as the initial step of protein tertiary structure and function predictions. Such information not only enhances protein-targeted drug development but also reduces the experimental cost of protein analysis by allowing researchers to work on a set of smaller and independent units. In this study, we propose a novel and accurate domain-linker prediction approach based on protein primary structure information only. We utilize a nature-inspired machine-learning model called Random Forest along with a novel domain-linker profile that contains physiochemical and domain-linker information of amino acid sequences.'),
(96484, 2014, 'bmc', 'Genetic algorithm with logistic regression for prediction of progression to Alzheimers disease', 'Johnson, Piers|Vandewater, Luke|Wilson, William|Maruff, Paul|Savage, Greg|Graham, Petra|Macaulay, Lance S|Ellis, Kathryn A|Szoeke, Cassandra|Martins, Ralph N|Rowe, Christopher C|Masters, Colin L|Ames, David|Zhang, Ping', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 33, 'Algorithms|Alzheimer Disease|Cognitive Dysfunction|Computer Simulation|Data Interpretation, Statistical|Disease Progression|Humans|Logistic Models|ROC Curve|Risk Factors', 'Journal Article', '10.1186/1471-2105-15-S16-S11', '25521394', 'Assessment of risk and early diagnosis of Alzheimers disease (AD) is a key to its prevention or slowing the progression of the disease. Previous research on risk factors for AD typically utilizes statistical comparison tests or stepwise selection with regression models. Outcomes of these methods tend to emphasize single risk factors rather than a combination of risk factors. However, a combination of factors, rather than any one alone, is likely to affect disease development. Genetic algorithms (GA) can be useful and efficient for searching a combination of variables for the best achievement (eg. accuracy of diagnosis), especially when the search space is large, complex or poorly understood, as in the case in prediction of AD development.'),
(96485, 2014, 'bmc', 'IFACEwat: the interfacial water-implemented re-ranking algorithm to improve the discrimination of near native structures for protein rigid docking', 'Su, Chinh|Nguyen, Thuy-Diem|Zheng, Jie|Kwoh, Chee-Keong', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States|United States', 2, 'Algorithms|Antigen-Antibody Complex|Computer Simulation|Humans|Hydrogen Bonding|Models, Molecular|Protein Binding|Protein Conformation|Proteins|Software|Water', 'Journal Article', '10.1186/1471-2105-15-S16-S9', '25521441', 'Protein-protein docking is an in silico method to predict the formation of protein complexes. Due to limited computational resources, the protein-protein docking approach has been developed under the assumption of rigid docking, in which one of the two protein partners remains rigid during the protein associations and water contribution is ignored or implicitly presented. Despite obtaining a number of acceptable complex predictions, it seems to-date that most initial rigid docking algorithms still find it difficult or even fail to discriminate successfully the correct predictions from the other incorrect or false positive ones. To improve the rigid docking results, re-ranking is one of the effective methods that help re-locate the correct predictions in top high ranks, discriminating them from the other incorrect ones.'),
(96486, 2014, 'bmc', 'Improving protein fold recognition using the amalgamation of evolutionary-based and structural based information', 'Paliwal, Kuldip K|Sharma, Alok|Lyons, James|Dehzangi, Abdollah', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States|United States', 0, 'Algorithms|Databases, Factual|Datasets as Topic|Evolution, Molecular|Humans|Position-Specific Scoring Matrices|Protein Folding|Protein Structure, Secondary|Proteins|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-15-S16-S12', '25521502', 'Deciphering three dimensional structure of a protein sequence is a challenging task in biological science. Protein fold recognition and protein secondary structure prediction are transitional steps in identifying the three dimensional structure of a protein. For protein fold recognition, evolutionary-based information of amino acid sequences from the position specific scoring matrix (PSSM) has been recently applied with improved results. On the other hand, the SPINE-X predictor has been developed and applied for protein secondary structure prediction. Several reported methods for protein fold recognition have only limited accuracy. In this paper, we have developed a strategy of combining evolutionary-based information (from PSSM) and predicted secondary structure using SPINE-X to improve protein fold recognition. The strategy is based on finding the probabilities of amino acid pairs (AAP). The proposed method has been tested on several protein benchmark datasets and an improvement of 8.9% recognition accuracy has been achieved. We have achieved, for the first time over 90% and 75% prediction accuracies for sequence similarity values below 40% and 25%, respectively. We also obtain 90.6% and 77.0% prediction accuracies, respectively, for the Extended Ding and Dubchak and Taguchi and Gromiha benchmark protein fold recognition datasets widely used for in the literature. '),
(96487, 2014, 'bmc', 'Computational identification of novel natural inhibitors of glucagon receptor for checking type II diabetes mellitus', 'Grover, Sonam|Dhanjal, Jaspreet Kaur|Goyal, Sukriti|Grover, Abhinav|Sundar, Durai', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States|United States|United States', 13, 'Blood Glucose|Computational Biology|Diabetes Mellitus, Type 2|Glucagon|High-Throughput Screening Assays|Humans|Liver|Molecular Dynamics Simulation|Peptide Library|Pharmaceutical Preparations|Protein Binding|Protein Conformation|Pyrazoles|Receptors, Glucagon|beta-Alanine', 'Journal Article', '10.1186/1471-2105-15-S16-S13', '25521597', 'Interaction of the small peptide hormone glucagon with glucagon receptor (GCGR) stimulates the release of glucose from the hepatic cells during fasting, hence GCGR performs a significant function in glucose homeostasis. Inhibiting the interaction between glucagon and its receptor has been reported to control hepatic glucose overproduction and thus GCGR has evolved as an attractive therapeutic target for the treatment of type II diabetes mellitus.'),
(96488, 2014, 'bmc', 'Introducing TreeCollapse: a novel greedy algorithm to solve the cophylogeny reconstruction problem', 'Drinkwater, Benjamin|Charleston, Michael A', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States', 9, 'Algorithms|Biological Evolution|Computational Biology|Humans|Models, Theoretical|Phylogeny', 'Journal Article', '10.1186/1471-2105-15-S16-S14', '25521705', 'Cophylogeny mapping is used to uncover deep coevolutionary associations between two or more phylogenetic histories at a macro coevolutionary scale. As cophylogeny mapping is NP-Hard, this technique relies heavily on heuristics to solve all but the most trivial cases. One notable approach utilises a metaheuristic to search only a subset of the exponential number of fixed node orderings possible for the phylogenetic histories in question. This is of particular interest as it is the only known heuristic that guarantees biologically feasible solutions. This has enabled research to focus on larger coevolutionary systems, such as coevolutionary associations between figs and their pollinator wasps, including over 200 taxa. Although able to converge on solutions for problem instances of this size, a reduction from the current cubic running time is required to handle larger systems, such as Wolbachia and their insect hosts.'),
(96489, 2014, 'bmc', 'Verification and validation of bioinformatics software without a gold standard: a case study of BWA and Bowtie', 'Giannoulatou, Eleni|Park, Shin-Ho|Humphreys, David T|Ho, Joshua W K', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States|United States', 0, 'Computational Biology|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-15-S16-S15', '25521810', 'Bioinformatics software quality assurance is essential in genomic medicine. Systematic verification and validation of bioinformatics software is difficult because it is often not possible to obtain a realistic gold standard for systematic evaluation. Here we apply a technique that originates from the software testing literature, namely Metamorphic Testing (MT), to systematically test three widely used short-read sequence alignment programs.'),
(96490, 2014, 'bmc', 'Supervised prediction of drug-induced nephrotoxicity based on interleukin-6 and -8 expression levels', 'Su, Ran|Li, Yao|Zink, Daniele|Loo, Lit-Hsin', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States|United States', 20, 'Algorithms|Artificial Intelligence|Bayes Theorem|Humans|Interleukin-6|Interleukin-8|Kidney Diseases|Kidney Tubules, Proximal|Models, Theoretical|Pharmaceutical Preparations|ROC Curve|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-15-S16-S16', '25521947', 'Drug-induced nephrotoxicity causes acute kidney injury and chronic kidney diseases, and is a major reason for late-stage failures in the clinical trials of new drugs. Therefore, early, pre-clinical prediction of nephrotoxicity could help to prioritize drug candidates for further evaluations, and increase the success rates of clinical trials. Recently, an in vitro model for predicting renal-proximal-tubular-cell (PTC) toxicity based on the expression levels of two inflammatory markers, interleukin (IL)-6 and -8, has been described. However, this and other existing models usually use linear and manually determined thresholds to predict nephrotoxicity. Automated machine learning algorithms may improve these models, and produce more accurate and unbiased predictions.'),
(96491, 2014, 'bmc', 'An integrative model of multi-organ drug-induced toxicity prediction using gene-expression data', 'Kim, Jinwoo|Shin, Miyoung', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States', 9, 'Drug-Related Side Effects and Adverse Reactions|Humans|Kidney|Liver|Microarray Analysis|Models, Statistical|Systems Integration|Transcriptome', 'Journal Article', '10.1186/1471-2105-15-S16-S2', '25522097', 'In practice, some drugs produce a number of negative biological effects that can mitigate their effectiveness as a remedy. To address this issue, several studies have been performed for the prediction of drug-induced toxicity from gene-expression data, and a significant amount of work has been done on predicting limited drug-induced symptoms or single-organ toxicity. Since drugs often lead to some injuries in several organs like liver or kidney, however, it would be very useful to forecast the drug-induced injuries for multiple organs. Therefore, in this work, our aim was to develop a multi-organ toxicity prediction model using an integrative model of gene-expression data.'),
(96492, 2014, 'bmc', 'Use B-factor related features for accurate classification between protein binding interfaces and crystal packing contacts', 'Liu, Qian|Li, Zhenhua|Li, Jinyan', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States', 30, 'Computational Biology|Crystallography, X-Ray|Databases, Protein|Humans|Models, Molecular|Protein Binding|Protein Conformation|Proteins|Software', 'Journal Article', '10.1186/1471-2105-15-S16-S3', '25522196', 'Distinction between true protein interactions and crystal packing contacts is important for structural bioinformatics studies to respond to the need of accurate classification of the rapidly increasing protein structures. There are many unannotated crystal contacts and there also exist false annotations in this rapidly expanding volume of data. Previous tools have been proposed to address this problem. However, challenging issues still remain, such as low performance when the training and test data contain mixed interfaces having diverse sizes of contact areas.'),
(96493, 2014, 'bmc', 'SCMHBP: prediction and analysis of heme binding proteins using propensity scores of dipeptides', 'Liou, Yi-Fan|Charoenkwan, Phasit|Srinivasulu, Yerukala|Vasylenko, Tamara|Lai, Shih-Chung|Lee, Hua-Chin|Chen, Yi-Hsiung|Huang, Hui-Ling|Ho, Shinn-Ying', 'Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.|Process Systems Engineering Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. pib@mit.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 16, 'Bayes Theorem|Binding Sites|Carrier Proteins|Databases, Protein|Dipeptides|Heme|Hemeproteins|Humans|Hydrophobic and Hydrophilic Interactions|Ligands|Propensity Score|Protein Conformation|Software|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-15-S16-S4', '25522279', 'Heme binding proteins (HBPs) are metalloproteins that contain a heme ligand (an iron-porphyrin complex) as the prosthetic group. Several computational methods have been proposed to predict heme binding residues and thereby to understand the interactions between heme and its host proteins. However, few in silico methods for identifying HBPs have been proposed.'),
(96494, 2014, 'bmc', 'EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression', 'Lian, Yao|Ge, Meng|Pan, Xian-Ming', 'The Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, Beijing, 100084, China. lianyao1112@gmail.com.|CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China. gemeng@big.ac.cn.|The Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, Beijing, 100084, China. pan-xm@mail.tsinghua.edu.cn.', 'China|China|China', 18, 'Algorithms|B-Lymphocytes|Biomedical Research|Computational Biology|Epitope Mapping|Epitopes, B-Lymphocyte|Humans|Linear Models|ROC Curve', 'Journal Article', '10.1186/s12859-014-0414-y', '25523327', 'B-cell epitopes have been studied extensively due to their immunological applications, such as peptide-based vaccine development, antibody production, and disease diagnosis and therapy. Despite several decades of research, the accurate prediction of linear B-cell epitopes has remained a challenging task.'),
(96495, 2014, 'bmc', 'Interactive visual exploration of overlapping similar structures for three-dimensional microscope images', 'Nakao, Megumi|Takemoto, Shintaro|Sugiura, Tadao|Sawada, Kazuaki|Kawakami, Ryosuke|Nemoto, Tomomi|Matsuda, Tetsuya', 'Graduate School of Informatics, Kyoto University, Yoshida Honmachi, Sakyo, Kyoto, Japan. megumi@i.kyoto-u.ac.jp.|Graduate School of Informatics, Kyoto University, Yoshida Honmachi, Sakyo, Kyoto, Japan. takemoto@sys.i.kyoto-u.ac.jp.|Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5, Takayama, Ikoma, Nara, Japan. sugiura@is.naist.jp.|Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Hokkaido, Japan. sawady@ec.hokudai.ac.jp.|Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Hokkaido, Japan. rkawascb@es.hokudai.ac.jp.|Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Hokkaido, Japan. tn@es.hokudai.ac.jp.|Graduate School of Informatics, Kyoto University, Yoshida Honmachi, Sakyo, Kyoto, Japan. tetsu@i.kyoto-u.ac.jp.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 1, 'Animals|Blood Vessels|Computer Graphics|Dendrites|Image Processing, Computer-Assisted|Imaging, Three-Dimensional|Liver|Mice|Microscopy, Confocal|Neurons|Software|User-Computer Interface', 'Journal Article', '10.1186/s12859-014-0415-x', '25523409', 'Recent advances in microscopy enable the acquisition of large numbers of tomographic images from living tissues. Three-dimensional microscope images are often displayed with volume rendering by adjusting the transfer functions. However, because the emissions from fluorescent materials and the optical properties based on point spread functions affect the imaging results, the intensity value can differ locally, even in the same structure. Further, images obtained from brain tissues contain a variety of neural structures such as dendrites and axons with complex crossings and overlapping linear structures. In these cases, the transfer functions previously used fail to optimize image generation, making it difficult to explore the connectivity of these tissues.'),
(96496, 2014, 'bmc', 'Unique features of apicoplast DNA gyrases from Toxoplasma gondii and Plasmodium falciparum', 'Nagano, Soshichiro|Lin, Ting-Yu|Edula, Jyotheeswara Reddy|Heddle, Jonathan Gardiner', 'Heddle Initiative Research Unit, RIKEN, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan. nagano.soshichiro@gmail.com.|Heddle Initiative Research Unit, RIKEN, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan. ting-yu.lin@riken.jp.|Heddle Initiative Research Unit, RIKEN, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan. jyotheeswara@biken.osaka-u.ac.jp.|Heddle Initiative Research Unit, RIKEN, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan. heddle@riken.jp.', 'Japan|Japan|Japan|Japan', 6, 'Amino Acid Sequence|Apicoplasts|Bacterial Proteins|Biological Transport|Computer Simulation|DNA Gyrase|Fetal Proteins|Humans|Malaria, Falciparum|Models, Molecular|Molecular Sequence Data|Plasmodium falciparum|Sequence Homology, Amino Acid|T-Box Domain Proteins|Toxoplasma', 'Journal Article', '10.1186/s12859-014-0416-9', '25523502', 'DNA gyrase, an enzyme once thought to be unique to bacteria, is also found in some eukaryotic plastids including the apicoplast of Apicomplexa such as Plasmodium falciparum and Toxoplasma gondii which are important disease-causing organisms. DNA gyrase is an excellent target for antibacterial drugs, yet such antibacterials seem ineffective against Apicomplexa. Characterisation of the apicoplast gyrases would be a useful step towards understanding why this should be so. While purification of active apicoplast gyrase has proved impossible to date, in silico analyses have allowed us to discover differences in the apicoplast proteins. The resulting predicted structural and functional differences will be a first step towards development of apicoplast-gyrase specific inhibitors.'),
(96497, 2014, 'bmc', 'Linear-time computation of minimal absent words using suffix array', 'Barton, Carl|Heliou, Alice|Mouchard, Laurent|Pissis, Solon P', 'Department of Informatics, Kings College London, The Strand, WC2R 2LS, London, UK. carl.barton@kcl.ac.uk.|Inria Saclay-Île de France, AMIB, Bâtiment Alan Turing, Palaiseau, France. alice.heliou@lix.polytechnique.fr.|University of Rouen, LITIS EA 4108, TIBS, Rouen, France. laurent.mouchard@univ-rouen.fr.|Department of Informatics, Kings College London, The Strand, WC2R 2LS, London, UK. solon.pissis@kcl.ac.uk.', 'United Kingdom|France|France|United Kingdom', 18, 'Algorithms|Animals|Bacteria|Computational Biology|DNA|Eukaryota|Genome|Genomics|Humans|Programming Languages|Sequence Analysis, DNA', 'Journal Article', '10.1186/s12859-014-0388-9', '25526884', 'An absent word of a word y of length n is a word that does not occur in y. It is a minimal absent word if all its proper factors occur in y. Minimal absent words have been computed in genomes of organisms from all domains of life, their computation also provides a fast alternative for measuring approximation in sequence comparison. There exists an [Formula: see text]-time and [Formula: see text]-space algorithm for computing all minimal absent words on a fixed-sized alphabet based on the construction of suffix automata (Crochemore et al., 1998). No implementation of this algorithm is publicly available. There also exists an [Formula: see text]-time and [Formula: see text]-space algorithm for the same problem based on the construction of suffix arrays (Pinho et al., 2009). An implementation of this algorithm was also provided by the authors and is currently the fastest available.'),
(96498, 2014, 'bmc', 'BitTorious: global controlled genomics data publication, research and archiving via BitTorrent extensions', 'Lee, Preston V|Dinu, Valentin', 'Department of Biomedical Informatics, Arizona State University, 13212 East Shea Boulevard, Scottsdale, AZ, 85259, USA. preston@asu.edu.|Department of Biomedical Informatics, Arizona State University, 13212 East Shea Boulevard, Scottsdale, AZ, 85259, USA. valentin.dinu@asu.edu.', 'United States|United States', 2, 'Access to Information|Archives|Biomedical Research|Computational Biology|Database Management Systems|Genomics|Humans|Internet|Publishing|Software|United States', 'Journal Article', '10.1186/s12859-014-0424-9', '25528455', 'Centralized silos of genomic data are architecturally easier to initially design, develop and deploy than distributed models. However, as interoperability pains in EHR/EMR, HIE and other collaboration-centric life sciences domains have taught us, the core challenge of networking genomics systems is not in the construction of individual silos, but the interoperability of those deployments in a manner embracing the heterogeneous needs, terms and infrastructure of collaborating parties. This article demonstrates the adaptation of BitTorrent to private collaboration networks in an authenticated, authorized and encrypted manner while retaining the same characteristics of standard BitTorrent.'),
(96499, 2014, 'bmc', 'An integrated network visualization framework towards metabolic engineering applications', 'Noronha, Alberto|Vilaça, Paulo|Rocha, Miguel', 'Centre of Biological Engineering (CEB), School of Engineering, University of Minho, Campus de Gualtar, Braga, Portugal. bertonoronha@gmail.com.|Centre of Biological Engineering (CEB), School of Engineering, University of Minho, Campus de Gualtar, Braga, Portugal. pvilaca@silicolife.com.|Centre of Biological Engineering (CEB), School of Engineering, University of Minho, Campus de Gualtar, Braga, Portugal. mrocha@di.uminho.pt.', 'Portugal|Portugal|Portugal', 0, 'Algorithms|Computer Graphics|Escherichia coli|Glycine|Metabolic Engineering|Metabolic Networks and Pathways|Models, Biological|Programming Languages|Software|Succinic Acid|Systems Biology', 'Journal Article', '10.1186/s12859-014-0420-0', '25547011', 'Over the last years, several methods for the phenotype simulation of microorganisms, under specified genetic and environmental conditions have been proposed, in the context of Metabolic Engineering (ME). These methods provided insight on the functioning of microbial metabolism and played a key role in the design of genetic modifications that can lead to strains of industrial interest. On the other hand, in the context of Systems Biology research, biological network visualization has reinforced its role as a core tool in understanding biological processes. However, it has been scarcely used to foster ME related methods, in spite of the acknowledged potential.'),
(96500, 2014, 'bmc', 'Prediction of plant pre-microRNAs and their microRNAs in genome-scale sequences using structure-sequence features and support vector machine', 'Meng, Jun|Liu, Dong|Sun, Chao|Luan, Yushi', 'School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, 116023, China. mengjun@dlut.edu.cn.|School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, 116023, China. kobe_liudong@mail.dlut.edu.cn.|School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, 116023, China. 253376871@qq.com.|School of Life Science and Biotechnology, Dalian University of Technology, Dalian, Liaoning, 116023, China. luanyush@dlut.edu.cn.', 'China|China|China|China', 14, 'Arabidopsis|Artificial Intelligence|Base Sequence|Computational Biology|Genome, Plant|Lycopersicon esculentum|MicroRNAs|Molecular Sequence Data|Plants|Support Vector Machine', 'Journal Article', '10.1186/s12859-014-0423-x', '25547126', 'MicroRNAs (miRNAs) are a family of non-coding RNAs approximately 21 nucleotides in length that play pivotal roles at the post-transcriptional level in animals, plants and viruses. These molecules silence their target genes by degrading transcription or suppressing translation. Studies have shown that miRNAs are involved in biological responses to a variety of biotic and abiotic stresses. Identification of these molecules and their targets can aid the understanding of regulatory processes. Recently, prediction methods based on machine learning have been widely used for miRNA prediction. However, most of these methods were designed for mammalian miRNA prediction, and few are available for predicting miRNAs in the pre-miRNAs of specific plant species. Although the complete Solanum lycopersicum genome has been published, only 77 Solanum lycopersicum miRNAs have been identified, far less than the estimated number. Therefore, it is essential to develop a prediction method based on machine learning to identify new plant miRNAs.'),
(96501, 2014, 'bmc', 'A framework for feature extraction from hospital medical data with applications in risk prediction', 'Tran, Truyen|Luo, Wei|Phung, Dinh|Gupta, Sunil|Rana, Santu|Kennedy, Richard Lee|Larkins, Ann|Venkatesh, Svetha', 'Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, VIC, 3220, Australia. truyen.tran@deakin.edu.au.|Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, VIC, 3220, Australia. wei.luo@deakin.edu.au.|Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, VIC, 3220, Australia. dinh.phung@deakin.edu.au.|Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, VIC, 3220, Australia. sunil.gupta@deakin.edu.au.|Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, VIC, 3220, Australia. santu.rana@deakin.edu.au.|School of Medicine, Deakin University, Geelong, VIC, Australia. lee.kennedy@deakin.edu.au.|Barwon Health, Geelong, VIC, Australia. annla@barwonhealth.org.au.|Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, VIC, 3220, Australia. svetha.venkatesh@deakin.edu.au.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Aged|Area Under Curve|Comorbidity|Databases, Factual|Diabetes Mellitus|Female|Hospitals|Humans|Logistic Models|Male|Mental Disorders|Models, Theoretical|Pneumonia|Pulmonary Disease, Chronic Obstructive|Risk Assessment|Software', 'Journal Article', '10.1186/s12859-014-0425-8', '25547173', 'Feature engineering is a time consuming component of predictive modeling. We propose a versatile platform to automatically extract features for risk prediction, based on a pre-defined and extensible entity schema. The extraction is independent of disease type or risk prediction task. We contrast auto-extracted features to baselines generated from the Elixhauser comorbidities.'),
(96502, 2014, 'bmc', 'WEBnm@ v20: Web server and services for comparing protein flexibility', 'Tiwari, Sandhya P|Fuglebakk, Edvin|Hollup, Siv M|Skjærven, Lars|Cragnolini, Tristan|Grindhaug, Svenn H|Tekle, Kidane M|Reuter, Nathalie', 'Department of Molecular Biology, University of Bergen, Bergen, Norway. Sandhya.Tiwari@mbi.uib.no.|Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway. Edvin.Fuglebakk@mbi.uib.no.|Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway. siv.hollup@gmail.com.|Department of Biomedicine, University of Bergen, Bergen, Norway. Lars.Skjarven@biomed.uib.no.|Department of Molecular Biology, University of Bergen, Bergen, Norway. tristan.cragnolini@gmail.com.|Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway. svennhg@gmail.com.|Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway. kidane.tekle@cbu.uib.no.|Department of Molecular Biology, University of Bergen, Bergen, Norway. Nathalie.Reuter@mbi.uib.no.', 'Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway', 26, 'Adenylate Kinase|Databases, Protein|Humans|Internet|Metabolic Networks and Pathways|Multigene Family|Protein Conformation|Protein Folding|Protein Interaction Domains and Motifs|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1186/s12859-014-0427-6', '25547242', 'Normal mode analysis (NMA) using elastic network models is a reliable and cost-effective computational method to characterise protein flexibility and by extension, their dynamics. Further insight into the dynamics-function relationship can be gained by comparing protein motions between protein homologs and functional classifications. This can be achieved by comparing normal modes obtained from sets of evolutionary related proteins.'),
(96503, 2014, 'bmc', 'FogBank: a single cell segmentation across multiple cell lines and image modalities', 'Chalfoun, Joe|Majurski, Michael|Dima, Alden|Stuelten, Christina|Peskin, Adele|Brady, Mary', 'Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA. joe.chalfoun@nist.gov.|Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA. michael.majurski@nist.gov.|Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA. alden.dima@nist.gov.|Laboratory of Cellular and Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. chrisstu@mail.nih.gov.|Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA. adele.peskin@nist.gov.|Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA. mary.brady@nist.gov.', 'United States|United States|United States|United States|United States|United States', 25, 'Algorithms|Animals|Breast|Cells|Computational Biology|Female|Humans|Image Interpretation, Computer-Assisted|Mice|Microscopy, Fluorescence|Microscopy, Phase-Contrast|NIH 3T3 Cells|Saccharomyces cerevisiae', 'Journal Article', '10.1186/s12859-014-0431-x', '25547324', 'Many cell lines currently used in medical research, such as cancer cells or stem cells, grow in confluent sheets or colonies. The biology of individual cells provide valuable information, thus the separation of touching cells in these microscopy images is critical for counting, identification and measurement of individual cells. Over-segmentation of single cells continues to be a major problem for methods based on morphological watershed due to the high level of noise in microscopy cell images. There is a need for a new segmentation method that is robust over a wide variety of biological images and can accurately separate individual cells even in challenging datasets such as confluent sheets or colonies.'),
(96504, 2014, 'bmc', 'Identifying tandem Ankyrin repeats in protein structures', 'Chakrabarty, Broto|Parekh, Nita', 'Centre for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad, India. broto.chakrabarty@research.iiit.ac.in.|Centre for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad, India. nita@iiit.ac.in.', 'India|India', 0, 'Algorithms|Amino Acid Sequence|Ankyrin Repeat|Ankyrins|Computer Simulation|Humans|Models, Molecular|Molecular Sequence Data|Protein Conformation|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/s12859-014-0440-9', '25547411', 'Tandem repetition of structural motifs in proteins is frequently observed across all forms of life. Topology of repeating unit and its frequency of occurrence are associated to a wide range of structural and functional roles in diverse proteins, and defects in repeat proteins have been associated with a number of diseases. It is thus desirable to accurately identify specific repeat type and its copy number. Weak evolutionary constraints on repeat units and insertions/deletions between them make their identification difficult at the sequence level and structure based approaches are desired. The proposed graph spectral approach is based on protein structure represented as a graph for detecting one of the most frequently observed structural repeats, Ankyrin repeat.'),
(96505, 2014, 'bmc', 'APP: an Automated Proteomics Pipeline for the analysis of mass spectrometry data based on multiple open access tools', 'Malm, Erik K|Srivastava, Vaibhav|Sundqvist, Gustav|Bulone, Vincent', 'Division of Glycoscience, School of Biotechnology, Royal Institute of Technology (KTH), AlbaNova University Centre, Stockholm, Sweden. emalm@kth.se.|Division of Glycoscience, School of Biotechnology, Royal Institute of Technology (KTH), AlbaNova University Centre, Stockholm, Sweden. vaibhav.srivastava@biotech.kth.se.|Division of Glycoscience, School of Biotechnology, Royal Institute of Technology (KTH), AlbaNova University Centre, Stockholm, Sweden. gustavs@kth.se.|Division of Glycoscience, School of Biotechnology, Royal Institute of Technology (KTH), AlbaNova University Centre, Stockholm, Sweden. bulone@kth.se.', 'Sweden|Sweden|Sweden|Sweden', 0, 'Access to Information|Algorithms|Chromatography, Liquid|Computational Biology|Humans|Mass Spectrometry|Peptide Fragments|Populus|Proteins|Proteomics|Software|Tandem Mass Spectrometry|Workflow', 'Journal Article', '10.1186/s12859-014-0441-8', '25547515', 'Mass spectrometry analyses of complex protein samples yield large amounts of data and specific expertise is needed for data analysis, in addition to a dedicated computer infrastructure. Furthermore, the identification of proteins and their specific properties require the use of multiple independent bioinformatics tools and several database search algorithms to process the same datasets. In order to facilitate and increase the speed of data analysis, there is a need for an integrated platform that would allow a comprehensive profiling of thousands of peptides and proteins in a single process through the simultaneous exploitation of multiple complementary algorithms.'),
(96506, 2014, 'bmc', 'Identifying target processes for microbial electrosynthesis by elementary mode analysis', 'Kracke, Frauke|Krömer, Jens O', 'Centre for Microbial Electrosynthesis, The University of Queensland, Level 4, Gehrmann Laboratories Building (60), Brisbane, QLD, 4072, Australia. f.kracke@uq.edu.au.|Centre for Microbial Electrosynthesis, The University of Queensland, Level 4, Gehrmann Laboratories Building (60), Brisbane, QLD, 4072, Australia. j.kromer@uq.edu.au.', 'Australia|Australia', 47, 'Bioelectric Energy Sources|Biomass|Computational Biology|Electrochemistry|Electron Transport|Fermentation|Metabolic Engineering|Metabolic Networks and Pathways|Oxidation-Reduction', 'Journal Article', '10.1186/s12859-014-0410-2', '25547630', 'Microbial electrosynthesis and electro fermentation are techniques that aim to optimize microbial production of chemicals and fuels by regulating the cellular redox balance via interaction with electrodes. While the concept is known for decades major knowledge gaps remain, which make it hard to evaluate its biotechnological potential. Here we present an in silico approach to identify beneficial production processes for electro fermentation by elementary mode analysis. Since the fundamentals of electron transport between electrodes and microbes have not been fully uncovered yet, we propose different options and discuss their impact on biomass and product yields.'),
(96507, 2014, 'bmc', 'Mammalian transcriptional hotspots are enriched for tissue specific enhancers near cell type specific highly expressed genes and are predicted to act as transcriptional activator hubs', 'Joshi, Anagha', 'Division of Developmental Biology, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 8GR, UK. Anagha.Joshi@roslin.ed.ac.uk.', 'United Kingdom', 0, 'Animals|Cell Lineage|Chromatin Immunoprecipitation|DNA (Cytosine-5-)-Methyltransferase 1|DNA (Cytosine-5-)-Methyltransferases|Embryonic Stem Cells|Gene Expression Regulation|Genome|Humans|Mice|Protein Methyltransferases|Regulatory Sequences, Nucleic Acid|Species Specificity|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1186/s12859-014-0412-0', '25547756', 'Transcriptional hotspots are defined as genomic regions bound by multiple factors. They have been identified recently as cell type specific enhancers regulating developmentally essential genes in many species such as worm, fly and humans. The in-depth analysis of hotspots across multiple cell types in same species still remains to be explored and can bring new biological insights.'),
(96508, 2014, 'bmc', 'JRC GMO-Matrix: a web application to support Genetically Modified Organisms detection strategies', 'Angers-Loustau, Alexandre|Petrillo, Mauro|Bonfini, Laura|Gatto, Francesco|Rosa, Sabrina|Patak, Alexandre|Kreysa, Joachim', 'Molecular Biology and Genomics Unit, Joint Research Centre, European Commission, Ispra, Italy. Alexandre.ANGERS@ec.europa.eu.|Molecular Biology and Genomics Unit, Joint Research Centre, European Commission, Ispra, Italy. Mauro.PETRILLO@ec.europa.eu.|Molecular Biology and Genomics Unit, Joint Research Centre, European Commission, Ispra, Italy. Laura.BONFINI@jrc.ec.europa.eu.|Molecular Biology and Genomics Unit, Joint Research Centre, European Commission, Ispra, Italy. Francesco.GATTO@ec.europa.eu.|Molecular Biology and Genomics Unit, Joint Research Centre, European Commission, Ispra, Italy. Sabrina.ROSA@ec.europa.eu.|Molecular Biology and Genomics Unit, Joint Research Centre, European Commission, Ispra, Italy. Alexandre.PATAK@jrc.ec.europa.eu.|Molecular Biology and Genomics Unit, Joint Research Centre, European Commission, Ispra, Italy. Joachim.KREYSA@ec.europa.eu.', 'Italy|Italy|Italy|France|Italy|Italy|Italy', 23, 'Computational Biology|DNA, Plant|Databases, Factual|Decision Support Techniques|Genes, Plant|Laboratories|Plants, Genetically Modified|Polymerase Chain Reaction|Software', 'Journal Article', '10.1186/s12859-014-0417-8', '25547877', 'The polymerase chain reaction (PCR) is the current state of the art technique for DNA-based detection of Genetically Modified Organisms (GMOs). A typical control strategy starts by analyzing a sample for the presence of target sequences (GM-elements) known to be present in many GMOs. Positive findings from this screening are then confirmed with GM (event) specific test methods. A reliable knowledge of which GMOs are detected by combinations of GM-detection methods is thus crucial to minimize the verification efforts.'),
(96509, 2014, 'bmc', 'Prediction of piRNAs using transposon interaction and a support vector machine', 'Wang, Kai|Liang, Chun|Liu, Jinding|Xiao, Huamei|Huang, Shuiqing|Xu, Jianhua|Li, Fei', 'Department of Entomology, College of Plant Protection, Nanjing Agricultural University, Nanjing, 210095, China. wangk4@miamioh.edu.|Department of Biology, Miami University, Oxford, OH, 45056, USA. liangc@miamioh.edu.|Department of Entomology, College of Plant Protection, Nanjing Agricultural University, Nanjing, 210095, China. liujd@njau.edu.cn.|Department of Entomology, College of Plant Protection, Nanjing Agricultural University, Nanjing, 210095, China. xiaohuamei625@163.com.|College of Information and Technology, Nanjing Agricultural University, Nanjing, 210095, China. sqhuang@njau.edu.cn.|College of computer science and Technology, Nanjing Normal University, Nanjing, 210023, China. xujianghua@njnu.edu.cn.|Department of Entomology, College of Plant Protection, Nanjing Agricultural University, Nanjing, 210095, China. lifei03@tsinghua.org.cn.', 'China|United States|China|China|China|China|China', 0, 'Animals|Drosophila Proteins|Drosophila melanogaster|Humans|Mice|Moths|Oryza|RNA, Small Interfering|Rats|Support Vector Machine|User-Computer Interface', 'Journal Article', '10.1186/s12859-014-0419-6', '25547961', 'Piwi-interacting RNAs (piRNAs) are a class of small non-coding RNA primarily expressed in germ cells that can silence transposons at the post-transcriptional level. Accurate prediction of piRNAs remains a significant challenge.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96510, 2014, 'bmc', 'ExpaRNA-P: simultaneous exact pattern matching and folding of RNAs', 'Otto, Christina|Mxc3xb6hl, Mathias|Heyne, Steffen|Amit, Mika|Landau, Gad M|Backofen, Rolf|Will, Sebastian', 'Bioinformatics, Institute of Computer Science, University of Freiburg, Freiburg, Germany. schmiedc@informatik.uni-freiburg.de.|Bioinformatics, Institute of Computer Science, University of Freiburg, Freiburg, Germany. mamo181@googlemail.com.|Max Planck Institute of Immunobiology and Epigenetics, Stuebeweg 51, Freiburg, 79108, Germany. heyne@informatik.uni-freiburg.de.|Department of Computer Science, University of Haifa, Mount Carmel, Haifa, Israel. mika.amit2@gmail.com.|Department of Computer Science, University of Haifa, Mount Carmel, Haifa, Israel. landau@univ.haifa.ac.il.|Bioinformatics, Institute of Computer Science, University of Freiburg, Freiburg, Germany. backofen@informatik.uni-freiburg.de.|Bioinformatics, Institute of Computer Science, University of Freiburg, Freiburg, Germany. swill@csail.mit.edu.', 'Germany|Germany|Germany|Israel|Israel|Germany|Germany', 0, 'Algorithms|RNA|RNA Folding|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1186/s12859-014-0404-0', '25551362', 'Identifying sequence-structure motifs common to two RNAs can speed up the comparison of structural RNAs substantially. The core algorithm of the existent approach ExpaRNA solves this problem for a priori known input structures. However, such structures are rarely known, moreover, predicting them computationally is no rescue, since single sequence structure prediction is highly unreliable.'),
(96511, 2014, 'bmc', 'Predicting breast cancer using an expression values weighted clinical classifier', 'Thomas, Minta|De Brabanter, Kris|Suykens, Johan A K|De Moor, Bart', 'KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. minta.thomas@esat.kuleuven.be.|Department of Statistics & Computer Science, Iowa State University, Ames, IA, USA. kris.debrabanter@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. Johan.Suykens@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.', 'Belgium|United States|Belgium|Belgium', 7, 'Algorithms|Area Under Curve|Artificial Intelligence|Breast Neoplasms|Databases, Genetic|Humans|Oligonucleotide Array Sequence Analysis|Prognosis|Software|Support Vector Machine', 'Journal Article', '10.1186/s12859-014-0411-1', '25551433', 'Clinical data, such as patient history, laboratory analysis, ultrasound parameters-which are the basis of day-to-day clinical decision support-are often used to guide the clinical management of cancer in the presence of microarray data. Several data fusion techniques are available to integrate genomics or proteomics data, but only a few studies have created a single prediction model using both gene expression and clinical data. These studies often remain inconclusive regarding an obtained improvement in prediction performance. To improve clinical management, these data should be fully exploited. This requires efficient algorithms to integrate these data sets and design a final classifier. LS-SVM classifiers and generalized eigenvalue/singular value decompositions are successfully used in many bioinformatics applications for prediction tasks. While bringing up the benefits of these two techniques, we propose a machine learning approach, a weighted LS-SVM classifier to integrate two data sources: microarray and clinical parameters.'),
(96512, 2014, 'bmc', 'Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms', 'Yang, Jack Y|Dunker, A|Liu, Jun S|Qin, Xiang|Arabnia, Hamid R|Yang, William|Niemierko, Andrzej|Chen, Zhongxue|Luo, Zuojie|Wang, Liangjiang|Liu, Yunlong|Xu, Dong|Deng, Youping|Tong, Weida|Yang, Mary', 'KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belg', 0, 'Computational Biology|Genome, Human|Genomics|Humans|Neoplasms|Phenotype|Transcriptome|Translational Medical Research', 'Journal Article', '10.1186/1471-2105-15-S17-I1', '25559210', 'Advances of high-throughput technologies have rapidly produced more and more data from DNAs and RNAs to proteins, especially large volumes of genome-scale data. However, connection of the genomic information to cellular functions and biological behaviours relies on the development of effective approaches at higher systems level. In particular, advances in RNA-Seq technology has helped the studies of transcriptome, RNA expressed from the genome, while systems biology on the other hand provides more comprehensive pictures, from which genes and proteins actively interact to lead to cellular behaviours and physiological phenotypes. As biological interactions mediate many biological processes that are essential for cellular function or disease development, it is important to systematically identify genomic information including genetic mutations from GWAS (genome-wide association study), differentially expressed genes, bidirectional promoters, intrinsic disordered proteins (IDP) and protein interactions to gain deep insights into the underlying mechanisms of gene regulations and networks. Furthermore, bidirectional promoters can co-regulate many biological pathways, where the roles of bidirectional promoters can be studied systematically for identifying co-regulating genes at interactive network level. Combining information from different but related studies can ultimately help revealing the landscape of molecular mechanisms underlying complex diseases such as cancer. '),
(96513, 2014, 'bmc', 'Orthology-driven mapping of bidirectional promoters in human and mouse genomes', 'Yang, Mary|Elnitski, Laura', 'KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.', 'Belgium|Belgium', 5, 'Animals|Biological Evolution|Gene Expression Regulation|Genome|Humans|Mice|Open Reading Frames|Promoter Regions, Genetic|Regulatory Sequences, Nucleic Acid|Vertebrates', 'Journal Article', '10.1186/1471-2105-15-S17-S1', '25559261', 'The presence of bidirectional promoters in all vertebrate species suggests that the promoters may be maintained in orthologous positions. Therefore the identification of the comprehensive orthologous mapping of this type promoter across species can facilitate elucidation of regulatory mechanisms controlling bidirectional gene expression. However, the lack of annotation for many transcribed regions in the genome can impact the orthology designation of these promoters. Human and mouse are among genomes that have been relatively well annotated. Thus we used them as models to study the orthologous patterns of bidirectional promoters.'),
(96514, 2014, 'bmc', 'Identification of genes and pathways involved in kidney renal clear cell carcinoma', 'Yang, William|Yoshigoe, Kenji|Qin, Xiang|Liu, Jun S|Yang, Jack Y|Niemierko, Andrzej|Deng, Youping|Liu, Yunlong|Dunker, A|Chen, Zhongxue|Wang, Liangjiang|Xu, Dong|Arabnia, Hamid R|Tong, Weida|Yang, Mary', 'KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belg', 0, 'Biomarkers, Tumor|Carcinoma, Renal Cell|Case-Control Studies|Cluster Analysis|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|Kidney|Kidney Neoplasms|Signal Transduction|Support Vector Machine', 'Comparative Study', '10.1186/1471-2105-15-S17-S2', '25559354', 'Kidney Renal Clear Cell Carcinoma (KIRC) is one of fatal genitourinary diseases and accounts for most malignant kidney tumours. KIRC has been shown resistance to radiotherapy and chemotherapy. Like many types of cancers, there is no curative treatment for metastatic KIRC. Using advanced sequencing technologies, The Cancer Genome Atlas (TCGA) project of NIH/NCI-NHGRI has produced large-scale sequencing data, which provide unprecedented opportunities to reveal new molecular mechanisms of cancer. We combined differentially expressed genes, pathways and network analyses to gain new insights into the underlying molecular mechanisms of the disease development.'),
(96515, 2014, 'bmc', 'A new statistical approach to combining p-values using gamma distribution and its application to genome-wide association study', 'Chen, Zhongxue|Yang, William|Liu, Qingzhong|Yang, Jack Y|Li, Jing|Yang, Mary', 'KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Case-Control Studies|Computer Simulation|Genome-Wide Association Study|Humans|Models, Statistical', 'Comparative Study', '10.1186/1471-2105-15-S17-S3', '25559433', 'Combining information from different studies is an important and useful practice in bioinformatics, including genome-wide association study, rare variant data analysis and other set-based analyses. Many statistical methods have been proposed to combine p-values from independent studies. However, it is known that there is no uniformly most powerful test under all conditions, therefore, finding a powerful test in specific situation is important and desirable.'),
(96516, 2014, 'bmc', 'Improving protein order-disorder classification using charge-hydropathy plots', 'Huang, Fei|Oldfield, Christopher J|Xue, Bin|Hsu, Wei-Lun|Meng, Jingwei|Liu, Xiaowen|Shen, Li|Romero, Pedro|Uversky, Vladimir N|Dunker, A', 'KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 32, 'Algorithms|Amino Acids|Animals|Databases, Protein|Humans|Hydrophobic and Hydrophilic Interactions|Intrinsically Disordered Proteins|Proteins', 'Journal Article', '10.1186/1471-2105-15-S17-S4', '25559583', 'The earliest whole protein order/disorder predictor (Uversky et al., Proteins, 41: 415-427 (2000)), herein called the charge-hydropathy (C-H) plot, was originally developed using the Kyte-Doolittle (1982) hydropathy scale (Kyte & Doolittle., J. Mol. Biol, 157: 105-132(1982)). Here the goal is to determine whether the performance of the C-H plot in separating structured and disordered proteins can be improved by using an alternative hydropathy scale.'),
(96517, 2014, 'bmc', 'Developing discriminate model and comparative analysis of differentially expressed genes and pathways for bloodstream samples of diabetes mellitus type 2', 'Liu, Chang|Lu, Lili|Kong, Quan|Li, Yan|Wu, Haihua|Yang, William|Xu, Shandan|Yang, Xinyu|Song, Xiaolei|Yang, Jack Y|Yang, Mary|Deng, Youping', 'KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Adult|Biomarkers|Case-Control Studies|Chromosomes, Human|Diabetes Mellitus, Type 2|Gene Expression Profiling|Genome, Human|Humans|Models, Statistical|Oligonucleotide Array Sequence Analysis|Prediabetic State|RNA, Messenger|Signal Transduction', 'Comparative Study', '10.1186/1471-2105-15-S17-S5', '25559614', 'Diabetes mellitus of type 2 (T2D), also known as noninsulin-dependent diabetes mellitus (NIDDM) or adult-onset diabetes, is a common disease. It is estimated that more than 300 million people worldwide suffer from T2D. In this study, we investigated the T2D, pre-diabetic and healthy human (no diabetes) bloodstream samples using genomic, genealogical, and phonemic information. We identified differentially expressed genes and pathways. The study has provided deeper insights into the development of T2D, and provided useful information for further effective prevention and treatment of the disease.'),
(96518, 2014, 'bmc', 'Mining hidden knowledge for drug safety assessment: topic modeling of LiverTox as a case study', 'Yu, Ke|Zhang, Jie|Chen, Minjun|Xu, Xiaowei|Suzuki, Ayako|Ilic, Katarina|Tong, Weida', 'KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Chemical and Drug Induced Liver Injury|Data Mining|Databases, Factual|Drug-Related Side Effects and Adverse Reactions|Humans|Models, Biological|Safety Management', 'Journal Article', '10.1186/1471-2105-15-S17-S6', '25559675', 'Given the significant impact on public health and drug development, drug safety has been a focal point and research emphasis across multiple disciplines in addition to scientific investigation, including consumer advocates, drug developers and regulators. Such a concern and effort has led numerous databases with drug safety information available in the public domain and the majority of them contain substantial textual data. Text mining offers an opportunity to leverage the hidden knowledge within these textual data for the enhanced understanding of drug safety and thus improving public health.'),
(96519, 2014, 'bmc', 'Proceedings of the Thirteenth Annual UT- KBRIN Bioinformatics Summit 2014', 'Rouchka, Eric C|Chariker, Julia H', 'KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.|KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics/iMinds Future Health Department, Kasteelpark Arenberg 10, Leuven, 3001, Belgium. bart.demoor@esat.kuleuven.be.', 'Belgium|Belgium', 11, 'Computational Biology|Genetic Variation|Genomics|Mutation|Systems Biology', 'Introductory Journal Article', '10.1186/1471-2105-15-S17-S6', '25571995', '-'),
(96520, 2014, 'bmc', 'Proceedings of the 11th Annual MCBIOS Conference, March 6-8, 2014, Stillwater, Oklahoma', '-', '-', '-', 11, 'Animals|Computational Biology|Humans', 'Congress', '10.1186/1471-2105-15-S17-S6', '25590053', '-'),
(96521, 2015, 'bmc', 'YersiniaBase: a genomic resource and analysis platform for comparative analysis of Yersinia', 'Tan, Shi Yang|Dutta, Avirup|Jakubovics, Nicholas S|Ang, Mia Yang|Siow, Cheuk Chuen|Mutha, Naresh Vr|Heydari, Hamed|Wee, Wei Yee|Wong, Guat Jah|Choo, Siew Woh', 'Genome Informatics Research Laboratory, High Impact Research Building (HIR) Building, University of Malaya, 50603, Kuala Lumpur, Malaysia. shiyangtan@gmail.com.|Genome Informatics Research Laboratory, High Impact Research Building (HIR) Building, University of Malaya, 50603, Kuala Lumpur, Malaysia. avirupdutta@gmail.com.|Center for Oral Health Research, School of Dental Sciences, Newcastle University, Framlington Place, Newcastle upon Tyne, United Kingdom. nick.jakubovics@ncl.ac.uk.|Genome Informatics Research Laboratory, High Impact Research Building (HIR) Building, University of Malaya, 50603, Kuala Lumpur, Malaysia. angmiayang@gmail.com.|Genome Informatics Research Laboratory, High Impact Research Building (HIR) Building, University of Malaya, 50603, Kuala Lumpur, Malaysia. cheukchuen@gmail.com.|Genome Informatics Research Laboratory, High Impact Research Building (HIR) Building, University of Malaya, 50603, Kuala Lumpur, Malaysia. nareshmvr@gmail.com.|Genome Informatics Research Laboratory, High Impact Research Building (HIR) Building, University of Malaya, 50603, Kuala Lumpur, Malaysia. heydarihamed@yahoo.com.|Genome Informatics Research Laboratory, High Impact Research Building (HIR) Building, University of Malaya, 50603, Kuala Lumpur, Malaysia. gavinwwy89@hotmail.com.|Genome Informatics Research Laboratory, High Impact Research Building (HIR) Building, University of Malaya, 50603, Kuala Lumpur, Malaysia. winnie.my23dna@gmail.com.|Genome Informatics Research Laboratory, High Impact Research Building (HIR) Building, University of Malaya, 50603, Kuala Lumpur, Malaysia. lchoo@um.edu.my.', 'Malaysia|Malaysia|United Kingdom|Malaysia|Malaysia|Malaysia|Malaysia|Malaysia|Malaysia|Malaysia', 0, 'Chromosome Mapping|Databases, Genetic|Genome, Bacterial|Genomics|Humans|Internet|Phylogeny|Search Engine|Software|User-Computer Interface|Virulence|Yersinia|Yersinia Infections', 'Comparative Study', '10.1186/s12859-014-0422-y', '25591325', 'Yersinia is a Gram-negative bacteria that includes serious pathogens such as the Yersinia pestis, which causes plague, Yersinia pseudotuberculosis, Yersinia enterocolitica. The remaining species are generally considered non-pathogenic to humans, although there is evidence that at least some of these species can cause occasional infections using distinct mechanisms from the more pathogenic species. With the advances in sequencing technologies, many genomes of Yersinia have been sequenced. However, there is currently no specialized platform to hold the rapidly-growing Yersinia genomic data and to provide analysis tools particularly for comparative analyses, which are required to provide improved insights into their biology, evolution and pathogenicity.'),
(96522, 2015, 'bmc', 'SubPatCNV: approximate subspace pattern mining for mapping copy-number variations', 'Johnson, Nicholas|Zhang, Huanan|Fang, Gang|Kumar, Vipin|Kuang, Rui', 'Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota. njohnson@cs.umn.edu.|Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota. huanan@cs.umn.edu.|Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota. gang.fang@mssm.edu.|Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota. kumar@cs.umn.edu.|Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota. kuang@cs.umn.edu.', '-|-|-|-|-', 0, 'Algorithms|DNA Copy Number Variations|Data Mining|Female|HapMap Project|Humans|Ovarian Neoplasms|Software', 'Journal Article', '10.1186/s12859-014-0426-7', '25591662', 'Many DNA copy-number variations (CNVs) are known to lead to phenotypic variations and pathogenesis. While CNVs are often only common in a small number of samples in the studied population or patient cohort, previous work has not focused on customized identification of CNV regions that only exhibit in subsets of samples with advanced data mining techniques to reliably answer questions such as Which are all the chromosomal fragments showing nearly identical deletions or insertions in more than 30% of the individuals?.'),
(96523, 2015, 'bmc', 'Single-molecule dataset (SMD): a generalized storage format for raw and processed single-molecule data', 'Greenfeld, Max|van de Meent, Jan-Willem|Pavlichin, Dmitri S|Mabuchi, Hideo|Wiggins, Chris H|Gonzalez, Ruben L|Herschlag, Daniel', 'Department of Chemical Engineering, Stanford University, Stanford, CA, 94305, USA. max.greenfeld@gmail.com.|Department of Statistics, Columbia University, New York, NY, 10027, USA. janwillem.vandemeent@gmail.com.|Department of Physics, Stanford University, Stanford, CA, 94305, USA. dmitrip@stanford.edu.|Department of Applied Physics, Stanford University, Stanford, CA, 94305, USA. hmabuchi@stanford.edu.|Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, 10027, USA. chris.wiggins@columbia.edu.|Department of Chemistry, Columbia University, New York, NY, 10027, USA. rlg2118@columbia.edu.|Department of Chemical Engineering, Stanford University, Stanford, CA, 94305, USA. herschla@stanford.edu.', 'United States|United States|United States|United States|United States|United States|United States', 4, 'Cell Physiological Phenomena|Computational Biology|Datasets as Topic|Humans|Kinetics|Microscopy|Software', 'Journal Article', '10.1186/s12859-014-0429-4', '25591752', 'Single-molecule techniques have emerged as incisive approaches for addressing a wide range of questions arising in contemporary biological research [Trends Biochem Sci 38:30-37, 2013, Nat Rev Genet 14:9-22, 2013, Curr Opin Struct Biol 2014, 28C:112-121, Annu Rev Biophys 43:19-39, 2014]. The analysis and interpretation of raw single-molecule data benefits greatly from the ongoing development of sophisticated statistical analysis tools that enable accurate inference at the low signal-to-noise ratios frequently associated with these measurements. While a number of groups have released analysis toolkits as open source software [J Phys Chem B 114:5386-5403, 2010, Biophys J 79:1915-1927, 2000, Biophys J 91:1941-1951, 2006, Biophys J 79:1928-1944, 2000, Biophys J 86:4015-4029, 2004, Biophys J 97:3196-3205, 2009, PLoS One 7:e30024, 2012, BMC Bioinformatics 288 11(8):S2, 2010, Biophys J 106:1327-1337, 2014, Proc Int Conf Mach Learn 28:361-369, 2013], it remains difficult to compare analysis for experiments performed in different labs due to a lack of standardization.'),
(96524, 2015, 'bmc', 'Predicting protein functions using incomplete hierarchical labels', 'Yu, Guoxian|Zhu, Hailong|Domeniconi, Carlotta', 'Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China. guoxian85@gmail.com.|Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China. hlzhu@comp.hkbu.edu.hk.|Department of Computer Science, George Mason University, Fairfax, VA, USA. carlotta@cs.gmu.edu.', 'China|China|United States', 0, 'Algorithms|Databases, Protein|Molecular Dynamics Simulation|Proteins', 'Journal Article', '10.1186/s12859-014-0430-y', '25591917', 'Protein function prediction is to assign biological or biochemical functions to proteins, and it is a challenging computational problem characterized by several factors: (1) the number of function labels (annotations) is large, (2) a protein may be associated with multiple labels, (3) the function labels are structured in a hierarchy, and (4) the labels are incomplete. Current predictive models often assume that the labels of the labeled proteins are complete, i.e. no label is missing. But in real scenarios, we may be aware of only some hierarchical labels of a protein, and we may not know whether additional ones are actually present. The scenario of incomplete hierarchical labels, a challenging and practical problem, is seldom studied in protein function prediction.'),
(96525, 2015, 'bmc', 'Amyloid precursor protein interaction network in human testis: sentinel proteins for male reproduction', 'Silva, Joana Vieira|Yoon, Sooyeon|Domingues, Sara|Guimarães, Sofia|Goltsev, Alexander V|da Cruz E Silva, Edgar Figueiredo|Mendes, José Fernando F|da Cruz E Silva, Odete Abreu Beirão|Fardilha, Margarida', 'Laboratory of Signal Transduction, Centre for Cell Biology, Health Sciences Department and Biology Department, University of Aveiro, 3810-193, Aveiro, Portugal. joanavieirasilva@ua.pt.|Department of Physics, I3N, University of Aveiro, 3810-193, Aveiro, Portugal. syoon@ua.pt.|Laboratory of Neurosciences, Centre for Cell Biology, Health Sciences Department and Biology Department, University of Aveiro, 3810-193, Aveiro, Portugal. sdomingues@ua.pt.|Laboratory of Neurosciences, Centre for Cell Biology, Health Sciences Department and Biology Department, University of Aveiro, 3810-193, Aveiro, Portugal. asofia.guimaraes@gmail.com.|Department of Physics, I3N, University of Aveiro, 3810-193, Aveiro, Portugal. goltsev@ua.pt.|Laboratory of Signal Transduction, Centre for Cell Biology, Health Sciences Department and Biology Department, University of Aveiro, 3810-193, Aveiro, Portugal. msanciofardilha@ua.pt.|Department of Physics, I3N, University of Aveiro, 3810-193, Aveiro, Portugal. jfmendes@ua.pt.|Laboratory of Neurosciences, Centre for Cell Biology, Health Sciences Department and Biology Department, University of Aveiro, 3810-193, Aveiro, Portugal. odetecs@ua.pt.|Laboratory of Signal Transduction, Centre for Cell Biology, Health Sciences Department and Biology Department, University of Aveiro, 3810-193, Aveiro, Portugal. mfardilha@ua.pt.', 'Portugal|Portugal|Portugal|Portugal|Portugal|Portugal|Portugal|Portugal|Portugal', 15, 'Amyloid beta-Protein Precursor|Humans|Male|Protein Interaction Mapping|Protein Interaction Maps|Reproduction|Spermatozoa|Testis', 'Journal Article', '10.1186/s12859-014-0432-9', '25591988', 'Amyloid precursor protein (APP) is widely recognized for playing a central role in Alzheimers disease pathogenesis. Although APP is expressed in several tissues outside the human central nervous system, the functions of APP and its family members in other tissues are still poorly understood. APP is involved in several biological functions which might be potentially important for male fertility, such as cell adhesion, cell motility, signaling, and apoptosis. Furthermore, APP superfamily members are known to be associated with fertility. Knowledge on the protein networks of APP in human testis and spermatozoa will shed light on the function of APP in the male reproductive system.'),
(96526, 2015, 'bmc', 'HyLiTE: accurate and flexible analysis of gene expression in hybrid and allopolyploid species', 'Duchemin, Wandrille|Dupont, Pierre-Yves|Campbell, Matthew A|Ganley, Austen R D|Cox, Murray P', 'Statistics and Bioinformatics Group, Institute of Fundamental Sciences, Massey University, Palmerston North, New Zealand. wandrille.duchemin@insa-lyon.fr.|Statistics and Bioinformatics Group, Institute of Fundamental Sciences, Massey University, Palmerston North, New Zealand. p.y.dupont@massey.ac.nz.|Statistics and Bioinformatics Group, Institute of Fundamental Sciences, Massey University, Palmerston North, New Zealand. m.campbell1@massey.ac.nz.|Institute of Mathematical and Natural Sciences, Massey University, Auckland, New Zealand. a.r.ganley@massey.ac.nz.|Statistics and Bioinformatics Group, Institute of Fundamental Sciences, Massey University, Palmerston North, New Zealand. m.p.cox@massey.ac.nz.', 'New Zealand|New Zealand|New Zealand|New Zealand|New Zealand', 10, 'Animals|Biological Evolution|Fungi|Gene Expression Regulation|Goldfish|Gossypium|High-Throughput Nucleotide Sequencing|Hybridization, Genetic|Polymorphism, Single Nucleotide|Polyploidy|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-014-0433-8', '25592117', 'Forming a new species through the merger of two or more divergent parent species is increasingly seen as a key phenomenon in the evolution of many biological systems. However, little is known about how expression of parental gene copies (homeologs) responds following genome merger. High throughput RNA sequencing now makes this analysis technically feasible, but tools to determine homeolog expression are still in their infancy.'),
(96527, 2015, 'bmc', 'Structure and sequence analyses of Bacteroides proteins BVU_4064 and BF1687 reveal presence of two novel predominantly-beta domains, predicted to be involved in lipid and cell surface interactions', 'Natarajan, Padmaja|Punta, Marco|Kumar, Abhinav|Yeh, Andrew P|Godzik, Adam|Aravind, L', 'Joint Center for Structural Genomics, San Diego, USA. pnatarajan@sanfordburnham.org.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK. mpunta@ebi.ac.uk.|Joint Center for Structural Genomics, San Diego, USA. abhinavk@slac.stanford.edu.|Joint Center for Structural Genomics, San Diego, USA. Andrew.P.Yeh@gmail.com.|Joint Center for Structural Genomics, San Diego, USA. adam@sanfordburnham.org.|National Center for Biotechnology Information, National Library of Medicine, Building 38A, Bethesda, MD, 20894, USA. aravind@ncbi.nlm.nih.gov.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 1, 'Amino Acid Sequence|Bacterial Proteins|Bacteroides|Cell Adhesion|Cell Adhesion Molecules|Crystallography, X-Ray|Humans|Lipids|Membrane Proteins|Molecular Sequence Data|Protein Folding|Protein Structure, Tertiary|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/s12859-014-0434-7', '25592227', 'N-terminal domains of BVU_4064 and BF1687 proteins from Bacteroides vulgatus and Bacteroides fragilis respectively are members of the Pfam family PF12985 (DUF3869). Proteins containing a domain from this family can be found in most Bacteroides species and, in large numbers, in all human gut microbiome samples. Both BVU_4064 and BF1687 proteins have a consensus lipobox motif implying they are anchored to the membrane, but their functions are otherwise unknown. The C-terminal half of BVU_4064 is assigned to protein family PF12986 (DUF3870), the equivalent part of BF1687 was unclassified.'),
(96528, 2015, 'bmc', 'Pollux: platform independent error correction of single and mixed genomes', 'Marinier, Eric|Brown, Daniel G|McConkey, Brendan J', 'David R. Cheriton School of Computer Science, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada. eric.marinier@uwaterloo.ca.|David R. Cheriton School of Computer Science, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada. dan.brown@uwaterloo.ca.|Department of Biology, University of Waterloo, 200 University Ave W, N2L3G1 Waterloo, Canada. mcconkey@uwaterloo.ca.', 'Canada|Canada|Canada', 19, 'Algorithms|Bacteria|Computational Biology|DNA, Bacterial|Databases, Genetic|Genome, Bacterial|High-Throughput Nucleotide Sequencing|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1186/s12859-014-0435-6', '25592313', 'Second-generation sequencers generate millions of relatively short, but error-prone, reads. These errors make sequence assembly and other downstream projects more challenging. Correcting these errors improves the quality of assemblies and projects which benefit from error-free reads.'),
(96529, 2015, 'bmc', 'Rational selection of experimental readout and intervention sites for reducing uncertainties in computational model predictions', 'Flassig, Robert J|Migal, Iryna|der Zalm, Esther van|Rihko-Struckmann, Liisa|Sundmacher, Kai', 'Department Process Systems Engineering (PSE), Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, Magdeburg, D-39106, Germany. flassig@mpi-magdeburg.mpg.de.|Department Process Systems Engineering (PSE), Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, Magdeburg, D-39106, Germany. migal@mpi-magdeburg.mpg.de.|Department Process Systems Engineering (PSE), Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, Magdeburg, D-39106, Germany. van_der_zalm@mpi-magdeburg.mpg.de.|Department Process Systems Engineering (PSE), Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, Magdeburg, D-39106, Germany. rihko@mpi-magdeburg.mpg.de.|Department Process Systems Engineering (PSE), Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, Magdeburg, D-39106, Germany. sundmacher@mpi-magdeburg.mpg.de.', 'Germany|Germany|Germany|Germany|Germany', 3, 'Chlorophyll|Chlorophyta|Computer Simulation|Likelihood Functions|Models, Biological|Uncertainty', 'Journal Article', '10.1186/s12859-014-0436-5', '25592474', 'Understanding the dynamics of biological processes can substantially be supported by computational models in the form of nonlinear ordinary differential equations (ODE). Typically, this model class contains many unknown parameters, which are estimated from inadequate and noisy data. Depending on the ODE structure, predictions based on unmeasured states and associated parameters are highly uncertain, even undetermined. For given data, profile likelihood analysis has been proven to be one of the most practically relevant approaches for analyzing the identifiability of an ODE structure, and thus model predictions. In case of highly uncertain or non-identifiable parameters, rational experimental design based on various approaches has shown to significantly reduce parameter uncertainties with minimal amount of effort.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96530, 2015, 'bmc', 'Decomposing the space of protein quaternary structures with the interface fragment pair library', 'Xie, Zhong-Ru|Chen, Jiawen|Zhao, Yilin|Wu, Yinghao', 'Department of Systems and Computational Biology, Albert Einstein College of Medicine of Yeshiva University, 1300 Morris Park Avenue, Bronx, NY, 10461, USA. Zhong-Ru.Xie@einstein.yu.edu.|Department of Systems and Computational Biology, Albert Einstein College of Medicine of Yeshiva University, 1300 Morris Park Avenue, Bronx, NY, 10461, USA. jiawen.chen@einstein.yu.edu.|Department of Systems and Computational Biology, Albert Einstein College of Medicine of Yeshiva University, 1300 Morris Park Avenue, Bronx, NY, 10461, USA. yzhao2@mail.einstein.yu.edu.|Department of Systems and Computational Biology, Albert Einstein College of Medicine of Yeshiva University, 1300 Morris Park Avenue, Bronx, NY, 10461, USA. yinghao.wu@einstein.yu.edu.', 'United States|United States|United States|United States', 4, 'Databases, Protein|Models, Molecular|Protein Interaction Domains and Motifs|Protein Structure, Quaternary|Protein Structure, Secondary', 'Journal Article', '10.1186/s12859-014-0437-4', '25592649', 'The physical interactions between proteins constitute the basis of protein quaternary structures. They dominate many biological processes in living cells. Deciphering the structural features of interacting proteins is essential to understand their cellular functions. Similar to the space of protein tertiary structures in which discrete patterns are clearly observed on fold or sub-fold motif levels, it has been found that the space of protein quaternary structures is highly degenerate due to the packing of compact secondary structure elements at interfaces. Therefore, it is necessary to further decompose the protein quaternary structural space into a more local representation.'),
(96531, 2015, 'bmc', 'Biomedical question answering using semantic relations', 'Hristovski, Dimitar|Dinevski, Dejan|Kastrin, Andrej|Rindflesch, Thomas C', 'Institute for Biostatistics and Medical Informatics, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, SI-1104, Ljubljana, Slovenia. dimitar.hristovski@mf.uni-lj.si.|Faculty of Medicine, University of Maribor, Slomškov trg 15, SI-2000, Maribor, Slovenia. dejan.dinevski@um.si.|Faculty of Information Studies, Ulica talcev 3, SI-8000, Novo mesto, Slovenia. andrej.kastrin@guest.arnes.si.|Lister Hill National Center for Biomedical Communications, U.S. National Library of Medicine, 8600 Rockville Pike, Bethesda, MD, 20894, USA. trindflesch@mail.nih.gov.', 'Slovenia|Slovenia|Slovenia|United States', 29, 'Abstracting and Indexing as Topic|Algorithms|Databases, Factual|Humans|Information Storage and Retrieval|Natural Language Processing|Oligonucleotide Array Sequence Analysis|Pharmacogenetics|Semantics|Software', 'Journal Article', '10.1186/s12859-014-0365-3', '25592675', 'The proliferation of the scientific literature in the field of biomedicine makes it difficult to keep abreast of current knowledge, even for domain experts. While general Web search engines and specialized information retrieval (IR) systems have made important strides in recent decades, the problem of accurate knowledge extraction from the biomedical literature is far from solved. Classical IR systems usually return a list of documents that have to be read by the user to extract relevant information. This tedious and time-consuming work can be lessened with automatic Question Answering (QA) systems, which aim to provide users with direct and precise answers to their questions. In this work we propose a novel methodology for QA based on semantic relations extracted from the biomedical literature.'),
(96532, 2015, 'bmc', 'Nonparametric Bayesian clustering to detect bipolar methylated genomic loci', 'Wu, Xiaowei|Sun, Ming-An|Zhu, Hongxiao|Xie, Hehuang', 'Department of Statistics, Virginia Tech, 250 Drillfield Drive, Blacksburg, 24061, VA, USA. xwwu@vt.edu.|Virginia Bioinformatics Institute, Virginia Tech, 1015 Life Science Circle, Blacksburg, 24061, VA, USA. masun@vt.edu.|Department of Statistics, Virginia Tech, 250 Drillfield Drive, Blacksburg, 24061, VA, USA. hongxiao@vt.edu.|Virginia Bioinformatics Institute, Virginia Tech, 1015 Life Science Circle, Blacksburg, 24061, VA, USA. davidxie@vt.edu.', 'United States|United States|United States|United States', 5, 'Alleles|Animals|B-Lymphocytes|Bayes Theorem|Cluster Analysis|DNA Methylation|Epigenesis, Genetic|Genetic Loci|Genomics|Humans|Mice|Neuroglia|Neurons|Neutrophils|Sequence Analysis, DNA|Statistics, Nonparametric', 'Journal Article', '10.1186/s12859-014-0439-2', '25592753', 'With recent development in sequencing technology, a large number of genome-wide DNA methylation studies have generated massive amounts of bisulfite sequencing data. The analysis of DNA methylation patterns helps researchers understand epigenetic regulatory mechanisms. Highly variable methylation patterns reflect stochastic fluctuations in DNA methylation, whereas well-structured methylation patterns imply deterministic methylation events. Among these methylation patterns, bipolar patterns are important as they may originate from allele-specific methylation (ASM) or cell-specific methylation (CSM).'),
(96533, 2015, 'bmc', 'Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study', 'Walker, Martin|Basáñez, María-Gloria|Ouédraogo, André Lin|Hermsen, Cornelus|Bousema, Teun|Churcher, Thomas S', 'Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Marys campus), Imperial College London, Norfolk Place, London, W2 1PG, UK. m.walker06@imperial.ac.uk.|Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Marys campus), Imperial College London, Norfolk Place, London, W2 1PG, UK. m.basanez@imperial.ac.uk.|Centre National de Recherche et de Formation sur le Paludisme, BP 2208, Ouagadougou, 01, Burkina Faso. andrelin.cnrfp@fasonet.bf.|Department of Medical Microbiology, Radboud University Medical Centre, Nijmegen, PO Box 9101, 6500 HB, Nijmegen, Netherlands. R.Hermsen@ncmls.ru.nl.|Department of Medical Microbiology, Radboud University Medical Centre, Nijmegen, PO Box 9101, 6500 HB, Nijmegen, Netherlands. Teun.Bousema@lshtm.ac.uk.|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Marys campus), Imperial College London, Norfolk Place, London, W2 1PG, UK. thomas.churcher@imperial.ac.uk.', 'United Kingdom|United Kingdom|Burkina Faso|Netherlands|Netherlands|United Kingdom', 10, 'Bayes Theorem|DNA, Protozoan|Data Interpretation, Statistical|Humans|Malaria, Falciparum|Plasmodium falciparum|Real-Time Polymerase Chain Reaction|Reproducibility of Results|Self-Sustained Sequence Replication|Sensitivity and Specificity', 'Journal Article', '10.1186/s12859-014-0402-2', '25592782', 'Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA.'),
(96534, 2015, 'bmc', 'Semi-supervised adaptive-height snipping of the hierarchical clustering tree', 'Obulkasim, Askar|Meijer, Gerrit A|van de Wiel, Mark A', 'Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. a.wubulikasimu@erasmusmc.nl.|Department of Pathology, VU University Medical Center, Amsterdam, The Netherlands. ga.meijer@vumc.nl.|Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. mark.vdwiel@vumc.nl.', 'Netherlands|Netherlands|Netherlands', 4, 'Algorithms|Cluster Analysis|DNA Copy Number Variations|Data Mining|Gene Expression Profiling|Genomics|Humans|Neoplasms|Survival Analysis', 'Journal Article', '10.1186/s12859-014-0448-1', '25592847', 'In genomics, hierarchical clustering (HC) is a popular method for grouping similar samples based on a distance measure. HC algorithms do not actually create clusters, but compute a hierarchical representation of the data set. Usually, a fixed height on the HC tree is used, and each contiguous branch of samples below that height is considered a separate cluster. Due to the fixed-height cutting, those clusters may not unravel significant functional coherence hidden deeper in the tree. Besides that, most existing approaches do not make use of available clinical information to guide cluster extraction from the HC. Thus, the identified subgroups may be difficult to interpret in relation to that information.'),
(96535, 2015, 'bmc', 'Fast individual ancestry inference from DNA sequence data leveraging allele frequencies for multiple populations', 'Bansal, Vikas|Libiger, Ondrej', 'Department of Pediatrics, University of California San Diego, 9500 Gilman Drive, La Jolla, 92093, CA, USA. vibansal@ucsd.edu.|Scripps Translational Science Institute, 3344 N Torrey Pines Court, La Jolla, 92037, CA, USA. ondrej@mdrevolution.com.', 'United States|United States', 17, 'Algorithms|Computer Simulation|Exome|Gene Frequency|Genetic Association Studies|Genetics, Population|Genome, Human|Genomics|Genotype|HapMap Project|Humans|Likelihood Functions|Linkage Disequilibrium|Models, Genetic|Population Groups|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-014-0418-7', '25592880', 'Estimation of individual ancestry from genetic data is useful for the analysis of disease association studies, understanding human population history and interpreting personal genomic variation. New, computationally efficient methods are needed for ancestry inference that can effectively utilize existing information about allele frequencies associated with different human populations and can work directly with DNA sequence reads.'),
(96536, 2015, 'bmc', 'Fast and robust group-wise eQTL mapping using sparse graphical models', 'Cheng, Wei|Shi, Yu|Zhang, Xiang|Wang, Wei', 'Department of Computer Science, UNC at Chapel Hill, 201 S Columbia St., Chapel Hill, 27599, NC, USA. weicheng@cs.unc.edu.|Computer Science at the University of Illinois at Urbana-Champaign, 201 North Goodwin Avenue, Urbana, 61801, IL, USA. shiyu7500@gmail.com.|Department of Elect. Eng. and Computer Science, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, 44106, OH, USA. xiang.zhang@case.edu.|Department of Computer Science, University of California, Los Angeles, 3531-G Boelter Hall, Los Angeles, 90095, CA, USA. weiwang@cs.ucla.edu.', 'United States|United States|United States|United States', 6, 'Algorithms|Chromosome Mapping|Computational Biology|Computer Graphics|Gene Ontology|Gene Regulatory Networks|Genome, Fungal|Models, Genetic|Quantitative Trait Loci|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/s12859-014-0421-z', '25593000', 'Genome-wide expression quantitative trait loci (eQTL) studies have emerged as a powerful tool to understand the genetic basis of gene expression and complex traits. The traditional eQTL methods focus on testing the associations between individual single-nucleotide polymorphisms (SNPs) and gene expression traits. A major drawback of this approach is that it cannot model the joint effect of a set of SNPs on a set of genes, which may correspond to hidden biological pathways.'),
(96537, 2015, 'bmc', 'Quantitative analysis of differences in copy numbers using read depth obtained from PCR-enriched samples and controls', 'Reinecke, Frank|Satya, Ravi Vijaya|DiCarlo, John', 'Bioinformatics Assay Design & Analysis, QIAGEN GmbH, Max-Volmer-Straße 4, Hilden, 40724, Germany. frank.reinecke@qiagen.com.|Bioinformatics Assay Design & Analysis, QIAGEN Sciences Inc., 6951 Executive Way, Frederick MD, 21703, USA. ravi.vijayasatya@qiagen.com.|Bioinformatics Assay Design & Analysis, QIAGEN Sciences Inc., 6951 Executive Way, Frederick MD, 21703, USA. john.dicarlo@qiagen.com.', 'Germany|United States|United States', 8, 'Algorithms|Case-Control Studies|DNA Copy Number Variations|High-Throughput Nucleotide Sequencing|Humans|Polymerase Chain Reaction|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1186/s12859-014-0428-5', '25626454', 'Next-generation sequencing (NGS) is rapidly becoming common practice in clinical diagnostics and cancer research. In addition to the detection of single nucleotide variants (SNVs), information on copy number variants (CNVs) is of great interest. Several algorithms exist to detect CNVs by analyzing whole genome sequencing data or data from samples enriched by hybridization-capture. PCR-enriched amplicon-sequencing data have special characteristics that have been taken into account by only one publicly available algorithm so far.'),
(96538, 2015, 'bmc', 'Fast inexact mapping using advanced tree exploration on backward search methods', 'Salavert, José|Tomás, Andrés|Tárraga, Joaquín|Medina, Ignacio|Dopazo, Joaquín|Blanquer, Ignacio', 'GRyCAP department of I3M, Universitat Politècnica de València, Building 8B, Camino de vera s/n, Valencia, 46022, Spain. josator@i3m.upv.es.|GRyCAP department of I3M, Universitat Politècnica de València, Building 8B, Camino de vera s/n, Valencia, 46022, Spain. antodo@i3m.upv.es.|Bioinformatics department of Centro de Investigación Príncipe Felipe, Autopista del Saler 16, Valencia, 46012, Spain. jtarraga@cipf.es.|Bioinformatics department of Centro de Investigación Príncipe Felipe, Autopista del Saler 16, Valencia, 46012, Spain. imedina@cipf.es.|Bioinformatics department of Centro de Investigación Príncipe Felipe, Autopista del Saler 16, Valencia, 46012, Spain. jdopazo@cipf.es.|GRyCAP department of I3M, Universitat Politècnica de València, Building 8B, Camino de vera s/n, Valencia, 46022, Spain. iblanque@dsic.upv.es.', 'Spain|Spain|Spain|Spain|Spain|Spain', 3, 'Algorithms|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-014-0438-3', '25626517', 'Short sequence mapping methods for Next Generation Sequencing consist on a combination of seeding techniques followed by local alignment based on dynamic programming approaches. Most seeding algorithms are based on backward search alignment, using the Burrows Wheeler Transform, the Ferragina and Manzini Index or Suffix Arrays. All these backward search algorithms have excellent performance, but their computational cost highly increases when allowing errors. In this paper, we discuss an inexact mapping algorithm based on pruning strategies for search tree exploration over genomic data.'),
(96539, 2015, 'bmc', 'MDAT- Aligning multiple domain arrangements', 'Kemena, Carsten|Bitard-Feildel, Tristan|Bornberg-Bauer, Erich', 'Institute for Evolution and Biodiversity, University of Münster, Hüfferstr. 1, Münster, Germany. c.kemena@uni-muenster.de.|Institute for Evolution and Biodiversity, University of Münster, Hüfferstr. 1, Münster, Germany. t.bitard.feildel@uni-muenster.de.|Institute for Evolution and Biodiversity, University of Münster, Hüfferstr. 1, Münster, Germany. ebb@uni-muenster.de.', 'Germany|Germany|Germany', 1, 'Algorithms|Humans|Programming Languages|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/s12859-014-0442-7', '25626688', 'Proteins are composed of domains, protein segments that fold independently from the rest of the protein and have a specific function. During evolution the arrangement of domains can change: domains are gained, lost or their order is rearranged. To facilitate the analysis of these changes we propose the use of multiple domain alignments.'),
(96540, 2015, 'bmc', 'ERD: a fast and reliable tool for RNA design including constraints', 'Esmaili-Taheri, Ali|Ganjtabesh, Mohammad', 'Department of Computer Science, School of Mathematics, Statistics, and Computer Science, College of Science, University of Tehran, Tehran, Iran. aliesmaili@ut.ac.ir.|Department of Computer Science, School of Mathematics, Statistics, and Computer Science, College of Science, University of Tehran, Tehran, Iran. mgtabesh@ut.ac.ir.', '-|-', 0, 'Algorithms|Base Sequence|Humans|Molecular Sequence Data|Nucleic Acid Conformation|RNA|RNA Folding|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/s12859-014-0444-5', '25626878', 'The function of an RNA in cellular processes is directly related to its structure. The free energy of RNA structure in another important key to its function as only some structures with a specific level of free energy can take part in cellular reactions. Therefore, to perform a specific function, a particular RNA structure with specific level of free energy is required. For a given RNA structure, the goal of the RNA design problem is to design an RNA sequence that folds into the given structure. To mimic the biological features of RNA sequences and structures, some sequence and energy constraints should be considered in designing RNA. Although the level of free energy is important, it is not considered in the available approaches for RNA design problem.'),
(96541, 2015, 'bmc', 'Exploring possible DNA structures in real-time polymerase kinetics using Pacific Biosciences sequencer data', 'Sawaya, Sterling|Boocock, James|Black, Michael A|Gemmell, Neil J', 'Institute for Behavioral Genetics, University of Colorado, Boulder, USA. sterlingsawaya@gmail.com.|Department of Biochemistry, University of Otago, Dunedin, New Zealand. james.boocock@otago.ac.nz.|Department of Biochemistry, University of Otago, Dunedin, New Zealand. mik.black@otago.ac.nz.|Department of Anatomy, and Allan Wilson Centre for Molecular Ecology and Evolution, University of Otago, Dunedin, New Zealand. neil.gemmell@otago.ac.nz.', 'United States|New Zealand|New Zealand|New Zealand', 4, 'DNA|DNA, Z-Form|DNA-Directed DNA Polymerase|G-Quadruplexes|Humans|Kinetics|Models, Molecular|Sequence Analysis, DNA', 'Journal Article', '10.1186/s12859-014-0449-0', '25626999', 'Pausing of DNA polymerase can indicate the presence of a DNA structure that differs from the canonical double-helix. Here we detail a method to investigate how polymerase pausing in the Pacific Biosciences sequencer reads can be related to DNA sequences. The Pacific Biosciences sequencer uses optics to view a polymerase and its interaction with a single DNA molecule in real-time, offering a unique way to detect potential alternative DNA structures.'),
(96542, 2015, 'bmc', 'Alignment-free clustering of transcription factor binding motifs using a genetic-k-medoids approach', 'Broin, Pilib Ó|Smith, Terry J|Golden, Aaron Aj', 'Department of Genetics, Albert Einstein College of Medicine, 1301 Morris Park Avenue, Bronx, New York, 10461, USA. pilib.obroin@einstein.yu.edu.|Department of Genetics, Albert Einstein College of Medicine, 1301 Morris Park Avenue, Bronx, New York, 10461, USA. terry.smith@nuigalway.ie.|Department of Genetics, Albert Einstein College of Medicine, 1301 Morris Park Avenue, Bronx, New York, 10461, USA. aaron.golden@einstein.yu.edu.', 'United States|United States|United States', 0, 'Algorithms|Binding Sites|Cluster Analysis|DNA|DNA-Binding Proteins|Databases, Genetic|Humans|Nucleotide Motifs|Protein Binding|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1186/s12859-015-0450-2', '25627106', 'Familial binding profiles (FBPs) represent the average binding specificity for a group of structurally related DNA-binding proteins. The construction of such profiles allows the classification of novel motifs based on similarity to known families, can help to reduce redundancy in motif databases and de novo prediction algorithms, and can provide valuable insights into the evolution of binding sites. Many current approaches to automated motif clustering rely on progressive tree-based techniques, and can suffer from so-called frozen sub-alignments, where motifs which are clustered early on in the process remain locked in place despite the potential for better placement at a later stage. In order to avoid this scenario, we have developed a genetic-k-medoids approach which allows motifs to move freely between clusters at any point in the clustering process.'),
(96543, 2015, 'bmc', 'An algorithm to enumerate all possible protein conformations verifying a set of distance constraints', 'Cassioli, Andrea|Bardiaux, Benjamin|Bouvier, Guillaume|Mucherino, Antonio|Alves, Rafael|Liberti, Leo|Nilges, Michael|Lavor, Carlile|Malliavin, Thxc3xa9rxc3xa8se E', 'LIX, Ecole Polytechnique, Palaiseau, 91128, France. cassioliandre@gmail.com.|Institut Pasteur, Structural Bioinformatics Unit, 25, rue du Dr Roux, Paris, 75015, France. benjamin.bardiaux@pasteur.fr.|Institut Pasteur, Structural Bioinformatics Unit, 25, rue du Dr Roux, Paris, 75015, France. guillaume.bouvier@pasteur.fr.|Universitxc3xa9 de Rennes-I, Rennes, France. antonio.mucherino@irisa.fr.|LIX, Ecole Polytechnique, Palaiseau, 91128, France. rafaelsoalves@uol.com.br.|LIX, Ecole Polytechnique, Palaiseau, 91128, France. liberti@lix.polytechnique.fr.|Institut Pasteur, Structural Bioinformatics Unit, 25, rue du Dr Roux, Paris, 75015, France. michael.nilges@pasteur.fr.|University of Campinas (IMECC-UNICAMP), Campinas-SP, 13083-859, Brasil. clavor@ime.unicamp.br.|Institut Pasteur, Structural Bioinformatics Unit, 25, rue du Dr Roux, Paris, 75015, France. therese.malliavin@pasteur.fr.', 'France|France|France|France|France|France|France|-|France', 0, 'Algorithms|Computational Biology|Computer Simulation|Humans|Models, Molecular|Peptide Fragments|Protein Conformation|Proteins', 'Journal Article', '10.1186/s12859-015-0451-1', '25627244', 'The determination of protein structures satisfying distance constraints is an important problem in structural biology. Whereas the most common method currently employed is simulated annealing, there have been other methods previously proposed in the literature. Most of them, however, are designed to find one solution only.'),
(96544, 2015, 'bmc', 'TagDust2: a generic method to extract reads from sequencing data', 'Lassmann, Timo', 'RIKEN Center for Life Science Technologies (CLST), RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045, Kanagawa, Japan. timolassmann@gmail.com.', 'Japan', 25, 'Computational Biology|Electronic Data Processing|Gene Library|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-015-0454-y', '25627334', 'Arguably the most basic step in the analysis of next generation sequencing data (NGS) involves the extraction of mappable reads from the raw reads produced by sequencing instruments. The presence of barcodes, adaptors and artifacts subject to sequencing errors makes this step non-trivial.'),
(96545, 2015, 'bmc', 'Candidate prioritization for low-abundant differentially expressed proteins in 2D-DIGE datasets', 'Nandal, Umesh K|Vlietstra, Wytze J|Byrman, Carsten|Jeeninga, Rienk E|Ringrose, Jeffrey H|van Kampen, Antoine H C|Speijer, Dave|Moerland, Perry D', 'Bioinformatics Laboratory, Academic Medical Center, University of Amsterdam, PO Box 22700, DE Amsterdam, 1100, The Netherlands. u.k.nandal@amc.uva.nl.|Bioinformatics Laboratory, Academic Medical Center, University of Amsterdam, PO Box 22700, DE Amsterdam, 1100, The Netherlands. wytze.vlietstra@gmail.com.|Bioinformatics Laboratory, Academic Medical Center, University of Amsterdam, PO Box 22700, DE Amsterdam, 1100, The Netherlands. carsten@byrman.demon.nl.|Laboratory of Experimental Virology, Department of Medical Microbiology, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center, University of Amsterdam, PO Box 22700, DE Amsterdam, 1100, The Netherlands. r.jeeninga@amc.uva.nl.|Laboratory of Experimental Virology, Department of Medical Microbiology, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center, University of Amsterdam, PO Box 22700, DE Amsterdam, 1100, The Netherlands. J.H.Ringrose@uu.nl.|Bioinformatics Laboratory, Academic Medical Center, University of Amsterdam, PO Box 22700, DE Amsterdam, 1100, The Netherlands. a.h.vankampen@amc.uva.nl.|Department of Medical Biochemistry, Academic Medical Center, University of Amsterdam, PO Box 22700, DE Amsterdam, 1100, The Netherlands. d.speijer@amc.uva.nl.|Bioinformatics Laboratory, Academic Medical Center, University of Amsterdam, PO Box 22700, DE Amsterdam, 1100, The Netherlands. p.d.moerland@amc.uva.nl.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Cells, Cultured|Electrophoresis, Gel, Two-Dimensional|HIV Infections|HIV-1|Humans|Peptide Fragments|Proteins|Proteomics|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization|T-Lymphocytes|Two-Dimensional Difference Gel Electrophoresis', 'Journal Article', '10.1186/s12859-015-0455-x', '25627479', 'Two-dimensional differential gel electrophoresis (2D-DIGE) provides a powerful technique to separate proteins on their isoelectric point and apparent molecular mass and quantify changes in protein expression. Abundantly available proteins in spots can be identified using mass spectrometry-based approaches. However, identification is often not possible for low-abundant proteins.'),
(96546, 2015, 'bmc', 'Aber-OWL: a framework for ontology-based data access in biology', 'Hoehndorf, Robert|Slater, Luke|Schofield, Paul N|Gkoutos, Georgios V', 'Computational Bioscience Research Center, King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Saudi Arabia. robert.hoehndorf@kaust.edu.sa.|Computational Bioscience Research Center, King Abdullah University of Science and Technology, 4700 KAUST, Thuwal, 23955-6900, Saudi Arabia. luke.slater@kaust.edu.sa.|Department of Physiology, Development & Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK. pns12@cam.ac.uk.|Department of Computer Science, Aberystwyth University, Llandinam Building, Aberystwyth, SY23 3DB, UK. geg18@aber.ac.uk.', 'Saudi Arabia|Saudi Arabia|United Kingdom|United Kingdom', 38, 'Apoptosis Regulatory Proteins|Biological Ontologies|Computational Biology|Databases, Factual|Genome-Wide Association Study|Heart Septal Defects, Ventricular|Humans|Internet|Knowledge|Language|Models, Genetic|Phenotype|Semantics|Software', 'Journal Article', '10.1186/s12859-015-0456-9', '25627673', 'Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within these ontologies relies on the use of automated reasoning.'),
(96547, 2015, 'bmc', 'SFMetrics: an analysis tool for scanning force microscopy images of biomolecules', 'Sánchez, Humberto|Wyman, Claire', 'Department of Genetics, Erasmus University Medical Center, Rotterdam 3000CA, The Netherlands. h.sanchezgonzalez@erasmusmc.nl.|Department of Genetics, Erasmus University Medical Center, Rotterdam 3000CA, The Netherlands. h.sanchezgonzalez@erasmusmc.nl.', 'Netherlands|Netherlands', 11, 'Algorithms|DNA|Imaging, Three-Dimensional|Internet|Microscopy, Atomic Force|Nanotechnology|Nucleic Acid Conformation|Protein Conformation|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1186/s12859-015-0457-8', '25627825', 'Scanning force microscopy (SFM) allows direct, rapid and high-resolution visualization of single molecular complexes, irregular shapes and differences in sizes are immediately revealed by the scanning tip in three-dimensional images. However, high-throughput analysis of SFM data is limited by the lack of versatile software tools accessible to SFM users. Most existing SFM software tools are aimed at broad general use: from material-surface analysis to visualization of biomolecules.'),
(96548, 2015, 'bmc', 'Computational study of xcexb2-N-acetylhexosaminidase from Talaromyces flavus, a glycosidase with high substrate flexibility', 'Kulik, Natallia|Slxc3xa1movxc3xa1, Kristxc3xbdna|Ettrich, Rxc3xbcdiger|Kxc5x99en, Vladimxc3xadr', 'Department of Structure and Function of Proteins, Institute of Nanobiology and Structural Biology of GCRC, Academy of Sciences of the Czech Republic, Zamek 136, 37333, Nove Hrady, Czech Republic. kulik@nh.cas.cz.|Laboratory of Biotransformation, Institute of Microbiology, Academy of Sciences of the Czech Republic, Videnska 1083, 14220, Praha 4, Czech Republic. slamova.kristyna@gmail.com.|Department of Structure and Function of Proteins, Institute of Nanobiology and Structural Biology of GCRC, Academy of Sciences of the Czech Republic, Zamek 136, 37333, Nove Hrady, Czech Republic. ettrich@nh.cas.cz.|Laboratory of Biotransformation, Institute of Microbiology, Academy of Sciences of the Czech Republic, Videnska 1083, 14220, Praha 4, Czech Republic. kren@biomed.cas.cz.', '-|-|-|-', 0, 'Amino Acid Sequence|Catalytic Domain|Computational Biology|Glycosylation|Kinetics|Models, Molecular|Molecular Dynamics Simulation|Molecular Sequence Data|Phylogeny|Reproducibility of Results|Sequence Homology, Amino Acid|Structure-Activity Relationship|Substrate Specificity|Talaromyces|beta-N-Acetylhexosaminidases', 'Journal Article', '10.1186/s12859-015-0465-8', '25627923', 'xcexb2-N-Acetylhexosaminidase (GH20) from the filamentous fungus Talaromyces flavus, previously identified as a prominent enzyme in the biosynthesis of modified glycosides, lacks a high resolution three-dimensional structure so far. Despite of high sequence identity to previously reported Aspergillus oryzae and Penicilluim oxalicum xcexb2-N-acetylhexosaminidases, this enzyme tolerates significantly better substrate modification. Understanding of key structural features, prediction of effective mutants and potential substrate characteristics prior to their synthesis are of general interest.'),
(96549, 2015, 'bmc', 'The acquisition of novel N-glycosylation sites in conserved proteins during human evolution', 'Kim, Dong Seon|Hahn, Yoonsoo', 'Laboratory of Biotransformation, Institute of Microbiology, Academy of Sciences of the Czech Republic, Videnska 1083, 14220, Praha 4, Czech Republic. kren@biomed.cas.cz.|Department of Life Science, Research Center for Biomolecules and Biosystems, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu 156-756, Seoul, Korea. hahny@cau.ac.kr.', '-|-', 11, 'Adipocytes|Amino Acid Sequence|Animals|Antigens, CD|Cell Adhesion Molecules, Neuronal|Databases, Protein|Evolution, Molecular|Fetal Proteins|Glycoproteins|Glycosylation|Humans|Molecular Sequence Data|Protein Folding|Protein Transport|Proteome|Thyroglobulin|Thyroxine', 'Journal Article', '10.1186/s12859-015-0468-5', '25628020', 'N-linked protein glycosylation plays an important role in various biological processes, including protein folding and trafficking, and cell adhesion and signaling. The acquisition of a novel N-glycosylation site may have significant effect on protein structure and function, and therefore, on the phenotype.'),
(96550, 2015, 'bmc', 'MARZ: an algorithm to combinatorially analyze gapped n-mer models of transcription factor binding', 'Zellers, Rowan G|Drewell, Robert A|Dresch, Jacqueline M', 'Department of Computer Science, Harvey Mudd College, 301 Platt Boulevard, Claremont CA, 91711, USA. rzellers@hmc.edu.|Biology Department, Clark University, 950 Main Street, Worcester MA, 01610, USA. rdrewell@clarku.edu.|Department of Mathematics and Statistics, Amherst College, P.O. Box 5000, Amherst MA, 01002, USA. jdresch@amherst.edu.', 'United States|United States|United States', 5, 'Algorithms|Animals|Binding Sites|Computational Biology|DNA-Binding Proteins|Drosophila|Drosophila Proteins|Nucleotides|Position-Specific Scoring Matrices|Protein Binding|Transcription Factors', 'Journal Article', '10.1186/s12859-014-0446-3', '25637281', 'A key challenge in understanding the molecular mechanisms that control gene regulation is the characterization of the specificity with which transcription factor proteins bind to specific DNA sequences. A number of computational approaches have been developed to examine these interactions, including simple mononucleotide and dinucleotide position weight matrix models.'),
(96551, 2015, 'bmc', 'PCalign: a method to quantify physicochemical similarity of protein-protein interfaces', 'Cheng, Shanshan|Zhang, Yang|Brooks, Charles L', 'Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA. sscheng@umich.edu.|Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA. zhng@umich.edu.|Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA. brookscl@umich.edu.', 'United States|United States|United States', 0, 'Algorithms|Chemical Phenomena|Humans|Models, Molecular|Protein Binding|Proteins|Software', 'Journal Article', '10.1186/s12859-015-0471-x', '25638036', 'Structural comparison of protein-protein interfaces provides valuable insights into the functional relationship between proteins, which may not solely arise from shared evolutionary origin. A few methods that exist for such comparative studies have focused on structural models determined at atomic resolution, and may miss out interesting patterns present in large macromolecular complexes that are typically solved by low-resolution techniques.'),
(96552, 2015, 'bmc', 'A systematic evaluation of high-dimensional, ensemble-based regression for exploring large model spaces in microbiome analyses', 'Shankar, Jyoti|Szpakowski, Sebastian|Solis, Norma V|Mounaud, Stephanie|Liu, Hong|Losada, Liliana|Nierman, William C|Filler, Scott G', 'J. Craig Venter Institute, 9704, Medical Center Drive, Rockville, Maryland, 20850, US. jyoti.shankar@gmail.com.|J. Craig Venter Institute, 9704, Medical Center Drive, Rockville, Maryland, 20850, US. shpakoo@gmail.com.|Los Angeles Biomedical Research Institute at Harbor, UCLA Medical Center, 1124 West Carson Street, Torrance, California, 90509, US. nsolis@labiomed.org.|J. Craig Venter Institute, 9704, Medical Center Drive, Rockville, Maryland, 20850, US. smounaud@jcvi.org.|Los Angeles Biomedical Research Institute at Harbor, UCLA Medical Center, 1124 West Carson Street, Torrance, California, 90509, US. hliu@labiomed.org.|J. Craig Venter Institute, 9704, Medical Center Drive, Rockville, Maryland, 20850, US. llosada@jcvi.org.|J. Craig Venter Institute, 9704, Medical Center Drive, Rockville, Maryland, 20850, US. wnierman@jcvi.org.|Los Angeles Biomedical Research Institute at Harbor, UCLA Medical Center, 1124 West Carson Street, Torrance, California, 90509, US. sfiller@ucla.edu.', '-|-|-|-|-|-|-|-', 10, 'Anti-Bacterial Agents|Bayes Theorem|Candida albicans|Candidiasis|Computer Simulation|Microbiota|Models, Statistical|Research Design', 'Evaluation Studies', '10.1186/s12859-015-0467-6', '25638274', 'Microbiome studies incorporate next-generation sequencing to obtain profiles of microbial communities. Data generated from these experiments are high-dimensional with a rich correlation structure but modest sample sizes. A statistical model that utilizes these microbiome profiles to explain a clinical or biological endpoint needs to tackle high-dimensionality resulting from the very large space of variable configurations. Ensemble models are a class of approaches that can address high-dimensionality by aggregating information across large model spaces. Although such models are popular in fields as diverse as economics and genetics, their performance on microbiome data has been largely unexplored.'),
(96553, 2015, 'bmc', 'Sensitive and highly resolved identification of RNA-protein interaction sites in PAR-CLIP data', 'Comoglio, Federico|Sievers, Cem|Paro, Renato', 'Department of Biosystems Science and Engineering, Swiss Federal Institute of Technology Zurich, Mattenstrasse 26, Basel, 4058, Switzerland. federico.comoglio@bsse.ethz.ch.|Department of Biosystems Science and Engineering, Swiss Federal Institute of Technology Zurich, Mattenstrasse 26, Basel, 4058, Switzerland. csievers@mgh.harvard.edu.|Department of Biosystems Science and Engineering, Swiss Federal Institute of Technology Zurich, Mattenstrasse 26, Basel, 4058, Switzerland. renato.paro@bsse.ethz.ch.', 'Switzerland|Switzerland|Switzerland', 18, 'Algorithms|Bayes Theorem|Binding Sites|HEK293 Cells|High-Throughput Nucleotide Sequencing|Humans|Immunoprecipitation|MicroRNAs|Models, Statistical|RNA|RNA-Binding Proteins|Sequence Analysis, RNA|Transcriptome', 'Journal Article', '10.1186/s12859-015-0470-y', '25638391', 'PAR-CLIP is a recently developed Next Generation Sequencing-based method enabling transcriptome-wide identification of interaction sites between RNA and RNA-binding proteins. The PAR-CLIP procedure induces specific base transitions that originate from sites of RNA-protein interactions and can therefore guide the identification of binding sites. However, additional sources of transitions, such as cell type-specific SNPs and sequencing errors, challenge the inference of binding sites and suitable statistical approaches are crucial to control false discovery rates. In addition, a highly resolved delineation of binding sites followed by an extensive downstream analysis is necessary for a comprehensive characterization of the protein binding preferences and the subsequent design of validation experiments.'),
(96554, 2015, 'bmc', 'Evaluation and improvements of clustering algorithms for detecting remote homologous protein families', 'Bernardes, Juliana S|Vieira, Fabio R J|Costa, Lygia M M|Zaverucha, Gerson', 'Programa de Engenharia de Sistemas e Computação, COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil. juliana.silva_bernardes@upmc.fr.|Programa de Engenharia de Sistemas e Computação, COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil. fjimenez@cos.ufrj.br.|Engenharia de Computação e Informação, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil. lmmc@poli.ufrj.br.|Programa de Engenharia de Sistemas e Computação, COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil. gerson@cos.ufrj.br.', 'Brazil|Brazil|Brazil|Brazil', 13, 'Algorithms|Cluster Analysis|Evolution, Molecular|Humans|Multigene Family|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1186/s12859-014-0445-4', '25651949', 'An important problem in computational biology is the automatic detection of protein families (groups of homologous sequences). Clustering sequences into families is at the heart of most comparative studies dealing with protein evolution, structure, and function. Many methods have been developed for this task, and they perform reasonably well (over 0.88 of F-measure) when grouping proteins with high sequence identity. However, for highly diverged proteins the performance of these methods can be much lower, mainly because a common evolutionary origin is not deduced directly from sequence similarity. To the best of our knowledge, a systematic evaluation of clustering methods over distant homologous proteins is still lacking.'),
(96555, 2015, 'bmc', 'Data-intensive analysis of HIV mutations', 'Ozahata, Mina Cintho|Sabino, Ester Cerdeira|Diaz, Ricardo Sobhie|Cesar, Roberto M|Ferreira, João Eduardo', 'Department of Computer Science - DCC, University of São Paulo, Rua do Matão, 1010, CEP 05508-090 São Paulo, SP, Brazil. mina.cintho@usp.br.|Sangue Foundation, Health State Secretary, Department of Molecular Biology, Serology Division, Av Dr Enéas de Carvalho Aguiar, Cerqueira Cesar, CEP 05403-000 São Paulo, 155, SP, Brazil. sabinoec@gmail.com.|Federal University of São Paulo, Rua Pedro de Toledo, São Paulo, 669, CEP 04039-032, SP, Brazil. rsdiaz@catg.com.br.|Department of Computer Science - DCC, University of São Paulo, Rua do Matão, 1010, CEP 05508-090 São Paulo, SP, Brazil. cesar@ime.usp.br.|Sangue Foundation, Health State Secretary, Department of Molecular Biology, Serology Division, Av Dr Enéas de Carvalho Aguiar, Cerqueira Cesar, CEP 05403-000 São Paulo, 155, SP, Brazil. jef@ime.usp.br.', 'Brazil|Brazil|Brazil|Brazil|Brazil', 0, 'Algorithms|Anti-HIV Agents|Drug Resistance, Viral|Genotype|HIV Infections|HIV Protease|HIV Reverse Transcriptase|HIV-1|Humans|Mutation', 'Journal Article', '10.1186/s12859-015-0452-0', '25652056', 'In this study, clustering was performed using a bitmap representation of HIV reverse transcriptase and protease sequences, to produce an unsupervised classification of HIV sequences. The classification will aid our understanding of the interactions between mutations and drug resistance. 10,229 HIV genomic sequences from the protease and reverse transcriptase regions of the pol gene and antiretroviral resistant related mutations represented in an 82-dimensional binary vector space were analyzed.'),
(96556, 2015, 'bmc', 'MBBC: an efficient approach for metagenomic binning based on clustering', 'Wang, Ying|Hu, Haiyan|Li, Xiaoman', 'Department of Electric Engineering and Computer Science, University of Central Florida, Orlando, FL, 32816, USA. ying2010@knights.ucf.edu.|Department of Electric Engineering and Computer Science, University of Central Florida, Orlando, FL, 32816, USA. haihu@cs.ucf.edu.|Department of Electric Engineering and Computer Science, University of Central Florida, Orlando, FL, 32816, USA. xiaoman@mail.ucf.edu.', 'United States|United States|United States', 13, 'Algorithms|Cluster Analysis|Markov Chains|Metagenomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-015-0473-8', '25652152', 'Binning environmental shotgun reads is one of the most fundamental tasks in metagenomic studies, in which mixed reads from different species or operational taxonomical units (OTUs) are separated into different groups. While dozens of binning methods are available, there is still room for improvement.'),
(96557, 2015, 'bmc', 'BACA: bubble chArt to compare annotations', 'Fortino, Vittorio|Alenius, Harri|Greco, Dario', 'Unit of Systems Toxicology, Finnish Institute of Occupational Health (FIOH), Topeliuksenkatu 41b, 00250, Helsinki, Finland. vittorio.fortino@ttl.fi.|Unit of Systems Toxicology, Finnish Institute of Occupational Health (FIOH), Topeliuksenkatu 41b, 00250, Helsinki, Finland. harri.alenius@ttl.fi.|Unit of Systems Toxicology, Finnish Institute of Occupational Health (FIOH), Topeliuksenkatu 41b, 00250, Helsinki, Finland. dario.greco@ttl.fi.', 'Finland|Finland|Finland', 11, 'Computational Biology|Databases, Genetic|Genes|Molecular Sequence Annotation|Proteins|Software', 'Journal Article', '10.1186/s12859-015-0477-4', '25652236', 'DAVID is the most popular tool for interpreting large lists of gene/proteins classically produced in high-throughput experiments. However, the use of DAVID website becomes difficult when analyzing multiple gene lists, for it does not provide an adequate visualization tool to show/compare multiple enrichment results in a concise and informative manner.'),
(96558, 2015, 'bmc', 'Mutations and CpG islands among hepatitis B virus genotypes in Europe', 'Zhong, Chengyao|Hou, Zhiwei|Huang, Jihua|Xie, Qingdong|Zhong, Ying', 'Faculty of Science and Engineering, University Paul Sabatier, Toulouse, 31062, France. chengyao.zhong@gmail.com.|Key Laboratory of Birth Defects and Reproductive Health of National Health and Family Planning Commission, Chongqing Research Institute for Population and Family Planning Science and Technology, Chongqing, 400020, China. desonny@163.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. en_huang@sina.cn.|Research Center for Reproductive Medicine, Shantou University Medical College, Shantou, 515041, China. qdxie@stu.edu.cn.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'France|China|China|China|China', 5, 'CpG Islands|DNA Methylation|Epigenesis, Genetic|Europe|Genome, Viral|Genotype|Hepatitis B|Hepatitis B virus|Humans|Mutation', 'Journal Article', '10.1186/s12859-015-0481-8', '25652331', 'Hepatitis B virus (HBV) genotypes have a distinct geographical distribution and influence disease progression and treatment outcomes. The purpose of this study was to investigate the distribution of HBV genotypes in Europe, the impact of mutation of different genotypes on HBV gene abnormalities, the features of CpG islands in each genotype and their potential role in epigenetic regulation.'),
(96559, 2015, 'bmc', 'Characterization and identification of ubiquitin conjugation sites with E3 ligase recognition specificities', 'Nguyen, Van-Nui|Huang, Kai-Yao|Huang, Chien-Hsun|Chang, Tzu-Hao|Bretaña, Neil|Lai, K|Weng, Julia|Lee, Tzong-Yi', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China|China|China|China', 15, 'Animals|Computational Biology|Humans|Mice|Position-Specific Scoring Matrices|Protein Binding|Substrate Specificity|Ubiquitin|Ubiquitin-Protein Ligases|Ubiquitination', 'Journal Article', '10.1186/1471-2105-16-S1-S1', '25707307', 'In eukaryotes, ubiquitin-conjugation is an important mechanism underlying proteasome-mediated degradation of proteins, and as such, plays an essential role in the regulation of many cellular processes. In the ubiquitin-proteasome pathway, E3 ligases play important roles by recognizing a specific protein substrate and catalyzing the attachment of ubiquitin to a lysine (K) residue. As more and more experimental data on ubiquitin conjugation sites become available, it becomes possible to develop prediction models that can be scaled to big data. However, no development that focuses on the investigation of ubiquitinated substrate specificities has existed. Herein, we present an approach that exploits an iteratively statistical method to identify ubiquitin conjugation sites with substrate site specificities.'),
(96560, 2015, 'bmc', 'Data-driven encoding for quantitative genetic trait prediction', 'He, Dan|Wang, Zhanyong|Parida, Laxmi', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China', 13, 'Alleles|Animals|Genetic Markers|Genotype|Heterozygote|Homozygote|Humans|Linear Models|Models, Genetic|Phenotype|Plants|Polymorphism, Single Nucleotide|Quantitative Trait, Heritable', 'Journal Article', '10.1186/1471-2105-16-S1-S10', '25707435', 'Given a set of biallelic molecular markers, such as SNPs, with genotype values on a collection of plant, animal or human samples, the goal of quantitative genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Quantitative genetic trait prediction is usually represented as linear regression models which require quantitative encodings for the genotypes: the three distinct genotype values, corresponding to one heterozygous and two homozygous alleles, are usually coded as integers, and manipulated algebraically in the model. Further, epistasis between multiple markers is modeled as multiplication between the markers: it is unclear that the regression model continues to be effective under this. In this work we investigate the effects of encodings to the quantitative genetic trait prediction problem.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96561, 2015, 'bmc', 'PEAT: an intelligent and efficient paired-end sequencing adapter trimming algorithm', 'Li, Yun-Lung|Weng, Jui-Cheng|Hsiao, Chiung-Chih|Chou, Min-Te|Tseng, Chin-Wen|Hung, Jui-Hung', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China|China', 25, 'Algorithms|Chromatin Immunoprecipitation|High-Throughput Nucleotide Sequencing|Sequence Analysis, DNA|Sequence Analysis, RNA|Software|Time Factors', 'Journal Article', '10.1186/1471-2105-16-S1-S2', '25707528', 'In modern paired-end sequencing protocols short DNA fragments lead to adapter-appended reads. Current paired-end adapter removal approaches trim adapter by scanning the fragment of adapter on the 3 end of the reads, which are not competent in some applications.'),
(96562, 2015, 'bmc', 'IAOseq: inferring abundance of overlapping genes using RNA-seq data', 'Sun, Hong|Yang, Shuang|Tun, Liangliang|Li, Yixue', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China', 1, 'Computational Biology|Data Mining|Gene Expression Profiling|Gene Library|Genes, Overlapping|RNA, Messenger|Sequence Analysis, RNA|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-16-S1-S3', '25707673', 'Overlapping transcription constitutes a common mechanism for regulating gene expression. A major limitation of the overlapping transcription assays is the lack of high throughput expression data.'),
(96563, 2015, 'bmc', 'Estimating copy numbers of alleles from population-scale high-throughput sequencing data', 'Mimori, Takahiro|Nariai, Naoki|Kojima, Kaname|Sato, Yukuto|Kawai, Yosuke|Yamaguchi-Kabata, Yumi|Nagasaki, Masao', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China|China|China', 0, 'Alleles|Amylases|Bayes Theorem|Computational Biology|DNA Copy Number Variations|Female|Genetics, Population|Haplotypes|High-Throughput Nucleotide Sequencing|Humans|Male|Models, Statistical|Pedigree|Phenotype|Saliva|Utah', 'Journal Article', '10.1186/1471-2105-16-S1-S4', '25707811', 'With the recent development of microarray and high-throughput sequencing (HTS) technologies, a number of studies have revealed catalogs of copy number variants (CNVs) and their association with phenotypes and complex traits. In parallel, a number of approaches to predict CNV regions and genotypes are proposed for both microarray and HTS data. However, only a few approaches focus on haplotyping of CNV loci.'),
(96564, 2015, 'bmc', 'An interpretable rule-based diagnostic classification of diabetic nephropathy among type 2 diabetes patients', 'Huang, Guan-Mau|Huang, Kai-Yao|Lee, Tzong-Yi|Weng, Julia', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China', 30, 'Bayes Theorem|Computational Biology|Decision Trees|Diabetes Mellitus, Type 2|Diabetic Nephropathies|Disease Susceptibility|Female|Genotype|Humans|Male|Models, Statistical|Risk Assessment|Sex Factors|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-16-S1-S5', '25707942', 'The prevalence of type 2 diabetes is increasing at an alarming rate. Various complications are associated with type 2 diabetes, with diabetic nephropathy being the leading cause of renal failure among diabetics. Often, when patients are diagnosed with diabetic nephropathy, their renal functions have already been significantly damaged. Therefore, a risk prediction tool may be beneficial for the implementation of early treatment and prevention.'),
(96565, 2015, 'bmc', 'Network tuned multiple rank aggregation and applications to gene ranking', 'Wang, Wenhui|Zhou, Xianghong|Liu, Zhenqiu|Sun, Fengzhu', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China', 2, 'Computational Biology|Fungal Proteins|Gene Ontology|Protein Interaction Mapping|Software', 'Journal Article', '10.1186/1471-2105-16-S1-S6', '25708095', 'With the development of various high throughput technologies and analysis methods, researchers can study different aspects of a biological phenomenon simultaneously or one aspect repeatedly with different experimental techniques and analysis methods. The output from each study is a rank list of components of interest. Aggregation of the rank lists of components, such as proteins, genes and single nucleotide variants (SNV), produced by these experiments has been proven to be helpful in both filtering the noise and bringing forth a more complete understanding of the biological problems. Current available rank aggregation methods do not consider the network information that has been observed to provide vital contributions in many data integration studies. We developed network tuned rank aggregation methods incorporating network information and demonstrated its superior performance over aggregation methods without network information. '),
(96566, 2015, 'bmc', 'On the packing density of the unbound protein-protein interaction interface and its implications in dynamics', 'Lin, Jau-Ji|Lin, Zih-Lin|Hwang, Jenn-Kang|Huang, Tsun-Tsao', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China', 2, 'Computational Biology|Models, Molecular|Protein Binding|Protein Conformation|Protein Interaction Mapping|Protein Subunits', 'Journal Article', '10.1186/1471-2105-16-S1-S7', '25708145', 'Characterizing the interface residues will help shed light on protein-protein interactions, which are involved in many important biological processes. Many studies focus on characterizing sequence or structure features of protein interfaces, but there are few studies characterizing the dynamics of interfaces. Therefore, we would like to know whether there is any specific dynamics pattern in the protein-protein interaction interfaces. Thermal fluctuation is an important dynamical property for a residue, and could be quickly estimated by local packing density without large computation since studies have showen closely relationship between these two properties. Therefore, we divided surface of an unbound subunit (free protein subunits before they are involved in forming the protein complexes) into several separate regions, and compared their average thermal fluctuations of different regions in order to characterize the dynamics pattern in unbound protein-protein interaction interfaces.'),
(96567, 2015, 'bmc', 'SCMPSP: Prediction and characterization of photosynthetic proteins based on a scoring card method', 'Vasylenko, Tamara|Liou, Yi-Fan|Chen, Hong-An|Charoenkwan, Phasit|Huang, Hui-Ling|Ho, Shinn-Ying', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China|China', 8, 'Bayes Theorem|Chloroplast Proteins|Computational Biology|Databases, Protein|Dipeptides|Gene Ontology|Intracellular Membranes|Photosynthesis|Protein Structure, Secondary|Support Vector Machine|Water', 'Journal Article', '10.1186/1471-2105-16-S1-S8', '25708243', 'Photosynthetic proteins (PSPs) greatly differ in their structure and function as they are involved in numerous subprocesses that take place inside an organelle called a chloroplast. Few studies predict PSPs from sequences due to their high variety of sequences and structues. This work aims to predict and characterize PSPs by establishing the datasets of PSP and non-PSP sequences and developing prediction methods.'),
(96568, 2015, 'bmc', 'ViralmiR: a support-vector-machine-based method for predicting viral microRNA precursors', 'Huang, Kai-Yao|Lee, Tzong-Yi|Teng, Yu-Chuan|Chang, Tzu-Hao', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China', 0, 'Computational Biology|Humans|MicroRNAs|RNA Precursors|RNA, Messenger|RNA, Viral|Sequence Analysis, RNA|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-16-S1-S9', '25708359', 'microRNAs (miRNAs) play a vital role in development, oncogenesis, and apoptosis by binding to mRNAs to regulate the posttranscriptional level of coding genes in mammals, plants, and insects. Recent studies have demonstrated that the expression of viral miRNAs is associated with the ability of the virus to infect a host. Identifying potential viral miRNAs from experimental sequence data is valuable for deciphering virus-host interactions. Thus far, a specific predictive model for viral miRNA identification has yet to be developed.'),
(96569, 2015, 'bmc', 'Highlights from the tenth ISCB Student Council Symposium 2014', 'Rahman, Farzana|Wilkins, Katie|Jacobsen, Annika|Junge, Alexander|Vicedo, Esmeralda|DeBlasio, Dan|Jigisha, Anupama|Di Domenico, Tomás', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China|China|China|China', 0, 'Computational Biology|Drug Resistance, Multiple|High-Throughput Nucleotide Sequencing|Microsatellite Repeats|Peer Review, Research|Publishing|RNA, Messenger|Sequence Analysis, DNA', 'Congress', '10.1186/1471-2105-16-S1-S9', '25708534', 'This report summarizes the scientific content and activities of the annual symposium organized by the Student Council of the International Society for Computational Biology (ISCB), held in conjunction with the Intelligent Systems for Molecular Biology (ISMB) conference in Boston, USA, on July 11th, 2014.'),
(96570, 2015, 'bmc', 'Highlights from the Third International Society for Computational Biology (ISCB) European Student Council Symposium 2014', 'Francescatto, Margherita|Hermans, Susanne M A|Babaei, Sepideh|Vicedo, Esmeralda|Borrel, Alexandre|Meysman, Pieter', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China|China', 0, 'Awards and Prizes|Computational Biology|Databases, Factual|Gene Regulatory Networks|Models, Statistical|Peer Review, Research', 'Congress', '10.1186/1471-2105-16-S1-S9', '25708611', 'In this meeting report, we give an overview of the talks, presentations and posters presented at the third European Symposium of the International Society for Computational Biology (ISCB) Student Council. The event was organized as a satellite meeting of the 13th European Conference for Computational Biology (ECCB) and took place in Strasbourg, France on September 6th, 2014.'),
(96571, 2015, 'bmc', 'Effective alignment of RNA pseudoknot structures using partition function posterior log-odds scores', 'Song, Yang|Hua, Lei|Shapiro, Bruce A|Wang, Jason T L', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China', 0, 'Algorithms|Base Pair Mismatch|Base Pairing|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/s12859-015-0464-9', '25727492', 'RNA pseudoknots play important roles in many biological processes. Previous methods for comparative pseudoknot analysis mainly focus on simultaneous folding and alignment of RNA sequences. Little work has been done to align two known RNA secondary structures with pseudoknots taking into account both sequence and structure information of the two RNAs.'),
(96572, 2015, 'bmc', 'Integration of gene expression and DNA-methylation profiles improves molecular subtype classification in acute myeloid leukemia', 'Taskesen, Erdogan|Babaei, Sepideh|Reinders, Marcel M J|de Ridder, Jeroen', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China', 0, 'Adult|Biomarkers, Tumor|DNA Methylation|DNA, Neoplasm|Gene Expression Profiling|Humans|Karyotyping|Leukemia, Myeloid, Acute|Neoplasm Staging|Signal Transduction', 'Journal Article', '10.1186/1471-2105-16-S4-S5', '25734246', 'Acute Myeloid Leukemia (AML) is characterized by various cytogenetic and molecular abnormalities. Detection of these abnormalities is important in the risk-classification of patients but requires laborious experimentation. Various studies showed that gene expression profiles (GEP), and the gene signatures derived from GEP, can be used for the prediction of subtypes in AML. Similarly, successful prediction was also achieved by exploiting DNA-methylation profiles (DMP). There are, however, no studies that compared classification accuracy and performance between GEP and DMP, neither are there studies that integrated both types of data to determine whether predictive power can be improved.'),
(96573, 2015, 'bmc', 'Beef quality parameters estimation using ultrasound and color images', 'Nunes, Jose|Piquerez, Martín|Pujadas, Leonardo|Armstrong, Eileen|Fernández, Alicia|Lecumberry, Federico', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China|China', 0, 'Adipose Tissue|Animals|Cattle|Databases, Factual|Food Quality|Meat|Models, Statistical|Muscle, Skeletal|Regression Analysis|Ribs|Ultrasonography', 'Journal Article', '10.1186/1471-2105-16-S4-S6', '25734452', 'Beef quality measurement is a complex task with high economic impact. There is high interest in obtaining an automatic quality parameters estimation in live cattle or post mortem. In this paper we set out to obtain beef quality estimates from the analysis of ultrasound (in vivo) and color images (post mortem), with the measurement of various parameters related to tenderness and amount of meat: rib eye area, percentage of intramuscular fat and backfat thickness or subcutaneous fat.'),
(96574, 2015, 'bmc', 'Gram-positive and Gram-negative subcellular localization using rotation forest and physicochemical-based features', 'Dehzangi, Abdollah|Sohrabi, Sohrab|Heffernan, Rhys|Sharma, Alok|Lyons, James|Paliwal, Kuldip|Sattar, Abdul', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China|China|China', 21, 'Algorithms|Bacterial Proteins|Cluster Analysis|Computational Biology|Databases, Protein|Gram-Negative Bacteria|Gram-Positive Bacteria|Models, Statistical|Predictive Value of Tests|Sequence Analysis, Protein|Subcellular Fractions', 'Journal Article', '10.1186/1471-2105-16-S4-S1', '25734546', 'The functioning of a protein relies on its location in the cell. Therefore, predicting protein subcellular localization is an important step towards protein function prediction. Recent studies have shown that relying on Gene Ontology (GO) for feature extraction can improve the prediction performance. However, for newly sequenced proteins, the GO is not available. Therefore, for these cases, the prediction performance of GO based methods degrade significantly.'),
(96575, 2015, 'bmc', 'Analysis of miRNA expression profiles in breast cancer using biclustering', 'Fiannaca, Antonino|La Rosa, Massimo|La Paglia, Laura|Rizzo, Riccardo|Urso, Alfonso', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China', 0, 'Algorithms|Breast Neoplasms|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|MicroRNAs', 'Journal Article', '10.1186/1471-2105-16-S4-S7', '25734576', 'MicroRNAs (miRNAs) are important key regulators in multiple cellular functions, due to their a crucial role in different physiological processes. MiRNAs are differentially expressed in specific tissues, during specific cell status, or in different diseases as tumours. RNA sequencing (RNA-seq) is a Next Generation Sequencing (NGS) method for the analysis of differential gene expression. Using machine learning algorithms, it is possible to improve the functional significance interpretation of miRNA in the analysis and interpretation of data from RNA-seq. Furthermore, we tried to identify some patterns of deregulated miRNA in human breast cancer (BC), in order to give a contribution in the understanding of this type of cancer at the molecular level.'),
(96576, 2015, 'bmc', 'Problems with the nested granularity of feature domains in bioinformatics: the eXtasy case', 'Popovic, Dusan|Sifrim, Alejandro|Davis, Jesse|Moreau, Yves|De Moor, Bart', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China', 0, 'Algorithms|Computational Biology|Computer Simulation|Databases, Factual|Humans|Models, Theoretical|Mutation|Proteins', 'Journal Article', '10.1186/1471-2105-16-S4-S2', '25734591', 'Data from biomedical domains often have an inherit hierarchical structure. As this structure is usually implicit, its existence can be overlooked by practitioners interested in constructing and evaluating predictive models from such data. Ignoring these constructs leads to potentially problematic and the routinely unrecognized bias in the models and results. In this work, we discuss this bias in detail and propose a simple, sampling-based solution for it. Next, we explore its sources and extent on synthetic data. Finally, we demonstrate how the state-of-the-art variant prioritization framework, eXtasy, benefits from using the described approach in its Random forest-based core classification model.'),
(96577, 2015, 'bmc', 'BgN-Score and BsN-Score: bagging and boosting based ensemble neural networks scoring functions for accurate binding affinity prediction of protein-ligand complexes', 'Ashtawy, Hossam M|Mahapatra, Nihar R', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China', 0, 'Algorithms|Artificial Intelligence|Binding Sites|Computational Biology|Humans|Ligands|Models, Statistical|Neural Networks (Computer)|Protein Binding|Proteins', 'Journal Article', '10.1186/1471-2105-16-S4-S8', '25734685', 'Accurately predicting the binding affinities of large sets of protein-ligand complexes is a key challenge in computational biomolecular science, with applications in drug discovery, chemical biology, and structural biology. Since a scoring function (SF) is used to score, rank, and identify drug leads, the fidelity with which it predicts the affinity of a ligand candidate for a proteins binding site has a significant bearing on the accuracy of virtual screening. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited predictive power has been a major roadblock toward cost-effective drug discovery. Therefore, in this work, we present novel SFs employing a large ensemble of neural networks (NN) in conjunction with a diverse set of physicochemical and geometrical features characterizing protein-ligand complexes to predict binding affinity.'),
(96578, 2015, 'bmc', 'The relative vertex clustering value--a new criterion for the fast discovery of functional modules in protein interaction networks', 'Ibrahim, Zina M|Ngom, Alioune', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China', 3, 'Algorithms|Cluster Analysis|Computational Biology|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-16-S4-S3', '25734691', 'Cellular processes are known to be modular and are realized by groups of proteins implicated in common biological functions. Such groups of proteins are called functional modules, and many community detection methods have been devised for their discovery from protein interaction networks (PINs) data. In current agglomerative clustering approaches, vertices with just a very few neighbors are often classified as separate clusters, which does not make sense biologically. Also, a major limitation of agglomerative techniques is that their computational efficiency do not scale well to large PINs. Finally, PIN data obtained from large scale experiments generally contain many false positives, and this makes it hard for agglomerative clustering methods to find the correct clusters, since they are known to be sensitive to noisy data.'),
(96579, 2015, 'bmc', 'An integrated approach of gene expression and DNA-methylation profiles of WNT signaling genes uncovers novel prognostic markers in acute myeloid leukemia', 'Taskesen, Erdogan|Staal, Frank J T|Reinders, Marcel J T', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China', 10, 'Adult|Biomarkers, Tumor|DNA Methylation|DNA, Neoplasm|Gene Expression Profiling|Gene Regulatory Networks|Humans|Leukemia, Myeloid, Acute|Prognosis|Promoter Regions, Genetic|Signal Transduction|Survival Rate|Wnt Proteins', 'Journal Article', '10.1186/1471-2105-16-S4-S4', '25734857', 'The wingless-Int (WNT) pathway has an essential role in cell regulation of hematopoietic stem cells (HSC). For Acute Myeloid Leukemia (AML), the malignant counterpart of HSC, currently only a selective number of genes of the WNT pathway are analyzed by using either gene expression or DNA-methylation profiles for the identification of prognostic markers and potential candidate targets for drug therapy. It is known that mRNA expression is controlled by DNA-methylation and that specific patterns can infer the ability to differentiate biological differences, thus a combined analysis using all WNT annotated genes could provide more insight in the WNT signaling.'),
(96580, 2015, 'bmc', 'A molecular structure matching approach to efficient identification of endogenous mammalian biochemical structures', 'Hamdalla, Mai A|Ammar, Reda A|Rajasekaran, Sanguthevar', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China', 0, 'Animals|Databases, Factual|Mammals|Metabolomics|Molecular Structure|Pharmaceutical Preparations|Small Molecule Libraries|Software', 'Journal Article', '10.1186/1471-2105-16-S5-S11', '25859612', 'Metabolomics is the study of small molecules, called metabolites, of a cell, tissue or organism. It is of particular interest as endogenous metabolites represent the phenotype resulting from gene expression. A major challenge in metabolomics research is the structural identification of unknown biochemical compounds in complex biofluids. In this paper we present an efficient cheminformatics tool, BioSMXpress that uses known endogenous mammalian biochemicals and graph matching methods to identify endogenous mammalian biochemical structures in chemical structure space. The results of a comprehensive set of empirical experiments suggest that BioSMXpress identifies endogenous mammalian biochemical structures with high accuracy. BioSMXpress is 8 times faster than our previous work BioSM without compromising the accuracy of the predictions made. BioSMXpress is freely available at http://engr.uconn.edu/~rajasek/BioSMXpress.zip. '),
(96581, 2015, 'bmc', 'Exploiting topic modeling to boost metagenomic reads binning', 'Zhang, Ruichang|Cheng, Zhanzhan|Guan, Jihong|Zhou, Shuigeng', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China', 0, 'Algorithms|Cluster Analysis|DNA Barcoding, Taxonomic|Genome, Bacterial|High-Throughput Nucleotide Sequencing|Metagenome|Metagenomics|Microbiota|Molecular Sequence Annotation|Phylogeny|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-16-S5-S2', '25859745', 'With the rapid development of high-throughput technologies, researchers can sequence the whole metagenome of a microbial community sampled directly from the environment. The assignment of these metagenomic reads into different species or taxonomical classes is a vital step for metagenomic analysis, which is referred to as binning of metagenomic data.'),
(96582, 2015, 'bmc', 'Identifying overlapping mutated driver pathways by constructing gene networks in cancer', 'Wu, Hao|Gao, Lin|Li, Feng|Song, Fei|Yang, Xiaofei|Kasabov, Nikola', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China|China', 0, 'Algorithms|Female|Gene Regulatory Networks|Genomics|Glioblastoma|Head and Neck Neoplasms|Humans|Lung Neoplasms|Mutation|Neoplasm Proteins|Neoplasms|Ovarian Neoplasms|Signal Transduction', 'Journal Article', '10.1186/1471-2105-16-S5-S3', '25859819', 'Large-scale cancer genomic projects are providing lots of data on genomic, epigenomic and gene expression aberrations in many cancer types. One key challenge is to detect functional driver pathways and to filter out nonfunctional passenger genes in cancer genomics. Vandin et al. introduced the Maximum Weight Sub-matrix Problem to find driver pathways and showed that it is an NP-hard problem.'),
(96583, 2015, 'bmc', 'Improving multiple sequence alignment by using better guide trees', 'Zhan, Qing|Ye, Yongtao|Lam, Tak-Wah|Yiu, Siu-Ming|Wang, Yadong|Ting, Hing-Fung', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China|China', 5, 'Computational Biology|Computer Simulation|Databases, Genetic|Evolution, Molecular|Humans|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-16-S5-S4', '25859903', 'Progressive sequence alignment is one of the most commonly used method for multiple sequence alignment. Roughly speaking, the method first builds a guide tree, and then aligns the sequences progressively according to the topology of the tree. It is believed that guide trees are very important to progressive alignment, a better guide tree will give an alignment with higher accuracy. Recently, we have proposed an adaptive method for constructing guide trees. This paper studies the quality of the guide trees constructed by such method. Our study showed that our adaptive method can be used to improve the accuracy of many different progressive MSA tools. In fact, we give evidences showing that the guide trees constructed by the adaptive method are among the best. '),
(96584, 2015, 'bmc', 'An integrated network of microRNA and gene expression in ovarian cancer', 'Quitadamo, Andrew|Tian, Lu|Hall, Benika|Shi, Xinghua', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China', 20, 'Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|MicroRNAs|Ovarian Neoplasms|RNA, Messenger', 'Journal Article', '10.1186/1471-2105-16-S5-S5', '25860109', 'Ovarian cancer is a deadly female reproductive cancer. Understanding the biological mechanisms underlying ovarian cancer could help lead to quicker and more accurate diagnosis and more effective treatments. Both changes in microRNA(miRNA) expression and miRNA/mRNA dysregulation have been associated with ovarian cancer. With the availability of whole-genome miRNA and mRNA sequencing we now have new potentials to study these associations. In this study, we performed a comprehensive analysis of miRNA and mRNA expression in ovarian cancer using an integrative network approach combined with association analysis.'),
(96585, 2015, 'bmc', 'Comparing a knowledge-driven approach to a supervised machine learning approach in large-scale extraction of drug-side effect relationships from free-text biomedical literature', 'Xu, Rong|Wang, QuanQiu', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China', 12, 'Artificial Intelligence|Biological Ontologies|Data Mining|Databases, Pharmaceutical|Drug Discovery|Drug Repositioning|Drug-Related Side Effects and Adverse Reactions|Humans|Knowledge Bases|MEDLINE|Periodicals as Topic|Pharmaceutical Preparations|Phenotype|Search Engine', 'Comparative Study', '10.1186/1471-2105-16-S5-S6', '25860223', 'Systems approaches to studying drug-side-effect (drug-SE) associations are emerging as an active research area for both drug target discovery and drug repositioning. However, a comprehensive drug-SE association knowledge base does not exist. In this study, we present a novel knowledge-driven (KD) approach to effectively extract a large number of drug-SE pairs from published biomedical literature.'),
(96586, 2015, 'bmc', 'Isomorphism and similarity for 2-generation pedigrees', 'Jiang, Haitao|Lin, Guohui|Tong, Weitian|Zhu, Daming|Zhu, Binhai', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China', 0, 'Algorithms|Computational Biology|Computer Simulation|Female|Humans|Male|Pedigree', 'Journal Article', '10.1186/1471-2105-16-S5-S7', '25860335', 'We consider the emerging problem of comparing the similarity between (unlabeled) pedigrees. More specifically, we focus on the simplest pedigrees, namely, the 2-generation pedigrees. We show that the isomorphism testing for two 2-generation pedigrees is GI-hard. If the 2-generation pedigrees are monogamous (i.e., each individual at level-1 can mate with exactly one partner) then the isomorphism testing problem can be solved in polynomial time. We then consider the problem by relaxing it into an NP-complete decomposition problem which can be formulated as the Minimum Common Integer Pair Partition (MCIPP) problem, which we show to be FPT by exploiting a property of the optimal solution. While there is still some difficulty to overcome, this lays down a solid foundation for this research. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96587, 2015, 'bmc', 'Re-alignment of the unmapped reads with base quality score', 'Peng, Xiaoqing|Wang, Jianxin|Zhang, Zhen|Xiao, Qianghua|Li, Min|Pan, Yi', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China|China', 6, 'Chromosome Mapping|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Programming Languages|Quality Control|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-16-S5-S8', '25860434', 'Based on the next generation genome sequencing technologies, a variety of biological applications are developed, while alignment is the first step once the sequencing reads are obtained. In recent years, many software tools have been developed to efficiently and accurately align short reads to the reference genome. However, there are still many reads that cant be mapped to the reference genome, due to the exceeding of allowable mismatches. Moreover, besides the unmapped reads, the reads with low mapping qualities are also excluded from the downstream analysis, such as variance calling. If we can take advantages of the confident segments of these reads, not only can the alignment rates be improved, but also more information will be provided for the downstream analysis.'),
(96588, 2015, 'bmc', 'PIGS: improved estimates of identity-by-descent probabilities by probabilistic IBD graph sampling', 'Park, Danny S|Baran, Yael|Hormozdiari, Farhad|Eng, Celeste|Torgerson, Dara G|Burchard, Esteban G|Zaitlen, Noah', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China|China|China|China', 0, 'Asthma|Cohort Studies|Computational Biology|Computer Simulation|Genetics, Population|Genome, Human|Haplotypes|Hispanic Americans|Humans|Polymorphism, Single Nucleotide|Probability', 'Journal Article', '10.1186/1471-2105-16-S5-S9', '25860540', 'Identifying segments in the genome of different individuals that are identical-by-descent (IBD) is a fundamental element of genetics. IBD data is used for numerous applications including demographic inference, heritability estimation, and mapping disease loci. Simultaneous detection of IBD over multiple haplotypes has proven to be computationally difficult. To overcome this, many state of the art methods estimate the probability of IBD between each pair of haplotypes separately. While computationally efficient, these methods fail to leverage the clique structure of IBD resulting in less powerful IBD identification, especially for small IBD segments. '),
(96589, 2015, 'bmc', 'A comparative study of disease genes and drug targets in the human protein interactome', 'Sun, Jingchun|Zhu, Kevin|Zheng, W|Xu, Hua', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China', 0, 'Cluster Analysis|Computational Biology|Disease|Gene Expression Regulation|Genome-Wide Association Study|Humans|Pharmaceutical Preparations|Protein Interaction Maps|Proteins', 'Journal Article', '10.1186/1471-2105-16-S5-S1', '25861037', 'Disease genes cause or contribute genetically to the development of the most complex diseases. Drugs are the major approaches to treat the complex disease through interacting with their targets. Thus, drug targets are critical for treatment efficacy. However, the interrelationship between the disease genes and drug targets is not clear.'),
(96590, 2015, 'bmc', 'Using epigenomics data to predict gene expression in lung cancer', 'Li, Jeffery|Ching, Travers|Huang, Sijia|Garmire, Lana X', 'Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.|Jinxin Research Institute for Reproductive Medicine and Genetics, Chengdu Jinjiang Hospital for Maternal and Child Health Care, Chengdu, 610066, China. yzhong2014@126.com.', 'China|China|China|China', 26, 'Artificial Intelligence|CpG Islands|DNA Methylation|Epigenomics|Gene Expression Regulation, Neoplastic|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Histones|Humans|Lung Neoplasms', 'Journal Article', '10.1186/1471-2105-16-S5-S10', '25861082', 'Epigenetic alterations are known to correlate with changes in gene expression among various diseases including cancers. However, quantitative models that accurately predict the up or down regulation of gene expression are currently lacking.'),
(96591, 2015, 'bmc', 'Identifying restrictions in the order of accumulation of mutations during tumor progression: effects of passengers, evolutionary models, and sampling', 'Diaz-Uriarte, Ramon', 'Dept. Biochemistry, Universidad Autónoma de Madrid, Instituto de Investigaciones Biomédicas Alberto Sols (UAM-CSIC), Arzobispo Morcillo, 4, 28029, Madrid, Spain. ramon.diaz@iib.uam.es.', 'Spain', 0, 'Bayes Theorem|Biological Evolution|Cell Transformation, Neoplastic|Cross-Sectional Studies|Disease Progression|Humans|Models, Theoretical|Mutation|Neoplasm Proteins|Neoplasms|Sample Size', 'Journal Article', '10.1186/s12859-015-0466-7', '25879190', 'Cancer progression is caused by the sequential accumulation of mutations, but not all orders of accumulation are equally likely. When the fixation of some mutations depends on the presence of previous ones, identifying restrictions in the order of accumulation of mutations can lead to the discovery of therapeutic targets and diagnostic markers. The purpose of this study is to conduct a comprehensive comparison of the performance of all available methods to identify these restrictions from cross-sectional data. I used simulated data sets (where the true restrictions are known) but, in contrast to previous work, I embedded restrictions within evolutionary models of tumor progression that included passengers (mutations not responsible for the development of cancer, known to be very common). This allowed me to assess, for the first time, the effects of having to filter out passengers, of sampling schemes (when, how, and how many samples), and of deviations from order restrictions.'),
(96592, 2015, 'bmc', 'A multiobjective approach to the genetic code adaptability problem', 'de Oliveira, Lariza Laura|de Oliveira, Paulo S L|Tinós, Renato', 'Department of Computing and Mathematics, University of São Paulo, Ribeirão Preto, Brazil. larizalaura@gmail.com.|Brazilian Biosciences National Laboratory, Campinas, Brazil. paulo.oliveira@lnbio.cnpem.br.|Department of Computing and Mathematics, University of São Paulo, Ribeirão Preto, Brazil. rtinos@ffclrp.usp.br.', 'Brazil|Brazil|Brazil', 12, 'Algorithms|Amino Acids|Evolution, Molecular|Genetic Code|Humans|Models, Genetic|Mutation|Protein Biosynthesis|Selection, Genetic', 'Journal Article', '10.1186/s12859-015-0480-9', '25879480', 'The organization of the canonical code has intrigued researches since it was first described. If we consider all codes mapping the 64 codes into 20 amino acids and one stop codon, there are more than 1.51×10(84) possible genetic codes. The main question related to the organization of the genetic code is why exactly the canonical code was selected among this huge number of possible genetic codes. Many researchers argue that the organization of the canonical code is a product of natural selection and that the codes robustness against mutations would support this hypothesis. In order to investigate the natural selection hypothesis, some researches employ optimization algorithms to identify regions of the genetic code space where best codes, according to a given evaluation function, can be found (engineering approach). The optimization process uses only one objective to evaluate the codes, generally based on the robustness for an amino acid property. Only one objective is also employed in the statistical approach for the comparison of the canonical code with random codes. We propose a multiobjective approach where two or more objectives are considered simultaneously to evaluate the genetic codes.'),
(96593, 2015, 'bmc', 'Identification of indels in next-generation sequencing data', 'Ratan, Aakrosh|Olson, Thomas L|Loughran, Thomas P|Miller, Webb', 'Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, 506, Wartik Laboratory, University Park, PA, 16802, USA. ratan@bx.psu.edu.|Department of Medicine, Hematology and Oncology, and the University of Virginia Cancer Center, University of Virginia, Charlottesville, VA, 22908, USA. tlo6s@eservices.virginia.edu.|Department of Medicine, Hematology and Oncology, and the University of Virginia Cancer Center, University of Virginia, Charlottesville, VA, 22908, USA. tl7cs@hscmail.mcc.virginia.edu.|Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, 506, Wartik Laboratory, University Park, PA, 16802, USA. webb@bx.psu.edu.', 'United States|United States|United States|United States', 0, 'Algorithms|Biomarkers, Tumor|Case-Control Studies|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|INDEL Mutation|Neoplasms|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Comparative Study', '10.1186/s12859-015-0483-6', '25879703', 'The discovery and mapping of genomic variants is an essential step in most analysis done using sequencing reads. There are a number of mature software packages and associated pipelines that can identify single nucleotide polymorphisms (SNPs) with a high degree of concordance. However, the same cannot be said for tools that are used to identify the other types of variants. Indels represent the second most frequent class of variants in the human genome, after single nucleotide polymorphisms. The reliable detection of indels is still a challenging problem, especially for variants that are longer than a few bases.'),
(96594, 2015, 'bmc', 'BiNChE: a web tool and library for chemical enrichment analysis based on the ChEBI ontology', 'Moreno, Pablo|Beisken, Stephan|Harsha, Bhavana|Muthukrishnan, Venkatesh|Tudose, Ilinca|Dekker, Adriano|Dornfeldt, Stefanie|Taruttis, Franziska|Grosse, Ivo|Hastings, Janna|Neumann, Steffen|Steinbeck, Christoph', 'Cheminformatics and Metabolism, European Molecular Biology Laboratory - European Bioinformatics Institute, Cambridge, UK. pmoreno@ebi.ac.uk.|Cheminformatics and Metabolism, European Molecular Biology Laboratory - European Bioinformatics Institute, Cambridge, UK. beisken@ebi.ac.uk.|Cheminformatics and Metabolism, European Molecular Biology Laboratory - European Bioinformatics Institute, Cambridge, UK. bh4@sanger.ac.uk.|Cheminformatics and Metabolism, European Molecular Biology Laboratory - European Bioinformatics Institute, Cambridge, UK. venkat@ebi.ac.uk.|Cheminformatics and Metabolism, European Molecular Biology Laboratory - European Bioinformatics Institute, Cambridge, UK. tudose@ebi.ac.uk.|Cheminformatics and Metabolism, European Molecular Biology Laboratory - European Bioinformatics Institute, Cambridge, UK. adekker@ebi.ac.uk.|Dept. of Stress- and Developmental Biology, Leibniz Institute of Plant Biochemistry, Halle, Germany. stefanie.dornfeldt@student.uni-halle.de.|Dept. of Stress- and Developmental Biology, Leibniz Institute of Plant Biochemistry, Halle, Germany. franziska_taruttis@yahoo.de.|Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany. grosse@informatik.uni-halle.de.|Cheminformatics and Metabolism, European Molecular Biology Laboratory - European Bioinformatics Institute, Cambridge, UK. hastings@ebi.ac.uk.|Dept. of Stress- and Developmental Biology, Leibniz Institute of Plant Biochemistry, Halle, Germany. steffen.neumann@ipb-halle.de.|Cheminformatics and Metabolism, European Molecular Biology Laboratory - European Bioinformatics Institute, Cambridge, UK. steinbeck@ebi.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|Germany|Germany|Germany|United Kingdom|Germany|United Kingdom', 0, 'Biological Ontologies|Databases, Chemical|Internet|Pharmaceutical Preparations|Small Molecule Libraries|Software', 'Journal Article', '10.1186/s12859-015-0486-3', '25879798', 'Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes. While many tools exist that run enrichment analysis for protein sets annotated with the Gene Ontology, there are only a few that can be used for small molecules enrichment analysis.'),
(96595, 2015, 'bmc', 'Spectral gene set enrichment (SGSE)', 'Frost, H Robert|Li, Zhigang|Moore, Jason H', 'Institute of Quantitative Biomedical Sciences, Geisel School of Medicine, Lebanon, NH, 03756, USA. rob.frost@dartmouth.edu.|Institute of Quantitative Biomedical Sciences, Geisel School of Medicine, Lebanon, NH, 03756, USA. zhigang.li@dartmouth.edu.|Institute of Quantitative Biomedical Sciences, Geisel School of Medicine, Lebanon, NH, 03756, USA. jason.h.moore@dartmouth.edu.', 'Lebanon|Lebanon|Lebanon', 4, 'Algorithms|Biomarkers, Tumor|Cluster Analysis|Gene Expression Profiling|Gene Regulatory Networks|Genomics|Humans|Leukemia|Lymphoma, Large B-Cell, Diffuse|Microarray Analysis', 'Journal Article', '10.1186/s12859-015-0490-7', '25879888', 'Gene set testing is typically performed in a supervised context to quantify the association between groups of genes and a clinical phenotype. In many cases, however, a gene set-based interpretation of genomic data is desired in the absence of a phenotype variable. Although methods exist for unsupervised gene set testing, they predominantly compute enrichment relative to clusters of the genomic variables with performance strongly dependent on the clustering algorithm and number of clusters.'),
(96596, 2015, 'bmc', 'Inferring bona fide transfrags in RNA-Seq derived-transcriptome assemblies of non-model organisms', 'Mbandi, Stanley Kimbung|Hesse, Uljana|van Heusden, Peter|Christoffels, Alan', 'South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa. mbandi@sanbi.ac.za.|South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa. uljana@sanbi.ac.za.|South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa. pvh@sanbi.ac.za.|South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa. alan@sanbi.ac.za.', 'South Africa|South Africa|South Africa|South Africa', 0, 'Algorithms|Cluster Analysis|Genome, Fungal|High-Throughput Nucleotide Sequencing|Molecular Sequence Annotation|Neurospora crassa|Sequence Analysis, RNA|Software|Transcriptome', 'Journal Article', '10.1186/s12859-015-0492-5', '25880035', 'De novo transcriptome assembly of short transcribed fragments (transfrags) produced from sequencing-by-synthesis technologies often results in redundant datasets with differing levels of unassembled, partially assembled or mis-assembled transcripts. Post-assembly processing intended to reduce redundancy typically involves reassembly or clustering of assembled sequences. However, these approaches are mostly based on common word heuristics and often create clusters of biologically unrelated sequences, resulting in loss of unique transfrags annotations and propagation of mis-assemblies.'),
(96597, 2015, 'bmc', 'A high performance prediction of HPV genotypes by Chaos game representation and singular value decomposition', 'Tanchotsrinon, Watcharaporn|Lursinsap, Chidchanok|Poovorawan, Yong', 'Advanced Virtual and Intelligent Computing Research Center (AVIC), Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Phayathai Road, Bangkok, Thailand. Watcharaporn.T@Student.chula.ac.th.|Advanced Virtual and Intelligent Computing Research Center (AVIC), Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Phayathai Road, Bangkok, Thailand. lchidcha@gmail.com.|Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Phayathai Road, Bangkok, Thailand. Yong.P@chula.ac.th.', 'Thailand|Thailand|Thailand', 13, 'Female|Genome, Viral|Genotype|Humans|Neural Networks (Computer)|Papillomaviridae|Sequence Analysis, DNA|Uterine Cervical Neoplasms', 'Journal Article', '10.1186/s12859-015-0493-4', '25880169', 'Human Papillomavirus (HPV) genotyping is an important approach to fight cervical cancer due to the relevant information regarding risk stratification for diagnosis and the better understanding of the relationship of HPV with carcinogenesis. This paper proposed two new feature extraction techniques, i.e. ChaosCentroid and ChaosFrequency, for predicting HPV genotypes associated with the cancer. The additional diversified 12 HPV genotypes, i.e. types 6, 11, 16, 18, 31, 33, 35, 45, 52, 53, 58, and 66, were studied in this paper. In our proposed techniques, a partitioned Chaos Game Representation (CGR) is deployed to represent HPV genomes. ChaosCentroid captures the structure of sequences in terms of centroid of each sub-region with Euclidean distances among the centroids and the center of CGR as the relations of all sub-regions. ChaosFrequency extracts the statistical distribution of mono-, di-, or higher order nucleotides along HPV genomes and forms a matrix of frequency of dots in each sub-region. For performance evaluation, four different types of classifiers, i.e. Multi-layer Perceptron, Radial Basis Function, K-Nearest Neighbor, and Fuzzy K-Nearest Neighbor Techniques were deployed, and our best results from each classifier were compared with the NCBI genotyping tool.'),
(96598, 2015, 'bmc', 'MetCap: a bioinformatics probe design pipeline for large-scale targeted metagenomics', 'Kushwaha, Sandeep K|Manoharan, Lokeshwaran|Meerupati, Tejashwari|Hedlund, Katarina|Ahrén, Dag', 'Department of Biology, Lund University, Ecology Building, 223 62, Lund, Sweden. sandeep.kushwaha@biol.lu.se.|Department of Biology, Lund University, Ecology Building, 223 62, Lund, Sweden. lokeshwaran.manoharan@biol.lu.se.|Department of Biology, Lund University, Ecology Building, 223 62, Lund, Sweden. tejashwari.meerupati@biol.lu.se.|Department of Biology, Lund University, Ecology Building, 223 62, Lund, Sweden. katarina.hedlund@biol.lu.se.|Department of Biology, Lund University, Ecology Building, 223 62, Lund, Sweden. dag.ahren@biol.lu.se.', 'Sweden|Sweden|Sweden|Sweden|Sweden', 7, 'Computational Biology|DNA Primers|Ecology|Environment|Metagenome|Metagenomics|Sequence Analysis, DNA|Software|Soil', 'Journal Article', '10.1186/s12859-015-0501-8', '25880302', 'Massive sequencing of genes from different environments has evolved metagenomics as central to enhancing the understanding of the wide diversity of micro-organisms and their roles in driving ecological processes. Reduced cost and high throughput sequencing has made large-scale projects achievable to a wider group of researchers, though complete metagenome sequencing is still a daunting task in terms of sequencing as well as the downstream bioinformatics analyses. Alternative approaches such as targeted amplicon sequencing requires custom PCR primer generation, and is not scalable to thousands of genes or gene families.'),
(96599, 2015, 'bmc', 'Novel genetic matching methods for handling population stratification in genome-wide association studies', 'Lacour, André|Schüller, Vitalia|Drichel, Dmitriy|Herold, Christine|Jessen, Frank|Leber, Markus|Maier, Wolfgang|Noethen, Markus M|Ramirez, Alfredo|Vaitsiakhovich, Tatsiana|Becker, Tim', 'German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, Bonn, 53127, Germany. andre.lacour@dzne.de.|German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, Bonn, 53127, Germany. schueller@imbie.meb.uni-bonn.de.|German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, Bonn, 53127, Germany. dmitriy.drichel@dzne.de.|German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, Bonn, 53127, Germany. christine.herold@dzne.de.|German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, Bonn, 53127, Germany. frank.jessen@ukb.uni-bonn.de.|Institut für Medizinische Biometrie, Informatik und Epidemiologie, Universität Bonn, Sigmund-Freud-Str. 25, Bonn, 53127, Germany. leber@imbie.uni-bonn.de.|Abteilung für Psychiatrie und Psychotherapie, Universitätsklinikum Bonn, Sigmund-Freud-Str. 25, Bonn, 53127, Germany. wolfgang.maier@ukb.uni-bonn.de.|Institut für Humangenetik and Life & Brain Center, Universität Bonn, Sigmund-Freud-Str. 25, Bonn, 53127, Germany. markus.noethen@uni-bonn.de.|Abteilung für Psychiatrie und Psychotherapie, Universitätsklinikum Bonn, Sigmund-Freud-Str. 25, Bonn, 53127, Germany. alfredo.ramirez@ukb.uni-bonn.de.|Institut für Medizinische Biometrie, Informatik und Epidemiologie, Universität Bonn, Sigmund-Freud-Str. 25, Bonn, 53127, Germany. vait@imbie.uni-bonn.de.|German Center for Neurodegenerative Diseases (DZNE), Sigmund-Freud-Str. 25, Bonn, 53127, Germany. tim.becker@dzne.de.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 4, 'Alzheimer Disease|Case-Control Studies|Cluster Analysis|Genetics, Population|Genome-Wide Association Study|Genotype|Humans|Logistic Models|Population Groups', 'Comparative Study', '10.1186/s12859-015-0521-4', '25880419', 'A usually confronted problem in association studies is the occurrence of population stratification. In this work, we propose a novel framework to consider population matchings in the contexts of genome-wide and sequencing association studies. We employ pairwise and groupwise optimal case-control matchings and present an agglomerative hierarchical clustering, both based on a genetic similarity score matrix. In order to ensure that the resulting matches obtained from the matching algorithm capture correctly the population structure, we propose and discuss two stratum validation methods. We also invent a decisive extension to the Cochran-Armitage Trend test to explicitly take into account the particular population structure.'),
(96600, 2015, 'bmc', 'Aro: a machine learning approach to identifying single molecules and estimating classification error in fluorescence microscopy images', 'Wu, Allison Chia-Yi|Rifkin, Scott A', 'Graduate Program in Bioinformatics and Systems Biology, University of California, La Jolla, San Diego, CA, USA. allison.cy.wu@gmail.com.|Graduate Program in Bioinformatics and Systems Biology, University of California, La Jolla, San Diego, CA, USA. sarifkin@ucsd.edu.', 'United States|United States', 6, 'Algorithms|Animals|Artificial Intelligence|Caenorhabditis elegans|Computational Biology|Embryo, Nonmammalian|Fluorescence|Fluorescent Dyes|Image Processing, Computer-Assisted|In Situ Hybridization, Fluorescence|Microscopy, Fluorescence|Nanotechnology|RNA, Messenger|Software|Staining and Labeling', 'Journal Article', '10.1186/s12859-015-0534-z', '25880543', 'Recent techniques for tagging and visualizing single molecules in fixed or living organisms and cell lines have been revolutionizing our understanding of the spatial and temporal dynamics of fundamental biological processes. However, fluorescence microscopy images are often noisy, and it can be difficult to distinguish a fluorescently labeled single molecule from background speckle.'),
(96601, 2015, 'bmc', 'Essentiality and centrality in protein interaction networks revisited', 'Khuri, Sawsan|Wuchty, Stefan', 'Department of Computer Science, University of Miami, Coral Gables, FL, 33146, USA. skhuri@med.miami.edu.|Department of Computer Science, University of Miami, Coral Gables, FL, 33146, USA. wuchtys@cs.miami.edu.', 'United States|United States', 27, 'Computational Biology|Databases, Protein|Escherichia coli Proteins|Gene Expression Regulation|Genes, Essential|Humans|Protein Interaction Maps|Proteins|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/s12859-015-0536-x', '25880655', 'Minimum dominating sets (MDSet) of protein interaction networks allow the control of underlying protein interaction networks through their topological placement. While essential proteins are enriched in MDSets, we hypothesize that the statistical properties of biological functions of essential genes are enhanced when we focus on essential MDSet proteins (e-MDSet).'),
(96602, 2015, 'bmc', 'A strategy to build and validate a prognostic biomarker model based on RT-qPCR gene expression and clinical covariates', 'Tournoud, Maud|Larue, Audrey|Cazalis, Marie-Angelique|Venet, Fabienne|Pachot, Alexandre|Monneret, Guillaume|Lepape, Alain|Veyrieras, Jean-Baptiste', 'Bioinformatics Research Department, bioMérieux, Marcy LEtoile, France. maud.tournoud@biomerieux.com.|Bioinformatics Research Department, bioMérieux, Marcy LEtoile, France. audrey.larue-triolet@biomerieux.com.|Medical Diagnostic Discovery Department, bioMérieux, Marcy LEtoile, France. marie-angelique.cazalis@biomerieux.com.|Laboratoire Commun de Recherche, Hospices Civils de Lyon, Lyon, France. fabienne.venet@chu-lyon.fr.|Medical Diagnostic Discovery Department, bioMérieux, Marcy LEtoile, France. alexandre.pachot@biomerieux.com.|Laboratoire Commun de Recherche, Hospices Civils de Lyon, Lyon, France. guillaume.monneret@chu-lyon.fr.|Laboratoire Commun de Recherche, Hospices Civils de Lyon, Lyon, France. alain.lepape@chu-lyon.fr.|Bioinformatics Research Department, bioMérieux, Marcy LEtoile, France. jean-baptiste.veyrieras@biomerieux.com.', 'France|France|France|France|France|France|France|France', 3, 'Biomarkers|Gene Expression|Humans|Prognosis|Proportional Hazards Models|Real-Time Polymerase Chain Reaction|Reverse Transcriptase Polymerase Chain Reaction|Shock, Septic', 'Journal Article', '10.1186/s12859-015-0537-9', '25880752', 'Construction and validation of a prognostic model for survival data in the clinical domain is still an active field of research. Nevertheless there is no consensus on how to develop routine prognostic tests based on a combination of RT-qPCR biomarkers and clinical or demographic variables. In particular, the estimation of the model performance requires to properly account for the RT-qPCR experimental design.'),
(96603, 2015, 'bmc', 'Differential co-expression and regulation analyses reveal different mechanisms underlying major depressive disorder and subsyndromal symptomatic depression', 'Xu, Fan|Yang, Jing|Chen, Jin|Wu, Qingyuan|Gong, Wei|Zhang, Jianguo|Shao, Weihua|Mu, Jun|Yang, Deyu|Yang, Yongtao|Li, Zhiwei|Xie, Peng', 'Department of Neurology, Yongchuan Hospital, Chongqing Medical University, Chongqing, China. frank_cqmu@126.com.|School of Biotechnology, East China University of Science and Technology, Shanghai, China. liuk8628@163.com.|Department of Neurology, the First Affiliated Hospital, Chongqing Medical University, No. 1 Youyi Road, Chongqing, 400016, China. 570572292@qq.com.|Department of Neurology, the First Affiliated Hospital, Chongqing Medical University, No. 1 Youyi Road, Chongqing, 400016, China. zxn020@163.com.|Department of Neurology, Yongchuan Hospital, Chongqing Medical University, Chongqing, China. czs027@163.com.|Department of Neurology, Yongchuan Hospital, Chongqing Medical University, Chongqing, China. dyjianguo@163.com.|Department of Neurology, the First Affiliated Hospital, Chongqing Medical University, No. 1 Youyi Road, Chongqing, 400016, China. tyl0871@163.com.|Department of Neurology, the First Affiliated Hospital, Chongqing Medical University, No. 1 Youyi Road, Chongqing, 400016, China. ylx8623@163.com.|Department of Neurology, Yongchuan Hospital, Chongqing Medical University, Chongqing, China. bjj0550@163.com.|Institute of Neuroscience, Chongqing Medical University, and Chongqing Key Laboratory of Neurobiology, Chongqing, China. fzx023@163.com.|Department of Neurology, Yongchuan Hospital, Chongqing Medical University, Chongqing, China. zhiwei_li023@163.com.|Department of Neurology, Yongchuan Hospital, Chongqing Medical University, Chongqing, China. xiepeng@cqmu.edu.cn.', 'China|China|China|China|China|China|China|China|China|China|China|China', 12, 'Adolescent|Adult|Antidepressive Agents, Second-Generation|Biomarkers|Case-Control Studies|Cyclohexanols|Depression|Depressive Disorder, Major|Female|Gene Regulatory Networks|Humans|Leukocytes, Mononuclear|Male|Microarray Analysis|Venlafaxine Hydrochloride', 'Comparative Study', '10.1186/s12859-015-0543-y', '25880836', 'Recent depression research has revealed a growing awareness of how to best classify depression into depressive subtypes. Appropriately subtyping depression can lead to identification of subtypes that are more responsive to current pharmacological treatment and aid in separating out depressed patients in which current antidepressants are not particularly effective. Differential co-expression analysis (DCEA) and differential regulation analysis (DRA) were applied to compare the transcriptomic profiles of peripheral blood lymphocytes from patients with two depressive subtypes: major depressive disorder (MDD) and subsyndromal symptomatic depression (SSD).'),
(96604, 2015, 'bmc', 'REGULATOR: a database of metazoan transcription factors and maternal factors for developmental studies', 'Wang, Kai|Nishida, Hiroki', 'Department of Biological Sciences, Graduate School of Science, Osaka University, Toyonaka, Osaka, 560-0043, Japan. wangk@bio.sci.osaka-u.ac.jp.|Department of Biological Sciences, Graduate School of Science, Osaka University, Toyonaka, Osaka, 560-0043, Japan. hnishida@bio.sci.osaka-u.ac.jp.', 'Japan|Japan', 6, 'Animals|Databases, Factual|Gene Expression Regulation, Developmental|Gene Regulatory Networks|Humans|Mice|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1186/s12859-015-0552-x', '25880930', 'Genes encoding transcription factors that constitute gene-regulatory networks and maternal factors accumulating in egg cytoplasm are two classes of essential genes that play crucial roles in developmental processes. Transcription factors control the expression of their downstream target genes by interacting with cis-regulatory elements. Maternal factors initiate embryonic developmental programs by regulating the expression of zygotic genes and various other events during early embryogenesis.'),
(96605, 2015, 'bmc', 'Discovery of prognostic biomarkers for predicting lung cancer metastasis using microarray and survival data', 'Huang, Hui-Ling|Wu, Yu-Chung|Su, Li-Jen|Huang, Yun-Ju|Charoenkwan, Phasit|Chen, Wen-Liang|Lee, Hua-Chin|Chu, William Cheng-Chung|Ho, Shinn-Ying', 'Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan. hlhuang@mail.nctu.edu.tw.|Division of Thoracic Surgery, Department of Surgery, Taipei Veterans General Hospital, Taipei, Taiwan. wuyc@vghtpe.gov.tw.|Institute of Systems Biology and Bioinformatics, National Central University, Taoyuan, Taiwan. sulijen@ncu.edu.tw.|Institute of Molecular Medicine and Bioengineering, National Chiao Tung University, Hsinchu, Taiwan. woodstock_ivy@hotmail.com.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan. phaznexus@hotmail.com.|Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan. wenurea@yahoo.com.tw.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan. huachinlee@g2.nctu.edu.tw.|Department of Computer Science, Tunghai University, Taichung, Taiwan. cchu@thu.edu.tw.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan. syho@mail.nctu.edu.tw.', '-|-|-|-|-|-|-|-|-', 16, 'Adenocarcinoma|Aged|Biomarkers, Tumor|Carcinoma, Large Cell|Carcinoma, Squamous Cell|Epithelial-Mesenchymal Transition|Female|Follow-Up Studies|Humans|Lung Neoplasms|Male|Microarray Analysis|Neoplasm Staging|Prognosis|Prospective Studies|Signal Transduction|Survival Rate', 'Journal Article', '10.1186/s12859-015-0463-x', '25881029', 'Few studies have investigated prognostic biomarkers of distant metastases of lung cancer. One of the central difficulties in identifying biomarkers from microarray data is the availability of only a small number of samples, which results overtraining. Recently obtained evidence reveals that epithelial-mesenchymal transition (EMT) of tumor cells causes metastasis, which is detrimental to patients survival.'),
(96606, 2015, 'bmc', 'Comparing variant calling algorithms for target-exon sequencing in a large sample', 'Lo, Yancy|Kang, Hyun M|Nelson, Matthew R|Othman, Mohammad I|Chissoe, Stephanie L|Ehm, Margaret G|Abecasis, Gonçalo R|Zöllner, Sebastian', 'Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA. yancylo@umich.edu.|Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA. hmkang@umich.edu.|GlaxoSmithKline, Quantitative Sciences, Research Triangle Park, NC, USA. matthew.r.nelson@gsk.com.|Department of Ophthalmology, University of Michigan, Ann Arbor, MI, USA. miothman@med.umich.edu.|GlaxoSmithKline, Quantitative Sciences, Research Triangle Park, NC, USA. stephanie.l.chissoe@gsk.com.|GlaxoSmithKline, Quantitative Sciences, Research Triangle Park, NC, USA. meg.g.ehm@gsk.com.|Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA. goncalo@umich.edu.|Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA. szoellne@umich.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States', 2, 'Algorithms|Biomarkers|Disease|Exons|Genetics, Population|Genome, Human|Genotype|Haplotypes|High-Throughput Nucleotide Sequencing|Humans|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Software', 'Comparative Study', '10.1186/s12859-015-0489-0', '25884587', 'Sequencing studies of exonic regions aim to identify rare variants contributing to complex traits. With high coverage and large sample size, these studies tend to apply simple variant calling algorithms. However, coverage is often heterogeneous, sites with insufficient coverage may benefit from sophisticated calling algorithms used in low-coverage sequencing studies. We evaluate the potential benefits of different calling strategies by performing a comparative analysis of variant calling methods on exonic data from 202 genes sequenced at 24x in 7,842 individuals. We call variants using individual-based, population-based and linkage disequilibrium (LD)-aware methods with stringent quality control. We measure genotype accuracy by the concordance with on-target GWAS genotypes and between 80 pairs of sequencing replicates. We validate selected singleton variants using capillary sequencing.'),
(96607, 2015, 'bmc', 'histoneHMM: Differential analysis of histone modifications with broad genomic footprints', 'Heinig, Matthias|Colomé-Tatché, Maria|Taudt, Aaron|Rintisch, Carola|Schafer, Sebastian|Pravenec, Michal|Hubner, Norbert|Vingron, Martin|Johannes, Frank', 'Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnesstrasse 63-73, Berlin, 14195, Germany. heinig@molgen.mpg.de.|Quantitative Epigenetics, European Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, A. Deusinglaan 1, AV, Groningen, 9713, The Netherlands. m.colome.tatche@umcg.nl.|Quantitative Epigenetics, European Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, A. Deusinglaan 1, AV, Groningen, 9713, The Netherlands. a.s.taudt@umcg.nl.|Experimental Genetics Group, Max-Delbrück-Center for Molecular Medicine, Robert-Rössle-Strasse 10, 13092Berlin, Germany. carola.rintisch@mdc-berlin.de.|Experimental Genetics Group, Max-Delbrück-Center for Molecular Medicine, Robert-Rössle-Strasse 10, 13092Berlin, Germany. sebastian.schaefer@mdc-berlin.de.|Institute of Physiology, Academy of Sciences of the Czeck Republic, Videnska 1083, Prague, 14220, Czech Republic. pravenec@biomed.cas.cz.|Experimental Genetics Group, Max-Delbrück-Center for Molecular Medicine, Robert-Rössle-Strasse 10, 13092Berlin, Germany. nhuebner@mdc-berlin.de.|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnesstrasse 63-73, Berlin, 14195, Germany. vingron@molgen.mpg.de.|Groningen Bioinformatics Center, University of Groningen, Nijenborgh 7, AG, Groningen, 9747, The Netherlands. frank@johanneslab.org.', 'Germany|Netherlands|Netherlands|Germany|Germany|-|Germany|Germany|Netherlands', 10, 'Algorithms|Animals|Chromatin Immunoprecipitation|Computational Biology|Female|Genomics|High-Throughput Nucleotide Sequencing|Histones|Humans|Male|Markov Chains|Mice|Protein Processing, Post-Translational|Rats|Real-Time Polymerase Chain Reaction|Software', 'Journal Article', '10.1186/s12859-015-0491-6', '25884684', 'ChIP-seq has become a routine method for interrogating the genome-wide distribution of various histone modifications. An important experimental goal is to compare the ChIP-seq profiles between an experimental sample and a reference sample, and to identify regions that show differential enrichment. However, comparative analysis of samples remains challenging for histone modifications with broad domains, such as heterochromatin-associated H3K27me3, as most ChIP-seq algorithms are designed to detect well defined peak-like features.'),
(96608, 2015, 'bmc', 'A model of the regulatory network involved in the control of the cell cycle and cell differentiation in the Caenorhabditis elegans vulva', 'Weinstein, Nathan|Ortiz-Gutiérrez, Elizabeth|Muñoz, Stalin|Rosenblueth, David A|Álvarez-Buylla, Elena R|Mendoza, Luis', 'Programa de Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de, México, DF, México. nathan.weinstein@iibiomedicas.unam.mx.|Programa de Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de, México, DF, México. eortiz@lcg.unam.mx.|Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad, Nacional Autónoma de México, México, DF, México. stalinmunoz@yahoo.com.|Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad, Nacional Autónoma de México, México, DF, México. drosenbl@unam.mx.|Instituto de Ecología, Universidad Nacional Autónoma de México, México, DF, México. eabuylla@gmail.com.|Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, México, DF, México. lmendoza@biomedicas.unam.mx.', '-|-|-|-|-|-', 7, 'Animals|Caenorhabditis elegans|Caenorhabditis elegans Proteins|Cell Cycle|Cell Differentiation|Cell Division|Computer Simulation|Female|Gene Expression Regulation, Developmental|Gene Regulatory Networks|Models, Theoretical|Signal Transduction|Vulva', 'Journal Article', '10.1186/s12859-015-0498-z', '25884811', 'There are recent experimental reports on the cross-regulation between molecules involved in the control of the cell cycle and the differentiation of the vulval precursor cells (VPCs) of Caenorhabditis elegans. Such discoveries provide novel clues on how the molecular mechanisms involved in the cell cycle and cell differentiation processes are coordinated during vulval development. Dynamic computational models are helpful to understand the integrated regulatory mechanisms affecting these cellular processes.'),
(96609, 2015, 'bmc', 'Fully automated pipeline for detection of sex linked genes using RNA-Seq data', 'Michalovova, Monika|Kubat, Zdenek|Hobza, Roman|Vyskot, Boris|Kejnovsky, Eduard', 'Department of Plant Developmental Genetics, Institute of Biophysics, Academy of Sciences of the Czech Republic, Kralovopolska 135, CZ-61200, Brno, Czech Republic. biomonika@psu.edu.|Department of Plant Developmental Genetics, Institute of Biophysics, Academy of Sciences of the Czech Republic, Kralovopolska 135, CZ-61200, Brno, Czech Republic. kubat@ibp.cz.|Department of Plant Developmental Genetics, Institute of Biophysics, Academy of Sciences of the Czech Republic, Kralovopolska 135, CZ-61200, Brno, Czech Republic. hobza@ibp.cz.|Department of Plant Developmental Genetics, Institute of Biophysics, Academy of Sciences of the Czech Republic, Kralovopolska 135, CZ-61200, Brno, Czech Republic. vyskot@ibp.cz.|Department of Plant Developmental Genetics, Institute of Biophysics, Academy of Sciences of the Czech Republic, Kralovopolska 135, CZ-61200, Brno, Czech Republic. kejnovsk@ibp.cz.', '-|-|-|-|-', 8, 'Female|Genes, X-Linked|Genes, Y-Linked|Genetic Markers|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Male|Polymerase Chain Reaction|Polymorphism, Single Nucleotide|RNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/s12859-015-0509-0', '25884927', 'Sex chromosomes present a genomic region which to some extent, differs between the genders of a single species. Reliable high-throughput methods for detection of sex chromosomes specific markers are needed, especially in species where genome information is limited. Next generation sequencing (NGS) opens the door for identification of unique sequences or searching for nucleotide polymorphisms between datasets. A combination of classical genetic segregation analysis along with RNA-Seq data can present an ideal tool to map and identify sex chromosome-specific expressed markers. To address this challenge, we established genetic cross of dioecious plant Rumex acetosa and generated RNA-Seq data from both parental generation and male and female offspring.'),
(96610, 2015, 'bmc', 'Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource', 'Schuette, Scott|Piatkowski, Brian|Corley, Aaron|Lang, Daniel|Geisler, Matt', 'Department of Plant Biology, Southern Illinois University, Carbondale, IL, USA. swschuette@gmail.com.|Department of Plant Biology, Southern Illinois University, Carbondale, IL, USA. btpiatkowski@siu.edu.|Department of Plant Biology, Southern Illinois University, Carbondale, IL, USA. acorley101@gmail.com.|University of Freiburg, Plant Biotechnology Schaenzlestr. 1, D-79104, Freiburg, Germany. daniel.lang@biologie.uni-freiburg.de.|Department of Plant Biology, Southern Illinois University, Carbondale, IL, USA. mgeisler@plant.siu.edu.', 'United States|United States|United States|Germany|United States', 8, 'Animals|Arabidopsis|Bryopsida|Computational Biology|Gene Ontology|Genome, Plant|Humans|Mice|Plant Proteins|Protein Interaction Mapping|Rats', 'Journal Article', '10.1186/s12859-015-0524-1', '25885037', 'Physcomitrella patens, a haploid dominant plant, is fast becoming a useful molecular genetics and bioinformatics tool due to its key phylogenetic position as a bryophyte in the post-genomic era. Genome sequences from select reference species were compared bioinformatically to Physcomitrella patens using reciprocal blasts with the InParanoid software package. A reference protein interaction database assembled using MySQL by compiling BioGrid, BIND, DIP, and Intact databases was queried for moss orthologs existing for both interacting partners. This method has been used to successfully predict interactions for a number of angiosperm plants.'),
(96611, 2015, 'bmc', 'Understanding the molecular basis of EGFR kinase domain/MIG-6 peptide recognition complex using computational analyses', 'Moonrin, Ninnutt|Songtawee, Napat|Rattanabunyong, Siriluk|Chunsrivirot, Surasuk|Mokmak, Wanwimon|Tongsima, Sissades|Choowongkomon, Kiattawee', 'Department of Biochemistry, Faculty of Science, Kasetsart University, 50 Ngam, Wong Wan Rd, Bangkok, Chatuchak, 10900, Thailand. moonrin_jear@hotmail.com.|Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700, Thailand. napat.son@mahidol.ac.th.|Department of Biochemistry, Faculty of Science, Kasetsart University, 50 Ngam, Wong Wan Rd, Bangkok, Chatuchak, 10900, Thailand. fscislra@ku.ac.th.|Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok, Pathum Wan, 10330, Thailand. surasak.ch@chula.ac.th.|Genetic Engineering Interdisciplinary Program, Graduate School, Kasetsart University, 50 Ngam Wong Wan Rd, Bangkok, Chatuchak, 10900, Thailand. wanwimon.mok@biotec.or.th.|Genome Technology Research Unit, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency (NSTDA), 113 Thailand Science Park, Phahonyothin Road, Khlong Nueng, Pathum Thani, Khlong Luang, 12120, Thailand. sissades@biotec.or.th.|Department of Biochemistry, Faculty of Science, Kasetsart University, 50 Ngam, Wong Wan Rd, Bangkok, Chatuchak, 10900, Thailand. fsciktc@ku.ac.th.', 'Thailand|Thailand|Thailand|Thailand|Thailand|Thailand|Thailand', 11, 'Adaptor Proteins, Signal Transducing|Computational Biology|ErbB Receptors|Humans|Hydrogen Bonding|Molecular Dynamics Simulation|Mutagenesis|Peptides|Protein Binding|Protein Structure, Tertiary|Tumor Suppressor Proteins', 'Journal Article', '10.1186/s12859-015-0528-x', '25885222', 'Epidermal growth factor receptor (EGFR) signalling plays a major role in biological processes, including cell proliferation, differentiation and survival. Since the over-expression of EGFR causes human cancers, EGFR is an attractive drug target. A tumor suppressor endogenous protein, MIG-6, is known to suppress EGFR over-expression by binding to the C-lobe of EGFR kinase. Thus, this C-lobe of the EGFR kinase is a potential new target for EGFR kinase activity inhibition. In this study, molecular dynamics (MD) simulations and binding free energy calculations were used to investigate the protein-peptide interactions between EGFR kinase and a 27-residue peptide derived from MIG-6_s1 segment (residues 336-362).');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96612, 2015, 'bmc', 'YOC, A new strategy for pairwise alignment of collinear genomes', 'Uricaru, Raluca|Michotey, Célia|Chiapello, Hélène|Rivals, Eric', 'University of Bordeaux, CNRS / LaBRI, F-33405, Talence, France. ruricaru@labri.fr.|MIG, UR 1077, INRA, 78026, Jouy-en-Josas cedex, France. celia.michotey@versailles.inra.fr.|MIG, UR 1077, INRA, 78026, Jouy-en-Josas cedex, France. helene.chiapello@toulouse.inra.fr.|LIRMM, UMR 5506, Computational Biology Institute, CNRS, University of Montpellier 2, Montpellier, France. rivals@lirmm.fr.', 'France|France|France|France', 7, 'Algorithms|Comparative Genomic Hybridization|Genome, Bacterial|Internet|Lactococcus lactis|Sequence Alignment|User-Computer Interface', 'Journal Article', '10.1186/s12859-015-0530-3', '25885358', 'Comparing and aligning genomes is a key step in analyzing closely related genomes. Despite the development of many genome aligners in the last 15 years, the problem is not yet fully resolved, even when aligning closely related bacterial genomes of the same species. In addition, no procedures are available to assess the quality of genome alignments or to compare genome aligners.'),
(96613, 2015, 'bmc', 'ProteinVolume: calculating molecular van der Waals and void volumes in proteins', 'Chen, Calvin R|Makhatadze, George I', 'Department of Biological Sciences and Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY, 12180, USA. chenc13@rpi.edu.|Department of Biological Sciences and Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY, 12180, USA. makhag@rpi.edu.', 'United States|United States', 21, 'Algorithms|Models, Molecular|Proteins|Software', 'Journal Article', '10.1186/s12859-015-0531-2', '25885484', 'Voids and cavities in the native protein structure determine the pressure unfolding of proteins. In addition, the volume changes due to the interaction of newly exposed atoms with solvent upon protein unfolding also contribute to the pressure unfolding of proteins. Quantitative understanding of these effects is important for predicting and designing proteins with predefined response to changes in hydrostatic pressure using computational approaches. The molecular surface volume is a useful metric that describes contribution of geometrical volume, which includes van der Waals volume and volume of the voids, to the total volume of a protein in solution, thus isolating the effects of hydration for separate calculations.'),
(96614, 2015, 'bmc', 'FlowClus: efficiently filtering and denoising pyrosequenced amplicons', 'Gaspar, John M|Thomas, W Kelley', 'Department of Molecular Cellular & Biomedical Sciences, University of New Hampshire, Durham, NH, USA. jsh58@unh.edu.|Department of Molecular Cellular & Biomedical Sciences, University of New Hampshire, Durham, NH, USA. kelley.thomas@unh.edu.', 'United States|United States', 17, 'Algorithms|Metagenomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-015-0532-1', '25885646', 'Reducing the effects of sequencing errors and PCR artifacts has emerged as an essential component in amplicon-based metagenomic studies. Denoising algorithms have been designed that can reduce error rates in mock community data, but they change the sequence data in a manner that can be inconsistent with the process of removing errors in studies of real communities. In addition, they are limited by the size of the dataset and the sequencing technology used.'),
(96615, 2015, 'bmc', 'MAESTRO--multi agent stability prediction upon point mutations', 'Laimer, Josef|Hofer, Heidi|Fritz, Marko|Wegenkittl, Stefan|Lackner, Peter', 'Department of Molecular Biology, University of Salzburg, Hellbrunnerstr, Salzburg, 34, 5020, Austria. josef.laimer@stud.sbg.ac.at.|Department of Molecular Biology, University of Salzburg, Hellbrunnerstr, Salzburg, 34, 5020, Austria. heidi.hofer@stud.sbg.ac.at.|University of Applied Sciences Upper Austria, School of Informatics, Communications and Media, Softwarepark 11, Hagenberg, 4232, Austria. s1410595002@students.fh-hagenberg.at.|Salzburg University of Applied Sciences, Urstein Sxc3xbcd 1, Puch, 5412, Austria. stefan.wegenkittl@fh-salzburg.ac.at.|Department of Molecular Biology, University of Salzburg, Hellbrunnerstr, Salzburg, 34, 5020, Austria. peter.lackner@sbg.ac.at.', 'Austria|Austria|Austria|Austria|Austria', 0, 'Disulfides|Internet|Point Mutation|Protein Stability|Proteins|User-Computer Interface', 'Journal Article', '10.1186/s12859-015-0548-6', '25885774', 'Point mutations can have a strong impact on protein stability. A change in stability may subsequently lead to dysfunction and finally cause diseases. Moreover, protein engineering approaches aim to deliberately modify protein properties, where stability is a major constraint. In order to support basic research and protein design tasks, several computational tools for predicting the change in stability upon mutations have been developed. Comparative studies have shown the usefulness but also limitations of such programs.'),
(96616, 2015, 'bmc', 'EGFR Mutant Structural Database: computationally predicted 3D structures and the corresponding binding free energies with gefitinib and erlotinib', 'Ma, Lichun|Wang, Debby D|Huang, Yiqing|Yan, Hong|Wong, Maria P|Lee, Victor H F', 'Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong. lichunma2-c@my.cityu.edu.hk.|Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong. danwang6-c@my.cityu.edu.hk.|School of Computer Science and Technology, Soochow University, Suzhou, China. 149145459@qq.com.|Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong. h.yan@cityu.edu.hk.|Li Ka Sing Faculty of Medicne, University of Hong Kong, Pokfulam, Hong Kong. mwpik@hku.hk.|Li Ka Sing Faculty of Medicne, University of Hong Kong, Pokfulam, Hong Kong. vhflee@hku.hk.', 'Hong Kong|Hong Kong|China|Hong Kong|Hong Kong|Hong Kong', 21, 'Antineoplastic Agents|Carcinoma, Non-Small-Cell Lung|Databases, Protein|ErbB Receptors|Erlotinib Hydrochloride|Exons|Gefitinib|Humans|Lung Neoplasms|Molecular Dynamics Simulation|Mutation|Protein Binding|Protein Conformation|Protein Kinase Inhibitors|Quinazolines', 'Journal Article', '10.1186/s12859-015-0522-3', '25886721', 'Epidermal growth factor receptor (EGFR) mutation-induced drug resistance has caused great difficulties in the treatment of non-small-cell lung cancer (NSCLC). However, structural information is available for just a few EGFR mutants. In this study, we created an EGFR Mutant Structural Database (freely available at http://bcc.ee.cityu.edu.hk/data/EGFR.html ), including the 3D EGFR mutant structures and their corresponding binding free energies with two commonly used inhibitors (gefitinib and erlotinib).'),
(96617, 2015, 'bmc', 'Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research', 'Bravo, Àlex|Piñero, Janet|Queralt-Rosinach, Núria|Rautschka, Michael|Furlong, Laura I', 'Research Programme on Biomedical Informatics (GRIB), IMIM, DCEXS, Universitat Pompeu Fabra, Barcelona, Spain. abravo@imim.es.|Research Programme on Biomedical Informatics (GRIB), IMIM, DCEXS, Universitat Pompeu Fabra, Barcelona, Spain. jpinero@imim.es.|Research Programme on Biomedical Informatics (GRIB), IMIM, DCEXS, Universitat Pompeu Fabra, Barcelona, Spain. nqueralt@imim.es.|Research Programme on Biomedical Informatics (GRIB), IMIM, DCEXS, Universitat Pompeu Fabra, Barcelona, Spain. rautschy@gmail.com.|Research Programme on Biomedical Informatics (GRIB), IMIM, DCEXS, Universitat Pompeu Fabra, Barcelona, Spain. lfurlong@imim.es.', 'Spain|Spain|Spain|Spain|Spain', 57, 'Data Mining|Databases, Factual|Depression|Disease|Humans|Information Storage and Retrieval|Knowledge Bases|MEDLINE|Publications|Translational Medical Research', 'Journal Article', '10.1186/s12859-015-0472-9', '25886734', 'Current biomedical research needs to leverage and exploit the large amount of information reported in scientific publications. Automated text mining approaches, in particular those aimed at finding relationships between entities, are key for identification of actionable knowledge from free text repositories. We present the BeFree system aimed at identifying relationships between biomedical entities with a special focus on genes and their associated diseases.'),
(96618, 2015, 'bmc', 'A unified framework for estimating parameters of kinetic biological models', 'Baker, Syed Murtuza|Poskar, C Hart|Schreiber, Falk|Junker, Björn H', 'Manchester Institute of Biotechnology, University of Manchester, Manchester, UK. syed.murtuzabaker@manchester.ac.uk.|Systems Biology Group, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany. poskar@ipk-gatersleben.de.|Clayton School of Information Technology, Monash University, Clayton, VIC, Australia. Falk.Schreiber@monash.edu.|Systems Biology Group, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany. boernhard@gmail.com.', 'United Kingdom|Germany|Australia|Germany', 11, 'Algorithms|Gene Regulatory Networks|Kinetics|Models, Biological|Models, Statistical|Plant Proteins|Plant Stems|Saccharum|Sucrose', 'Journal Article', '10.1186/s12859-015-0500-9', '25886743', 'Utilizing kinetic models of biological systems commonly require computational approaches to estimate parameters, posing a variety of challenges due to their highly non-linear and dynamic nature, which is further complicated by the issue of non-identifiability. We propose a novel parameter estimation framework by combining approaches for solving identifiability with a recently introduced filtering technique that can uniquely estimate parameters where conventional methods fail. This framework first conducts a thorough analysis to identify and classify the non-identifiable parameters and provides a guideline for solving them. If no feasible solution can be found, the framework instead initializes the filtering technique with informed prior to yield a unique solution.'),
(96619, 2015, 'bmc', 'SCNVSim: somatic copy number variation and structure variation simulator', 'Qin, Maochun|Liu, Biao|Conroy, Jeffrey M|Morrison, Carl D|Hu, Qiang|Cheng, Yubo|Murakami, Mitsuko|Odunsi, Adekunle O|Johnson, Candace S|Wei, Lei|Liu, Song|Wang, Jianmin', 'Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA. Maochun.Qin@RoswellPark.org.|Center for Personalized Medicine, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA. Biao.Liu@RoswellPark.org.|Center for Personalized Medicine, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA. Jeffrey.Conroy@RoswellPark.org.|Center for Personalized Medicine, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA. Carl.Morrison@RoswellPark.org.|Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA. Qiang.Hu@RoswellPark.org.|Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA. Yubo.Cheng@RoswellPark.org.|Center for Personalized Medicine, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA. Mitsuko.Korobkin@RoswellPark.org.|Department of Gynecologic Oncology, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA. Kunle.Odunsi@RoswellPark.org.|Department of Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA. Candace.Johnson@RoswellPark.org.|Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA. Lei.Wei@RoswellPark.org.|Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA. Song.Liu@RoswellPark.org.|Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA. Jianmin.Wang@RoswellPark.org.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 16, 'Aneuploidy|Computer Simulation|DNA Copy Number Variations|Genome, Human|Genomics|Germ Cells|Heterozygote|High-Throughput Nucleotide Sequencing|Humans|Loss of Heterozygosity|Neoplasms|Sequence Analysis, DNA', 'Journal Article', '10.1186/s12859-015-0502-7', '25886838', 'Somatically acquired structure variations (SVs) and copy number variations (CNVs) can induce genetic changes that are directly related to tumor genesis. Somatic SV/CNV detection using next-generation sequencing (NGS) data still faces major challenges introduced by tumor sample characteristics, such as ploidy, heterogeneity, and purity. A simulated cancer genome with known SVs and CNVs can serve as a benchmark for evaluating the performance of existing somatic SV/CNV detection tools and developing new methods.'),
(96620, 2015, 'bmc', 'The application of sparse estimation of covariance matrix to quadratic discriminant analysis', 'Sun, Jiehuan|Zhao, Hongyu', 'Department of Biostatitics, Yale School of Publich Health, 60 College Street, New Haven, 06511, CT, USA. jiehuan.sun@yale.edu.|Department of Biostatitics, Yale School of Publich Health, 60 College Street, New Haven, 06511, CT, USA. hongyu.zhao@yale.edu.', 'United States|United States', 0, 'Algorithms|Case-Control Studies|Computer Simulation|Discriminant Analysis|Gene Expression Profiling|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Journal Article', '10.1186/s12859-014-0443-6', '25886892', 'Although Linear Discriminant Analysis (LDA) is commonly used for classification, it may not be directly applied in genomics studies due to the large p, small n problem in these studies. Different versions of sparse LDA have been proposed to address this significant challenge. One implicit assumption of various LDA-based methods is that the covariance matrices are the same across different classes. However, rewiring of genetic networks (therefore different covariance matrices) across different diseases has been observed in many genomics studies, which suggests that LDA and its variations may be suboptimal for disease classifications. However, it is not clear whether considering differing genetic networks across diseases can improve classification in genomics studies.'),
(96621, 2015, 'bmc', 'SimBA: simulation algorithm to fit extant-population distributions', 'Parida, Laxmi|Haiminen, Niina', 'Computational Biology Center, IBM T. J. Watson Research, Yorktown Heights, NY, USA. parida@us.ibm.com.|Computational Biology Center, IBM T. J. Watson Research, Yorktown Heights, NY, USA. nshaimin@us.ibm.com.', 'United States|United States', 3, 'Algorithms|Computer Simulation|Conservation of Natural Resources|Gene Frequency|Genetics, Population|Humans|Linkage Disequilibrium|Models, Theoretical|Population Dynamics', 'Journal Article', '10.1186/s12859-015-0525-0', '25886895', 'Simulation of populations with specified characteristics such as allele frequencies, linkage disequilibrium etc., is an integral component of many studies, including in-silico breeding optimization. Since the accuracy and sensitivity of population simulation is critical to the quality of the output of the applications that use them, accurate algorithms are required to provide a strong foundation to the methods in these studies.'),
(96622, 2015, 'bmc', 'Measuring semantic similarities by combining gene ontology annotations and gene co-function networks', 'Peng, Jiajie|Uygun, Sahra|Kim, Taehyong|Wang, Yadong|Rhee, Seung Y|Chen, Jin', 'School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. jiajiepeng@hit.edu.cn.|Department of Energy Plant Research Laboratory, Michigan State University, East Lansing, MI, 48824, USA. uygunsah@msu.edu.|Department of Plant Biology, Carnegie Institution for Science, 260 Panama St, Stanford, CA, 94305, USA. thkim04@gmail.com.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. ydwang@hit.edu.cn.|Department of Plant Biology, Carnegie Institution for Science, 260 Panama St, Stanford, CA, 94305, USA. srhee@carnegiescience.edu.|Department of Energy Plant Research Laboratory, Michigan State University, East Lansing, MI, 48824, USA. jinchen@msu.edu.', 'China|United States|Panama|China|Panama|United States', 34, 'Algorithms|Arabidopsis Proteins|Computational Biology|Cytochrome P-450 Enzyme System|Gene Ontology|Gene Regulatory Networks|Humans|Metabolic Networks and Pathways|Molecular Sequence Annotation|Multigene Family|Saccharomyces cerevisiae Proteins|Semantics|Software|Vocabulary, Controlled', 'Journal Article', '10.1186/s12859-015-0474-7', '25886899', 'Gene Ontology (GO) has been used widely to study functional relationships between genes. The current semantic similarity measures rely only on GO annotations and GO structure. This limits the power of GO-based similarity because of the limited proportion of genes that are annotated to GO in most organisms.'),
(96623, 2015, 'bmc', 'RIEMS: a software pipeline for sensitive and comprehensive taxonomic classification of reads from metagenomics datasets', 'Scheuch, Matthias|Höper, Dirk|Beer, Martin', 'Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald - Insel Riems, Germany. matthias_scheuch@yahoo.de.|Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald - Insel Riems, Germany. dirk.hoeper@fli.bund.de.|Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald - Insel Riems, Germany. martin.beer@fli.bund.de.', 'Germany|Germany|Germany', 0, 'Algorithms|Bacteria|Classification|Computational Biology|Datasets as Topic|High-Throughput Nucleotide Sequencing|Metagenomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-015-0503-6', '25886935', 'Fuelled by the advent and subsequent development of next generation sequencing technologies, metagenomics became a powerful tool for the analysis of microbial communities both scientifically and diagnostically. The biggest challenge is the extraction of relevant information from the huge sequence datasets generated for metagenomics studies. Although a plethora of tools are available, data analysis is still a bottleneck.'),
(96624, 2015, 'bmc', 'Sigma-RF: prediction of the variability of spatial restraints in template-based modeling by random forest', 'Lee, Juyong|Lee, Kiho|Joung, InSuk|Joo, Keehyoung|Brooks, Bernard R|Lee, Jooyoung', 'Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, 5635 Fishers Ln, Bethesda, 20852, USA. juyong.lee@nih.gov.|Center for In Silico Protein Science, Korea Institute for Advanced Study, Seoul, Korea. kiholee@kias.re.kr.|Center for In Silico Protein Science, Korea Institute for Advanced Study, Seoul, Korea. isjoung@kias.re.kr.|Center for In Silico Protein Science, Korea Institute for Advanced Study, Seoul, Korea. newton@kias.re.kr.|Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, 5635 Fishers Ln, Bethesda, 20852, USA. brb@nih.gov.|Center for In Silico Protein Science, Korea Institute for Advanced Study, Seoul, Korea. jlee@kias.re.kr.', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Models, Molecular|Models, Statistical|Sequence Alignment|Structural Homology, Protein', 'Journal Article', '10.1186/s12859-015-0526-z', '25886990', 'In template-based modeling when using a single template, inter-atomic distances of an unknown protein structure are assumed to be distributed by Gaussian probability density functions, whose center peaks are located at the distances between corresponding atoms in the template structure. The width of the Gaussian distribution, the variability of a spatial restraint, is closely related to the reliability of the restraint information extracted from a template, and it should be accurately estimated for successful template-based protein structure modeling.'),
(96625, 2015, 'bmc', 'Pheno2Geno - High-throughput generation of genetic markers and maps from molecular phenotypes for crosses between inbred strains', 'Zych, Konrad|Li, Yang|van der Velde, Joeri K|Joosen, Ronny V L|Ligterink, Wilco|Jansen, Ritsert C|Arends, Danny', 'University of Groningen, Groningen Bioinformatics Centre, Nijenborgh 7, Groningen, 9747, AG, The Netherlands. konradzych2@gmail.com.|University of Groningen, Groningen Bioinformatics Centre, Nijenborgh 7, Groningen, 9747, AG, The Netherlands. yang.li@rug.nl.|University of Groningen, University Medical Center Groningen, Genomics Coordination Center, PO Box 30001, Groningen, 9700, RB, The Netherlands. k.j.van.der.velde@umcg.nl.|Wageningen University, Wageningen Seed Lab, Droevendaalsesteeg 1, Wageningen, The Netherlands. rvl.joosen@gmail.com.|Wageningen University, Wageningen Seed Lab, Droevendaalsesteeg 1, Wageningen, The Netherlands. wilco.ligterink@wur.nl.|University of Groningen, Groningen Bioinformatics Centre, Nijenborgh 7, Groningen, 9747, AG, The Netherlands. r.c.jansen@rug.nl.|University of Groningen, Groningen Bioinformatics Centre, Nijenborgh 7, Groningen, 9747, AG, The Netherlands. danny.arends@gmail.com.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Arabidopsis|Chromosome Mapping|Crosses, Genetic|DNA, Plant|Genetic Linkage|Genetic Markers|Genome, Plant|Phenotype|Quantitative Trait Loci', 'Journal Article', '10.1186/s12859-015-0475-6', '25886992', 'Genetic markers and maps are instrumental in quantitative trait locus (QTL) mapping in segregating populations. The resolution of QTL localization depends on the number of informative recombinations in the population and how well they are tagged by markers. Larger populations and denser marker maps are better for detecting and locating QTLs. Marker maps that are initially too sparse can be saturated or derived de novo from high-throughput omics data, (e.g. gene expression, protein or metabolite abundance). If these molecular phenotypes are affected by genetic variation due to a major QTL they will show a clear multimodal distribution. Using this information, phenotypes can be converted into genetic markers.'),
(96626, 2015, 'bmc', 'Constrained distance transforms for spatial atlas registration', 'Hill, Bill|Baldock, Richard A', 'MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. bill.hill@igmm.ed.ac.uk.|MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh, EH4 2XU, UK. richard.baldock@igmm.ed.ac.uk.', 'United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Databases, Factual|Image Processing, Computer-Assisted|Mice', 'Journal Article', '10.1186/s12859-015-0504-5', '25887037', 'Spatial frameworks are used to capture organ or whole organism image data in biomedical research. The registration of large biomedical volumetric images is a complex and challenging task, but one that is required for spatially mapped biomedical atlas systems. In most biomedical applications the transforms required are non-rigid and may involve significant deformation relating to variation in pose, natural variation and mutation. Here we develop a new technique to establish such transformations for mapping data that cannot be achieved by existing approaches and that can be used interactively for expert editorial review.'),
(96627, 2015, 'bmc', 'Cell-composition effects in the analysis of DNA methylation array data: a mathematical perspective', 'Houseman, E Andres|Kelsey, Karl T|Wiencke, John K|Marsit, Carmen J', 'School of Biological and Population Health Sciences, College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA. andres.houseman@oregonstate.edu.|Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA. karl_kelsey@brown.edu.|Departments of Neurological Surgery, and Division of Epidemiology, University of California San Francisco, San Francisco, CA, USA. John.Wiencke@ucsf.edu.|Department of Community and Family Medicine, Dartmouth Medical School, Hanover, NH, USA. Carmen.J.Marsit@dartmouth.edu.', 'United States|United States|United States|United States', 49, 'Algorithms|DNA Methylation|Epigenesis, Genetic|Epigenomics|Genome-Wide Association Study|Humans|Leukocytes|Oligonucleotide Array Sequence Analysis|Phenotype', 'Journal Article', '10.1186/s12859-015-0527-y', '25887114', 'The impact of cell-composition effects in analysis of DNA methylation data is now widely appreciated. With the availability of a reference data set consisting of DNA methylation measurements on isolated cell types, it is possible to impute cell proportions and adjust for them, but there is increasing interest in methods that adjust for cell composition effects when reference sets are incomplete or unavailable.'),
(96628, 2015, 'bmc', 'Sampling with poling-based flux balance analysis: optimal versus sub-optimal flux space analysis of Actinobacillus succinogenes', 'Binns, Michael|de Atauri, Pedro|Vlysidis, Anestis|Cascante, Marta|Theodoropoulos, Constantinos', 'School of Chemical Engineering and Analytical Science, University of Manchester, Manchester, M13 9PL, UK. mbinns@hanyang.ac.kr.|Department of Biochemistry and Molecular Biology, Faculty of Biology and Institute of Biomedicine (IBUB), University of Barcelona, 08028, Barcelona, Spain. pde_atauri@ub.edu.|School of Chemical Engineering and Analytical Science, University of Manchester, Manchester, M13 9PL, UK. anestis.vlysidis@manchester.ac.uk.|Department of Biochemistry and Molecular Biology, Faculty of Biology and Institute of Biomedicine (IBUB), University of Barcelona, 08028, Barcelona, Spain. martacascante@ub.edu.|School of Chemical Engineering and Analytical Science, University of Manchester, Manchester, M13 9PL, UK. k.theodoropoulos@manchester.ac.uk.', 'United Kingdom|Spain|United Kingdom|Spain|United Kingdom', 6, 'Actinobacillus|Algorithms|Carbon Dioxide|Glycerol|Metabolic Networks and Pathways|Models, Biological|Succinic Acid', 'Journal Article', '10.1186/s12859-015-0476-5', '25887116', 'Flux balance analysis is traditionally implemented to identify the maximum theoretical flux for some specified reaction and a single distribution of flux values for all the reactions present which achieve this maximum value. However it is well known that the uncertainty in reaction networks due to branches, cycles and experimental errors results in a large number of combinations of internal reaction fluxes which can achieve the same optimal flux value.'),
(96629, 2015, 'bmc', 'dbVOR: a database system for importing pedigree, phenotype and genotype data and exporting selected subsets', 'Baron, Robert V|Conley, Yvette P|Gorin, Michael B|Weeks, Daniel E', 'Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, PittsburghPennsylvania, 15261, USA. rvb5@pitt.edu.|Department of Health Promotion and Development, School of Nursing, University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA. yconley@pitt.edu.|Department of Ophthalmology, David Geffen School of Medicine, Stein Eye Institute, University of California Los Angeles, Los Angeles, California, 90095, USA. gorin@jsei.ucla.edu.|Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, PittsburghPennsylvania, 15261, USA. weeks@pitt.edu.', 'United States|United States|United States|United States', 0, 'Databases, Genetic|Female|Genotype|Humans|Male|Pedigree|Phenotype|Software', 'Journal Article', '10.1186/s12859-015-0505-4', '25887129', 'When studying the genetics of a human trait, we typically have to manage both genome-wide and targeted genotype data. There can be overlap of both people and markers from different genotyping experiments, the overlap can introduce several kinds of problems. Most times the overlapping genotypes are the same, but sometimes they are different. Occasionally, the lab will return genotypes using a different allele labeling scheme (for example 1/2 vs A/C). Sometimes, the genotype for a person/marker index is unreliable or missing. Further, over time some markers are merged and bad samples are re-run under a different sample name. We need a consistent picture of the subset of data we have chosen to work with even though there might possibly be conflicting measurements from multiple data sources.'),
(96630, 2015, 'bmc', 'PathwayBooster: a tool to support the curation of metabolic pathways', 'Liberal, Rodrigo|Lisowska, Beata K|Leak, David J|Pinney, John W', 'Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, SW7 2AZ, UK. r.liberal@imperial.ac.uk.|Department of Biology and Biochemistry, University of Bath, Claverton Down, Bath BA2, 7AY, UK. b.k.lisowska@bath.ac.uk.|Department of Biology and Biochemistry, University of Bath, Claverton Down, Bath BA2, 7AY, UK. d.j.leak@bath.ac.uk.|Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, SW7 2AZ, UK. j.pinney@imperial.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 3, 'Cysteine|Databases, Factual|Enzymes|Genome|Metabolic Networks and Pathways|Methionine|Models, Biological|Molecular Sequence Annotation|Software', 'Journal Article', '10.1186/s12859-014-0447-2', '25887214', 'Despite several recent advances in the automated generation of draft metabolic reconstructions, the manual curation of these networks to produce high quality genome-scale metabolic models remains a labour-intensive and challenging task.'),
(96631, 2015, 'bmc', 'Removing batch effects from purified plasma cell gene expression microarrays with modified ComBat', 'Stein, Caleb K|Qu, Pingping|Epstein, Joshua|Buros, Amy|Rosenthal, Adam|Crowley, John|Morgan, Gareth|Barlogie, Bart', 'Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock, AR, USA. CKStein@uams.edu.|Cancer Research and Biostatistics, Seattle, WA, USA. pingping@crab.org.|Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock, AR, USA. EpsteinJoshua@uams.edu.|Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock, AR, USA. AFBuros@uams.edu.|Cancer Research and Biostatistics, Seattle, WA, USA. adamr@crab.org.|Cancer Research and Biostatistics, Seattle, WA, USA. johnc@crab.org.|Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock, AR, USA. GJMorgan@uams.edu.|Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock, AR, USA. BarlogieBart@uams.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States', 27, 'Algorithms|Bone Marrow|Data Interpretation, Statistical|Gene Expression Profiling|Humans|Microarray Analysis|Plasma Cells', 'Journal Article', '10.1186/s12859-015-0478-3', '25887219', 'Gene expression profiling (GEP) via microarray analysis is a widely used tool for assessing risk and other patient diagnostics in clinical settings. However, non-biological factors such as systematic changes in sample preparation, differences in scanners, and other potential batch effects are often unavoidable in long-term studies and meta-analysis. In order to reduce the impact of batch effects on microarray data, Johnson, Rabinovic, and Li developed ComBat for use when combining batches of gene expression microarray data. We propose a modification to ComBat that centers data to the location and scale of a pre-determined, gold-standard batch. This modified ComBat (M-Combat) is designed specifically in the context of meta-analysis and batch effect adjustment for use with predictive models that are validated and fixed on historical data from a gold-standard batch.'),
(96632, 2015, 'bmc', 'Kernel approaches for differential expression analysis of mass spectrometry-based metabolomics data', 'Zhan, Xiang|Patterson, Andrew D|Ghosh, Debashis', 'Department of Statistics, Pennsylvania State University, 325 Thomas Building, University Park, 16802, PA, USA. xyz5074@psu.edu.|Department of Molecular Toxicology, Pennsylvania State University, 322 Life Sciences Bldg, University Park, 16802, PA, USA. adp117@psu.edu.|Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, 13001 East 17th Place, Aurora, 80045, CO, USA. debashis.ghosh@ucdenver.edu.', 'United States|United States|United States', 0, 'Algorithms|Biomarkers, Tumor|Computer Simulation|Databases, Factual|Humans|Liver Neoplasms|Mass Spectrometry|Metabolomics|Software', 'Journal Article', '10.1186/s12859-015-0506-3', '25887233', 'Data generated from metabolomics experiments are different from other types of -omics data. For example, a common phenomenon in mass spectrometry (MS)-based metabolomics data is that the data matrix frequently contains missing values, which complicates some quantitative analyses. One way to tackle this problem is to treat them as absent. Hence there are two types of information that are available in metabolomics data: presence/absence of a metabolite and a quantitative value of the abundance level of a metabolite if it is present. Combining these two layers of information poses challenges to the application of traditional statistical approaches in differential expression analysis.'),
(96633, 2015, 'bmc', 'A hidden Markov approach for ascertaining cSNP genotypes from RNA sequence data in the presence of allelic imbalance by exploiting linkage disequilibrium', 'Steibel, Juan P|Wang, Heng|Zhong, Ping-Shou', 'Department of Animal Science, Michigan State University, East Lansing MI, 48824, USA. steibelj@msu.edu.|Department of Statistics and Probability, Michigan State University, 619 Red Cedar Road, East Lansing MI, 48824, USA. hengwang@stt.msu.edu.|Department of Statistics and Probability, Michigan State University, 619 Red Cedar Road, East Lansing MI, 48824, USA. pszhong@stt.msu.edu.', 'United States|United States|United States', 0, 'Algorithms|Alleles|Allelic Imbalance|Computational Biology|Genotype|High-Throughput Nucleotide Sequencing|Humans|Linkage Disequilibrium|Markov Chains|Polymorphism, Single Nucleotide|RNA|Sequence Analysis, RNA', 'Journal Article', '10.1186/s12859-015-0479-2', '25887316', 'Allelic specific expression (ASE) increases our understanding of the genetic control of gene expression and its links to phenotypic variation. ASE testing is implemented through binomial or beta-binomial tests of sequence read counts of alternative alleles at a cSNP of interest in heterozygous individuals. This requires prior ascertainment of the cSNP genotypes for all individuals. To meet the needs, we propose hidden Markov methods to call SNPs from next generation RNA sequence data when ASE possibly exists.'),
(96634, 2015, 'bmc', 'ITIS, a bioinformatics tool for accurate identification of transposon insertion sites using next-generation sequencing data', 'Jiang, Chuan|Chen, Chao|Huang, Ziyue|Liu, Renyi|Verdier, Jerome', 'Shanghai Center for Plant Stress Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 201602, China. chjiang@sibs.ac.cn.|Shanghai Center for Plant Stress Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 201602, China. chenchao@sibs.ac.cn.|Shanghai Center for Plant Stress Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 201602, China. ziyhuang@sibs.ac.cn.|Shanghai Center for Plant Stress Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 201602, China. ryliu@sibs.ac.cn.|Shanghai Center for Plant Stress Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 201602, China. javerdier@sibs.ac.cn.', 'China|China|China|China|China', 0, 'Algorithms|Computational Biology|DNA Transposable Elements|High-Throughput Nucleotide Sequencing|Medicago truncatula|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-015-0507-2', '25887332', 'Transposable elements constitute an important part of the genome and are essential in adaptive mechanisms. Transposition events associated with phenotypic changes occur naturally or are induced in insertional mutant populations. Transposon mutagenesis results in multiple random insertions and recovery of most/all the insertions is critical for forward genetics study. Using genome next-generation sequencing data and appropriate bioinformatics tool, it is plausible to accurately identify transposon insertion sites, which could provide candidate causal mutations for desired phenotypes for further functional validation.'),
(96635, 2015, 'bmc', 'Insertion and deletion correcting DNA barcodes based on watermarks', 'Kracht, David|Schober, Steffen', 'Institute of Communications Engineering, Ulm University, Albert-Einstein-Allee 43, Ulm, 89081, Germany. david.kracht@uni-ulm.de.|Institute of Communications Engineering, Ulm University, Albert-Einstein-Allee 43, Ulm, 89081, Germany. steffen.schober.de@ieee.org.', 'Germany|Germany', 10, 'Algorithms|Computational Biology|DNA|DNA Barcoding, Taxonomic|Gene Library|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1186/s12859-015-0482-7', '25887410', 'Barcode multiplexing is a key strategy for sharing the rising capacity of next-generation sequencing devices: Synthetic DNA tags, called barcodes, are attached to natural DNA fragments within the library preparation procedure. Different libraries, can individually be labeled with barcodes for a joint sequencing procedure. A post-processing step is needed to sort the sequencing data according to their origin, utilizing these DNA labels. The final separation step is called demultiplexing and is mainly determined by the characteristics of the DNA code words used as labels. Currently, we are facing two different strategies for barcoding: One is based on the Hamming distance, the other uses the edit metric to measure distances of code words. The theory of channel coding provides well-known code constructions for Hamming metric. They provide a large number of code words with variable lengths and maximal correction capability regarding substitution errors. However, some sequencing platforms are known to have exceptional high numbers of insertion or deletion errors. Barcodes based on the edit distance can take insertion and deletion errors into account in the decoding process. Unfortunately, there is no explicit code-construction known that gives optimal codes for edit metric.'),
(96636, 2015, 'bmc', 'Classification of bioinformatics workflows using weighted versions of partitioning and hierarchical clustering algorithms', 'Lord, Etienne|Diallo, Abdoulaye Baniré|Makarenkov, Vladimir', 'Département dinformatique, Université du Québec à Montréal, C.P. 8888 succ. Centre-Ville, Montreal, QC, H3C 3P8, Canada. lord.etienne@courrier.uqam.ca.|Département dinformatique, Université du Québec à Montréal, C.P. 8888 succ. Centre-Ville, Montreal, QC, H3C 3P8, Canada. diallo.abdoulaye@uqam.ca.|Département dinformatique, Université du Québec à Montréal, C.P. 8888 succ. Centre-Ville, Montreal, QC, H3C 3P8, Canada. makarenkov.vladimir@uqam.ca.', 'Canada|Canada|Canada', 0, 'Algorithms|Cluster Analysis|Computational Biology|Datasets as Topic|Phylogeny|Software|Workflow', 'Journal Article', '10.1186/s12859-015-0508-1', '25887434', 'Workflows, or computational pipelines, consisting of collections of multiple linked tasks are becoming more and more popular in many scientific fields, including computational biology. For example, simulation studies, which are now a must for statistical validation of new bioinformatics methods and software, are frequently carried out using the available workflow platforms. Workflows are typically organized to minimize the total execution time and to maximize the efficiency of the included operations. Clustering algorithms can be applied either for regrouping similar workflows for their simultaneous execution on a server, or for dispatching some lengthy workflows to different servers, or for classifying the available workflows with a view to performing a specific keyword search.'),
(96637, 2015, 'bmc', 'Family-based association analysis: a fast and efficient method of multivariate association analysis with multiple variants', 'Won, Sungho|Kim, Wonji|Lee, Sungyoung|Lee, Young|Sung, Joohon|Park, Taesung', 'Department of Public Health Science, Seoul National University, Seoul, Korea. won1@snu.ac.kr.|Interdisciplinary Program of Bioinformatics, Seoul National University, Seoul, Korea. dnjswlzz11@gmail.com.|Interdisciplinary Program of Bioinformatics, Seoul National University, Seoul, Korea. biznok@gmail.com.|The Center for Genome Science, Korea National Institute of Health, KCDC, Osong, Korea. lyou7688@gmail.com.|Department of Public Health Science, Seoul National University, Seoul, Korea. jsung@snu.ac.kr.|Interdisciplinary Program of Bioinformatics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr.', '-|-|-|-|-|-', 0, 'Cohort Studies|Computational Biology|Computer Simulation|Family|Female|Genetic Variation|Genetics, Population|Genome-Wide Association Study|Genotype|Humans|Male|Models, Statistical|Multivariate Analysis|Oligonucleotide Array Sequence Analysis|Pedigree|Phenotype|Twin Studies as Topic', 'Journal Article', '10.1186/s12859-015-0484-5', '25887481', 'Many disease phenotypes are outcomes of the complicated interplay between multiple genes, and multiple phenotypes are affected by a single or multiple genotypes. Therefore, joint analysis of multiple phenotypes and multiple markers has been considered as an efficient strategy for genome-wide association analysis, and in this work we propose an omnibus family-based association test for the joint analysis of multiple genotypes and multiple phenotypes.'),
(96638, 2015, 'bmc', 'MeSH ORA framework: R/Bioconductor packages to support MeSH over-representation analysis', 'Tsuyuzaki, Koki|Morota, Gota|Ishii, Manabu|Nakazato, Takeru|Miyazaki, Satoru|Nikaido, Itoshi', 'Department of Medical and Life Science, Faculty of Pharmaceutical Science, Tokyo University of Science, 2641 Yamazaki, Noda, 278-8510, Chiba, Japan. j3b12703@ed.tus.ac.jp.|Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE, USA. morota@ansci.wisc.edu.|Bioinformatics Research Unit, Advanced Center for Computing and Communication, RIKEN, 2-1 Hirosawa, Wako, 351-0198, Saitama, Japan. manabu.ishii@riken.jp.|Database Center for Life Science (DBCLS), Research Organization of Information and Systems (ROIS), Faculty of Engineering Building 12, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, 113-0032, Tokyo, Japan. nakazato@dbcls.rois.ac.jp.|Department of Medical and Life Science, Faculty of Pharmaceutical Science, Tokyo University of Science, 2641 Yamazaki, Noda, 278-8510, Chiba, Japan. smiyazak@rs.noda.tus.ac.jp.|Bioinformatics Research Unit, Advanced Center for Computing and Communication, RIKEN, 2-1 Hirosawa, Wako, 351-0198, Saitama, Japan. itoshi.nikaido@riken.jp.', 'Japan|United States|Japan|Japan|Japan|Japan', 21, 'Animals|Caloric Restriction|Computational Biology|Gene Expression Profiling|Genome-Wide Association Study|Humans|Information Storage and Retrieval|Medical Subject Headings|Molecular Sequence Annotation|Oligonucleotide Array Sequence Analysis|Pseudomonas aeruginosa|PubMed|Rats|Software|Vocabulary, Controlled', 'Journal Article', '10.1186/s12859-015-0453-z', '25887539', 'In genome-wide studies, over-representation analysis (ORA) against a set of genes is an essential step for biological interpretation. Many gene annotation resources and software platforms for ORA have been proposed. Recently, Medical Subject Headings (MeSH) terms, which are annotations of PubMed documents, have been used for ORA. MeSH enables the extraction of broader meaning from the gene lists and is expected to become an exhaustive annotation resource for ORA. However, the existing MeSH ORA software platforms are still not sufficient for several reasons.'),
(96639, 2015, 'bmc', 'Systematic computation with functional gene-sets among leukemic and hematopoietic stem cells reveals a favorable prognostic signature for acute myeloid leukemia', 'Yang, Xinan Holly|Li, Meiyi|Wang, Bin|Zhu, Wanqi|Desgardin, Aurelie|Onel, Kenan|de Jong, Jill|Chen, Jianjun|Chen, Luonan|Cunningham, John M', 'Department of Pediatrics, and Comer Childrens Hospital, Section of Hematology/Oncology, The University of Chicago, 900 East 57th Street, KCBD Room 5121, Chicago, Illinois, 60637, USA. xyang2@uchicago.edu.|Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China. limeiyi@sibs.ac.cn.|Department of Pediatrics, and Comer Childrens Hospital, Section of Hematology/Oncology, The University of Chicago, 900 East 57th Street, KCBD Room 5121, Chicago, Illinois, 60637, USA. bwang@peds.bsd.uchicago.edu.|Laboratory Schools, The University of Chicago, Chicago, USA. 1213.ghs@gmail.com.|Department of Pediatrics, and Comer Childrens Hospital, Section of Hematology/Oncology, The University of Chicago, 900 East 57th Street, KCBD Room 5121, Chicago, Illinois, 60637, USA. adesgard@bsd.uchicago.edu.|Department of Pediatrics, and Comer Childrens Hospital, Section of Hematology/Oncology, The University of Chicago, 900 East 57th Street, KCBD Room 5121, Chicago, Illinois, 60637, USA. konel@peds.bsd.uchicago.edu.|Department of Pediatrics, and Comer Childrens Hospital, Section of Hematology/Oncology, The University of Chicago, 900 East 57th Street, KCBD Room 5121, Chicago, Illinois, 60637, USA. jdejong@peds.bsd.uchicago.edu.|Department of Medicine, The University of Chicago, Chicago, USA. jchen@medicine.bsd.uchicago.edu.|Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China. lnchen@sibs.ac.cn.|Department of Pediatrics, and Comer Childrens Hospital, Section of Hematology/Oncology, The University of Chicago, 900 East 57th Street, KCBD Room 5121, Chicago, Illinois, 60637, USA. jmcunningham@uchicago.edu.', 'United States|China|United States|United States|United States|United States|United States|United States|China|United States', 0, 'Algorithms|Gene Expression Profiling|Gene Regulatory Networks|Hematopoietic Stem Cells|Humans|Leukemia, Myeloid, Acute|Neoplastic Stem Cells|Prognosis|Transcriptome', 'Journal Article', '10.1186/s12859-015-0510-7', '25887548', 'Genes that regulate stem cell function are suspected to exert adverse effects on prognosis in malignancy. However, diverse cancer stem cell signatures are difficult for physicians to interpret and apply clinically. To connect the transcriptome and stem cell biology, with potential clinical applications, we propose a novel computational gene-to-function, snapshot-to-dynamics, and biology-to-clinic framework to uncover core functional gene-sets signatures. This framework incorporates three function-centric gene-set analysis strategies: a meta-analysis of both microarray and RNA-seq data, novel dynamic network mechanism (DNM) identification, and a personalized prognostic indicator analysis. This work uses complex disease acute myeloid leukemia (AML) as a research platform.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96640, 2015, 'bmc', 'Automatic segmentation of deep intracerebral electrodes in computed tomography scans', 'Arnulfo, Gabriele|Narizzano, Massimo|Cardinale, Francesco|Fato, Marco Massimo|Palva, Jaakko Matias', 'Department of Informatics, Bioengineering, Robotics and System Engineering - DIBRIS, University of Genoa, Viale Causa 13, Genoa, Italy. gabriele.arnulfo@unige.it.|Department of Informatics, Bioengineering, Robotics and System Engineering - DIBRIS, University of Genoa, Viale Causa 13, Genoa, Italy. massimo.narizzano@unige.it.|C. Munari Centre for Epilepsy Surgery, Niguarda Hospital, Piazza Ospedale Maggiore 3, Milano, Italy. francesco.cardinale@ospedaleniguarda.it.|Department of Informatics, Bioengineering, Robotics and System Engineering - DIBRIS, University of Genoa, Viale Causa 13, Genoa, Italy. marco.fato@unige.it.|Neuroscience Center, University of Helsinki, P.O. Box 56 (Viikinkaari 4) FI-00014, Helsinki, Finland. matias.palva@helsinki.fi.', 'Italy|Italy|Italy|Italy|Finland', 0, 'Adolescent|Adult|Algorithms|Brain|Cone-Beam Computed Tomography|Electrodes|Electroencephalography|Epilepsy|Female|Humans|Male|Middle Aged|Young Adult', 'Journal Article', '10.1186/s12859-015-0511-6', '25887573', 'Invasive monitoring of brain activity by means of intracerebral electrodes is widely practiced to improve pre-surgical seizure onset zone localization in patients with medically refractory seizures. Stereo-Electroencephalography (SEEG) is mainly used to localize the epileptogenic zone and a precise knowledge of the location of the electrodes is expected to facilitate the recordings interpretation and the planning of resective surgery. However, the localization of intracerebral electrodes on post-implant acquisitions is usually time-consuming (i.e., manual segmentation), it requires advanced 3D visualization tools, and it needs the supervision of trained medical doctors in order to minimize the errors. In this paper we propose an automated segmentation algorithm specifically designed to segment SEEG contacts from a thresholded post-implant Cone-Beam CT volume (0.4 mm, 0.4 mm, 0.8 mm). The algorithm relies on the planned position of target and entry points for each electrode as a first estimation of electrode axis. We implemented the proposed algorithm into DEETO, an open source C++ prototype based on ITK library.'),
(96641, 2015, 'bmc', 'NMF-mGPU: non-negative matrix factorization on multi-GPU systems', 'Mejía-Roa, Edgardo|Tabas-Madrid, Daniel|Setoain, Javier|García, Carlos|Tirado, Francisco|Pascual-Montano, Alberto', 'ArTeCS Group, Department of Computer Architecture, Complutense University of Madrid (UCM), Madrid, 28040, Spain. edgardomejia@fis.ucm.es.|Functional Bioinformatics Group, Biocomputing Unit, National Center for Biotechnology-CSIC, UAM, Madrid, 28049, Spain. dtabas@cnb.csic.es.|Functional Bioinformatics Group, Biocomputing Unit, National Center for Biotechnology-CSIC, UAM, Madrid, 28049, Spain. jsetoain@cnb.csic.es.|ArTeCS Group, Department of Computer Architecture, Complutense University of Madrid (UCM), Madrid, 28040, Spain. garsanca@dacya.ucm.es.|ArTeCS Group, Department of Computer Architecture, Complutense University of Madrid (UCM), Madrid, 28040, Spain. ptirado@dacya.ucm.es.|Functional Bioinformatics Group, Biocomputing Unit, National Center for Biotechnology-CSIC, UAM, Madrid, 28049, Spain. pascual@cnb.csic.es.', 'Spain|Spain|Spain|Spain|Spain|Spain', 31, 'Algorithms|Biomarkers, Tumor|Computational Biology|Computer Graphics|Computing Methodologies|Humans|Microarray Analysis|Neurilemmoma|Neurofibroma|Numerical Analysis, Computer-Assisted|Schwann Cells|Software', 'Journal Article', '10.1186/s12859-015-0485-4', '25887585', 'In the last few years, the Non-negative Matrix Factorization ( NMF ) technique has gained a great interest among the Bioinformatics community, since it is able to extract interpretable parts from high-dimensional datasets. However, the computing time required to process large data matrices may become impractical, even for a parallel application running on a multiprocessors cluster. In this paper, we present NMF-mGPU, an efficient and easy-to-use implementation of the NMF algorithm that takes advantage of the high computing performance delivered by Graphics-Processing Units ( GPUs ). Driven by the ever-growing demands from the video-games industry, graphics cards usually provided in PCs and laptops have evolved from simple graphics-drawing platforms into high-performance programmable systems that can be used as coprocessors for linear-algebra operations. However, these devices may have a limited amount of on-board memory, which is not considered by other NMF implementations on GPU.'),
(96642, 2015, 'bmc', 'Prediction of host - pathogen protein interactions between Mycobacterium tuberculosis and Homo sapiens using sequence motifs', 'Huo, Tong|Liu, Wei|Guo, Yu|Yang, Cheng|Lin, Jianping|Rao, Zihe', 'State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300071, China. herohonan@126.com.|State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300071, China. 595643971@qq.com.|State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300071, China. yu.guo@htmdc.org.|State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300071, China. cheng.yang@nankai.edu.cn.|State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300071, China. jianpinglin@nankai.edu.cn.|State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300071, China. raozh@nankai.edu.cn.', 'China|China|China|China|China|China', 0, 'Computational Biology|Host-Pathogen Interactions|Humans|Molecular Sequence Annotation|Mycobacterium tuberculosis|Protein Interaction Mapping|Tuberculosis', 'Journal Article', '10.1186/s12859-015-0535-y', '25887594', 'Emergence of multiple drug resistant strains of M. tuberculosis (MDR-TB) threatens to derail global efforts aimed at reigning in the pathogen. Co-infections of M. tuberculosis with HIV are difficult to treat. To counter these new challenges, it is essential to study the interactions between M. tuberculosis and the host to learn how these bacteria cause disease.'),
(96643, 2015, 'bmc', 'Identification of active miRNA and transcription factor regulatory pathways in human obesity-related inflammation', 'Zhang, Xi-Mei|Guo, Lin|Chi, Mei-Hua|Sun, Hong-Mei|Chen, Xiao-Wen', 'Department of Histology and Embryology, Harbin Medical University, Harbin, 150081, PR China. ximei1119@126.com.|Department of Endocrinology and Metabolism, the Second Affiliated Hospital of Harbin Medical University, Harbin, 150081, PR China. guolin821@gmail.com.|Teaching Experiment Center of Morphology, Harbin Medical University, Harbin, 150081, PR China. 57557413@qq.com.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China. sunhongmei@hrbmu.edu.cn.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China. xiaowenchen8266@163.com.', 'China|China|China|China|China', 0, 'Algorithms|Databases, Factual|Gene Expression Profiling|Gene Regulatory Networks|Humans|Inflammation|MicroRNAs|Obesity|RNA, Messenger|Transcription Factors', 'Journal Article', '10.1186/s12859-015-0512-5', '25887648', 'Obesity-induced chronic inflammation plays a fundamental role in the pathogenesis of metabolic syndrome (MS). Recently, a growing body of evidence supports that miRNAs are largely dysregulated in obesity and that specific miRNAs regulate obesity-associated inflammation. We applied an approach aiming to identify active miRNA-TF-gene regulatory pathways in obesity. Firstly, we detected differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs) from mRNA and miRNA expression profiles, respectively. Secondly, by mapping the DEGs and DEmiRs to the curated miRNA-TF-gene regulatory network as active seed nodes and connect them with their immediate neighbors, we obtained the potential active miRNA-TF-gene regulatory subnetwork in obesity. Thirdly, using a Breadth-First-Search (BFS) algorithm, we identified potential active miRNA-TF-gene regulatory pathways in obesity. Finally, through the hypergeometric test, we identified the active miRNA-TF-gene regulatory pathways that were significantly related to obesity.'),
(96644, 2015, 'bmc', 'Identifying named entities from PubMed for enriching semantic categories', 'Kim, Sun|Lu, Zhiyong|Wilbur, W John', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, 20894, MD, USA. sun.kim@nih.gov.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, 20894, MD, USA. zhiyong.lu@nih.gov.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, 20894, MD, USA. wilbur@ncbi.nlm.nih.gov.', 'United States|United States|United States', 4, 'Artificial Intelligence|Humans|Medical Subject Headings|Natural Language Processing|PubMed|Semantics|Unified Medical Language System|Vocabulary, Controlled', 'Journal Article', '10.1186/s12859-015-0487-2', '25887671', 'Controlled vocabularies such as the Unified Medical Language System (UMLS) and Medical Subject Headings (MeSH) are widely used for biomedical natural language processing (NLP) tasks. However, the standard terminology in such collections suffers from low usage in biomedical literature, e.g. only 13% of UMLS terms appear in MEDLINE.'),
(96645, 2015, 'bmc', 'Wide-coverage relation extraction from MEDLINE using deep syntax', 'Nguyen, Nhung T H|Miwa, Makoto|Tsuruoka, Yoshimasa|Chikayama, Takashi|Tojo, Satoshi', 'School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa, Japan. nthnhung@jaist.ac.jp.|Toyota Technological Institute, Nagoya, Japan. makoto-miwa@toyota-ti.ac.jp.|Graduate School of Engineering, The University of Tokyo, Tokyo, Japan. tsuruoka@logos.t.u-tokyo.ac.jp.|Graduate School of Engineering, The University of Tokyo, Tokyo, Japan. chikayama@logos.t.u-tokyo.ac.jp.|School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa, Japan. tojo@jaist.ac.jp.', 'Japan|Japan|Japan|Japan|Japan', 9, 'Data Mining|MEDLINE|Semantics', 'Evaluation Studies', '10.1186/s12859-015-0538-8', '25887686', 'Relation extraction is a fundamental technology in biomedical text mining. Most of the previous studies on relation extraction from biomedical literature have focused on specific or predefined types of relations, which inherently limits the types of the extracted relations. With the aim of fully leveraging the knowledge described in the literature, we address much broader types of semantic relations using a single extraction framework.'),
(96646, 2015, 'bmc', 'ViVaMBC: estimating viral sequence variation in complex populations from illumina deep-sequencing data using model-based clustering', 'Verbist, Bie|Clement, Lieven|Reumers, Joke|Thys, Kim|Vapirev, Alexander|Talloen, Willem|Wetzels, Yves|Meys, Joris|Aerssens, Jeroen|Bijnens, Luc|Thas, Olivier', 'Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, Gent, 9000, Belgium. Bie.Verbist@ugent.be.|Department of Applied Mathematics, Informatics and Statistics, Ghent University, Krijgslaan 281 S9, Gent, 9000, Belgium. Lieven.Clement@ugent.be.|Janssen R&D, Janssen Pharmaceutical Companies of J&J, Turnhoutseweg 30, Beerse, 2340, Belgium. JReumers@its.jnj.com.|Janssen R&D, Janssen Pharmaceutical Companies of J&J, Turnhoutseweg 30, Beerse, 2340, Belgium. KThys@its.jnj.com.|Janssen R&D, Janssen Pharmaceutical Companies of J&J, Turnhoutseweg 30, Beerse, 2340, Belgium. avapirev@its.jnj.com.|Janssen R&D, Janssen Pharmaceutical Companies of J&J, Turnhoutseweg 30, Beerse, 2340, Belgium. WTalloen@its.jnj.com.|Janssen R&D, Janssen Pharmaceutical Companies of J&J, Turnhoutseweg 30, Beerse, 2340, Belgium. YWetzel@its.jnj.com.|Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, Gent, 9000, Belgium. joris.Meys@Ugent.be.|Janssen R&D, Janssen Pharmaceutical Companies of J&J, Turnhoutseweg 30, Beerse, 2340, Belgium. JAerssen@its.jnj.com.|Janssen R&D, Janssen Pharmaceutical Companies of J&J, Turnhoutseweg 30, Beerse, 2340, Belgium. LBIJNENS@its.jnj.com.|Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, Gent, 9000, Belgium. Olivier.Thas@ugent.be.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 9, 'Algorithms|Cluster Analysis|Genetic Variation|Genome, Viral|Genomics|Hepacivirus|Hepatitis C|High-Throughput Nucleotide Sequencing|Humans|Mutation|Sensitivity and Specificity|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-015-0458-7', '25887734', 'Deep-sequencing allows for an in-depth characterization of sequence variation in complex populations. However, technology associated errors may impede a powerful assessment of low-frequency mutations. Fortunately, base calls are complemented with quality scores which are derived from a quadruplet of intensities, one channel for each nucleotide type for Illumina sequencing. The highest intensity of the four channels determines the base that is called. Mismatch bases can often be corrected by the second best base, i.e. the base with the second highest intensity in the quadruplet. A virus variant model-based clustering method, ViVaMBC, is presented that explores quality scores and second best base calls for identifying and quantifying viral variants. ViVaMBC is optimized to call variants at the codon level (nucleotide triplets) which enables immediate biological interpretation of the variants with respect to their antiviral drug responses.'),
(96647, 2015, 'bmc', 'USI: a fast and accurate approach for conceptual document annotation', 'Fiorini, Nicolas|Ranwez, Sylvie|Montmain, Jacky|Ranwez, Vincent', 'LGI2P research center from the Ecole des mines dAlès, Site de Nîmes, Parc scientifique G. Besse, Nîmes cedex 1, 30035, France. nicolas.fiorini@mines-ales.fr.|LGI2P research center from the Ecole des mines dAlès, Site de Nîmes, Parc scientifique G. Besse, Nîmes cedex 1, 30035, France. sylvie.ranwez@mines-ales.fr.|LGI2P research center from the Ecole des mines dAlès, Site de Nîmes, Parc scientifique G. Besse, Nîmes cedex 1, 30035, France. jacky.montmain@mines-ales.fr.|UMR AGAP, Montpellier SupAgro/CIRAD/INRA, 2 place Pierre Viala, Montpellier Cedex 1, 34060, France. ranwez@supagro.inra.fr.', 'France|France|France|France', 5, 'Abstracting and Indexing as Topic|Algorithms|Humans|Information Storage and Retrieval|Medical Subject Headings|Natural Language Processing|Pattern Recognition, Automated|Semantics|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1186/s12859-015-0513-4', '25887746', 'Semantic approaches such as concept-based information retrieval rely on a corpus in which resources are indexed by concepts belonging to a domain ontology. In order to keep such applications up-to-date, new entities need to be frequently annotated to enrich the corpus. However, this task is time-consuming and requires a high-level of expertise in both the domain and the related ontology. Different strategies have thus been proposed to ease this indexing process, each one taking advantage from the features of the document.'),
(96648, 2015, 'bmc', 'OTO: Ontology Term Organizer', 'Huang, Fengqiong|Macklin, James A|Cui, Hong|Cole, Heather A|Endara, Lorena', 'School of Information Resources and Library Science, University of Arizona, Tucson, USA. huangfq@email.arizona.edu.|Agriculture Agri-Food Canada, Ottawa, Canada. James.Macklin@agr.gc.ca.|School of Information Resources and Library Science, University of Arizona, Tucson, USA. hongcui@email.arizona.edu.|Agriculture Agri-Food Canada, Ottawa, Canada. heather.cole@agr.gc.ca.|Department of Biology, University of Florida, Gainesville, USA. lendara@flmnh.ufl.edu.', 'United States|Canada|United States|Canada|United States', 0, 'Computational Biology|Humans|Natural Language Processing|Semantics|Software|Terminology as Topic|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1186/s12859-015-0488-1', '25887779', 'The need to create controlled vocabularies such as ontologies for knowledge organization and access has been widely recognized in various domains. Despite the indispensable need of thorough domain knowledge in ontology construction, most software tools for ontology construction are designed for knowledge engineers and not for domain experts to use. The differences in the opinions of different domain experts and in the terminology usages in source literature are rarely addressed by existing software.'),
(96649, 2015, 'bmc', 'Feature engineering for MEDLINE citation categorization with MeSH', 'Jimeno Yepes, Antonio Jose|Plaza, Laura|Carrillo-de-Albornoz, Jorge|Mork, James G|Aronson, Alan R', 'Department of Computing and Information Systems, The University of Melbourne, Parkville, 3010, VIC, Australia. antonio.jimeno@gmail.com.|UNED NLP & IR Group, C/Juan del Rosal 16, Madrid, 28040, Spain. lplaza@lsi.uned.es.|UNED NLP & IR Group, C/Juan del Rosal 16, Madrid, 28040, Spain. jcalbornoz@lsi.uned.es.|National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA. mork@nlm.nih.gov.|National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA. alan@nlm.nih.gov.', 'Australia|Spain|Spain|United States|United States', 0, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Humans|Information Storage and Retrieval|MEDLINE|Medical Subject Headings|Semantics', 'Journal Article', '10.1186/s12859-015-0539-7', '25887792', 'Research in biomedical text categorization has mostly used the bag-of-words representation. Other more sophisticated representations of text based on syntactic, semantic and argumentative properties have been less studied. In this paper, we evaluate the impact of different text representations of biomedical texts as features for reproducing the MeSH annotations of some of the most frequent MeSH headings. In addition to unigrams and bigrams, these features include noun phrases, citation meta-data, citation structure, and semantic annotation of the citations.'),
(96650, 2015, 'bmc', 'Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data', 'Gong, Wuming|Koyano-Nakagawa, Naoko|Li, Tongbin|Garry, Daniel J', 'Lillehei Heart Institute, University of Minnesota, 2231 6th St S.E, 4-165 CCRB, Minneapolis, MN, 55114, USA. gongx030@umn.edu.|Lillehei Heart Institute, University of Minnesota, 2231 6th St S.E, 4-165 CCRB, Minneapolis, MN, 55114, USA. koyano@umn.edu.|AccuraScience LLC, 5721 Merle Hay Road, Suite #16B, Johnston, IA, 50131, USA. toli@us.accurascience.com.|Lillehei Heart Institute, University of Minnesota, 2231 6th St S.E, 4-165 CCRB, Minneapolis, MN, 55114, USA. garry@umn.edu.', 'United States|United States|United States|United States', 0, 'Animals|Bayes Theorem|Binding Sites|Cell Differentiation|Chromatin Immunoprecipitation|Embryonic Stem Cells|Enhancer Elements, Genetic|Gene Regulatory Networks|Heart|Histones|Mice|Muscle Development|Myoblasts, Cardiac|Myocytes, Cardiac|Promoter Regions, Genetic|Sequence Analysis, RNA|Transcription Factors', 'Journal Article', '10.1186/s12859-015-0460-0', '25887857', 'Decoding the temporal control of gene expression patterns is key to the understanding of the complex mechanisms that govern developmental decisions during heart development. High-throughput methods have been employed to systematically study the dynamic and coordinated nature of cardiac differentiation at the global level with multiple dimensions. Therefore, there is a pressing need to develop a systems approach to integrate these data from individual studies and infer the dynamic regulatory networks in an unbiased fashion.'),
(96651, 2015, 'bmc', 'GBSX: a toolkit for experimental design and demultiplexing genotyping by sequencing experiments', 'Herten, Koen|Hestand, Matthew S|Vermeesch, Joris R|Van Houdt, Jeroen K J', 'Center for Human Genetics, KU Leuven, Herestraat 49, Leuven, 3000, Belgium. koen.herten@med.kuleuven.be.|Center for Human Genetics, KU Leuven, Herestraat 49, Leuven, 3000, Belgium. matthew.hestand@med.kuleuven.be.|Center for Human Genetics, KU Leuven, Herestraat 49, Leuven, 3000, Belgium. joris.vermeesch@med.kuleuven.be.|Center for Human Genetics, KU Leuven, Herestraat 49, Leuven, 3000, Belgium. jeroen.vanhoudt@med.kuleuven.be.', 'Belgium|Belgium|Belgium|Belgium', 37, 'DNA Restriction Enzymes|Genotyping Techniques|High-Throughput Nucleotide Sequencing|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-015-0514-3', '25887893', 'Massive parallel sequencing is a powerful tool for variant discovery and genotyping. To reduce costs, sequencing of restriction enzyme based reduced representation libraries can be utilized. This technology is generally referred to as Genotyping By Sequencing (GBS). To deal with GBS experimental design and initial processing specific bioinformatic tools are needed.'),
(96652, 2015, 'bmc', 'OpenMS-Simulator: an open-source software for theoretical tandem mass spectrum prediction', 'Wang, Yaojun|Yang, Fei|Wu, Peng|Bu, Dongbo|Sun, Shiwei', 'Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, 6, Kexueyuan South Road, Zhongguancun, Beijing, 100190, China. wangyaojun@ict.ac.cn.|Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, 6, Kexueyuan South Road, Zhongguancun, Beijing, 100190, China. yangfei@ict.ac.cn.|Institute of Biophysics, Chinese Academy of Sciences, 15, Datun Road, Chaoyang District, Beijing, 100101, China. wupeng@moon.ibp.ac.cn.|Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, 6, Kexueyuan South Road, Zhongguancun, Beijing, 100190, China. dbu@ict.ac.cn.|Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, 6, Kexueyuan South Road, Zhongguancun, Beijing, 100190, China. dwsun@ict.ac.cn.', 'China|China|China|China|China', 0, 'Algorithms|Computer Simulation|Databases, Factual|Humans|Models, Theoretical|Peptide Fragments|Proteins|Software|Tandem Mass Spectrometry', 'Journal Article', '10.1186/s12859-015-0540-1', '25887925', 'Tandem mass spectrometry (MS/MS) acts as a key technique for peptide identification. The MS/MS-based peptide identification approaches can be categorized into two families, namely, de novo and database search. Both of the two types of approaches can benefit from an accurate prediction of theoretical spectrum. A theoretical spectrum consists of m/z and intensity of possibly occurring ions, which are estimated via simulating the spectrum generating process. Extensive researches have been conducted for theoretical spectrum prediction, however, the prediction methods suffer from low prediciton accuracy due to oversimplifications in the spectrum simulation process.'),
(96653, 2015, 'bmc', 'Metabolome searcher: a high throughput tool for metabolite identification and metabolic pathway mapping directly from mass spectrometry and using genome restriction', 'Dhanasekaran, A Ranjitha|Pearson, Jon L|Ganesan, Balasubramanian|Weimer, Bart C', 'Center for Integrated BioSystems, Computer Science Department, Utah State University, Logan, 84322-8700, USA. bcweimer@ucdavis.edu.|Center for Integrated BioSystems, Computer Science Department, Utah State University, Logan, 84322-8700, USA. bcweimer@ucdavis.edu.|Center for Integrated BioSystems, Computer Science Department, Utah State University, Logan, 84322-8700, USA. bcweimer@ucdavis.edu.|University of California, Davis, School of Veterinary Medicine, 1089 Veterinary Medicine Dr., VM3B, Room 4023, Davis, CA, 95616, USA. bcweimer@ucdavis.edu.', 'United States|United States|United States|United States', 0, 'Bacteria|Databases, Factual|Genome, Bacterial|Mass Spectrometry|Metabolic Networks and Pathways|Metabolome|Metabolomics|Software', 'Journal Article', '10.1186/s12859-015-0462-y', '25887958', 'Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organisms genome as a database restricts metabolite identification to only those compounds that the organism can produce.'),
(96654, 2015, 'bmc', 'aTRAM - automated target restricted assembly method: a fast method for assembling loci across divergent taxa from next-generation sequencing data', 'Allen, Julie M|Huang, Daisie I|Cronk, Quentin C|Johnson, Kevin P', 'Illinois Natural History Survey, University of Illinois, Champaign, IL, 61820, USA. juliema@illinois.edu.|Department of Botany and Beaty Biodiversity Centre, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada. daisie@mac.com.|Department of Botany and Beaty Biodiversity Centre, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada. quentin.cronk@ubc.ca.|Illinois Natural History Survey, University of Illinois, Champaign, IL, 61820, USA. kpjohnso@illinois.edu.', 'United States|Canada|Canada|United States', 33, 'Genetic Loci|Genomic Library|Genomics|High-Throughput Nucleotide Sequencing|Phylogeny|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1186/s12859-015-0515-2', '25887972', 'Assembling genes from next-generation sequencing data is not only time consuming but computationally difficult, particularly for taxa without a closely related reference genome. Assembling even a draft genome using de novo approaches can take days, even on a powerful computer, and these assemblies typically require data from a variety of genomic libraries. Here we describe software that will alleviate these issues by rapidly assembling genes from distantly related taxa using a single library of paired-end reads: aTRAM, automated Target Restricted Assembly Method. The aTRAM pipeline uses a reference sequence, BLAST, and an iterative approach to target and locally assemble the genes of interest.'),
(96655, 2015, 'bmc', 'Interpolation based consensus clustering for gene expression time series', 'Chiu, Tai-Yu|Hsu, Ting-Chieh|Yen, Chia-Cheng|Wang, Jia-Shung', 'Department of Computer Science, National Tsing Hua University, No. 101, Section 2, Kuang-Fu Road, HsinChu, 30013, Taiwan. tychiu@vc.cs.nthu.edu.tw.|Department of Computer Science, National Tsing Hua University, No. 101, Section 2, Kuang-Fu Road, HsinChu, 30013, Taiwan. tchsu@vc.cs.nthu.edu.tw.|Department of Computer Science, National Tsing Hua University, No. 101, Section 2, Kuang-Fu Road, HsinChu, 30013, Taiwan. ccyen@vc.cs.nthu.edu.tw.|Department of Computer Science, National Tsing Hua University, No. 101, Section 2, Kuang-Fu Road, HsinChu, 30013, Taiwan. jswang@cs.nthu.edu.tw.', '-|-|-|-', 6, 'Algorithms|Cell Cycle|Cluster Analysis|Computer Graphics|Consensus Sequence|Galactose|Gene Expression Profiling|Gene Expression Regulation, Fungal|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Spores, Fungal|Time Factors', 'Journal Article', '10.1186/s12859-015-0541-0', '25888019', 'Unsupervised analyses such as clustering are the essential tools required to interpret time-series expression data from microarrays. Several clustering algorithms have been developed to analyze gene expression data. Early methods such as k-means, hierarchical clustering, and self-organizing maps are popular for their simplicity. However, because of noise and uncertainty of measurement, these common algorithms have low accuracy. Moreover, because gene expression is a temporal process, the relationship between successive time points should be considered in the analyses. In addition, biological processes are generally continuous, therefore, the datasets collected from time series experiments are often found to have an insufficient number of data points and, as a result, compensation for missing data can also be an issue.'),
(96656, 2015, 'bmc', 'Efficient representation of uncertainty in multiple sequence alignments using directed acyclic graphs', 'Herman, Joseph L|Novák, Ádám|Lyngsø, Rune|Szabó, Adrienn|Miklós, István|Hein, Jotun', 'Department of Statistics, University of Oxford, 1 South Parks Road, Oxford, OX1 3TG, UK. herman@stats.ox.ac.uk.|Department of Statistics, University of Oxford, 1 South Parks Road, Oxford, OX1 3TG, UK. novak@stats.ox.ac.uk.|Department of Statistics, University of Oxford, 1 South Parks Road, Oxford, OX1 3TG, UK. rune@lyngsoe.eu.|Institute of Computer Science and Control, Hungarian Academy of Sciences, Lagymanyosi u. 11., Budapest, 1111, Hungary. adrienn.szabo@sztaki.mta.hu.|Institute of Computer Science and Control, Hungarian Academy of Sciences, Lagymanyosi u. 11., Budapest, 1111, Hungary. miklosi@renyi.hu.|Department of Statistics, University of Oxford, 1 South Parks Road, Oxford, OX1 3TG, UK. hein@stats.ox.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom|Hungary|Hungary|United Kingdom', 0, 'Algorithms|Computational Biology|Computer Graphics|Computer Simulation|Humans|Models, Statistical|Sequence Alignment|Software|Uncertainty', 'Journal Article', '10.1186/s12859-015-0516-1', '25888064', 'A standard procedure in many areas of bioinformatics is to use a single multiple sequence alignment (MSA) as the basis for various types of analysis. However, downstream results may be highly sensitive to the alignment used, and neglecting the uncertainty in the alignment can lead to significant bias in the resulting inference. In recent years, a number of approaches have been developed for probabilistic sampling of alignments, rather than simply generating a single optimum. However, this type of probabilistic information is currently not widely used in the context of downstream inference, since most existing algorithms are set up to make use of a single alignment.'),
(96657, 2015, 'bmc', 'Impact of missing data imputation methods on gene expression clustering and classification', 'de Souto, Marcilio C P|Jaskowiak, Pablo A|Costa, Ivan G', 'Univ. Orleans, INSA Centre Val de Loire, LIFO EA 4022, Orleans, France. marcilio.desouto@univ-orleans.fr.|Institute of Mathematics and Computer Sciences, University of São Paulo, São Carlos - SP, Brazil. pablo@icmc.usp.br.|Center of Informatics, Federal University of Pernambuco, Recife - PE, Brazil. ivan.costa@rwth-aachen.de.', 'France|Brazil|Brazil', 32, 'Algorithms|Cluster Analysis|Data Interpretation, Statistical|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/s12859-015-0494-3', '25888091', 'Several missing value imputation methods for gene expression data have been proposed in the literature. In the past few years, researchers have been putting a great deal of effort into presenting systematic evaluations of the different imputation algorithms. Initially, most algorithms were assessed with an emphasis on the accuracy of the imputation, using metrics such as the root mean squared error. However, it has become clear that the success of the estimation of the expression value should be evaluated in more practical terms as well. One can consider, for example, the ability of the method to preserve the significant genes in the dataset, or its discriminative/predictive power for classification/clustering purposes.'),
(96658, 2015, 'bmc', 'CHEXVIS: a tool for molecular channel extraction and visualization', 'Masood, Talha Bin|Sandhya, Sankaran|Chandra, Nagasuma|Natarajan, Vijay', 'Department of Computer Science and Automation, Indian Institute of Science, Bangalore, 560012, India. tbmasood@csa.iisc.ernet.in.|Department of Biochemistry, Indian Institute of Science, Bangalore, 560012, India. sandhya@mbu.iisc.ernet.in.|Department of Biochemistry, Indian Institute of Science, Bangalore, 560012, India. nchandra@biochem.iisc.ernet.in.|Department of Computer Science and Automation, Indian Institute of Science, Bangalore, 560012, India. vijayn@csa.iisc.ernet.in.', 'India|India|India|India', 42, 'Computational Biology|Computer Graphics|Humans|Imaging, Three-Dimensional|Ion Channels|Membrane Proteins|Models, Molecular|Protein Conformation|Software|Static Electricity|Substrate Specificity|User-Computer Interface', 'Journal Article', '10.1186/s12859-015-0545-9', '25888118', 'Understanding channel structures that lead to active sites or traverse the molecule is important in the study of molecular functions such as ion, ligand, and small molecule transport. Efficient methods for extracting, storing, and analyzing protein channels are required to support such studies. Further, there is a need for an integrated framework that supports computation of the channels, interactive exploration of their structure, and detailed visual analysis of their properties.'),
(96659, 2015, 'bmc', 'micropan: an R-package for microbial pan-genomics', 'Snipen, Lars|Liland, Kristian Hovde', 'Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, P.O. Box 5003, N-1432, Ås, Norway. lars.snipen@nmbu.no.|Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, P.O. Box 5003, N-1432, Ås, Norway. kristian.liland@nofima.no.', 'Norway|Norway', 0, 'Algorithms|Computational Biology|Enterococcus|Genome, Bacterial|Genomics|Software', 'Journal Article', '10.1186/s12859-015-0517-0', '25888166', 'A pan-genome is defined as the set of all unique gene families found in one or more strains of a prokaryotic species. Due to the extensive within-species diversity in the microbial world, the pan-genome is often many times larger than a single genome. Studies of pan-genomes have become popular due to the easy access to whole-genome sequence data for prokaryotes. A pan-genome study reveals species diversity and gene families that may be of special interest, e.g because of their role in bacterial survival or their ability to discriminate strains.'),
(96660, 2015, 'bmc', 'A semi-supervised tensor regression model for siRNA efficacy prediction', 'Thang, Bui Ngoc|Ho, Tu Bao|Kanda, Tatsuo', 'School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa, Japan. thangbn@jaist.ac.jp.|School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa, Japan. bao@jaist.ac.jp.|Graduate School of Medicine, Chiba University, 1-8-1 Inohahan, Chuo-ku, Chiba, Japan. kandat-cib@umin.ac.jp.', 'Japan|Japan|Japan', 5, 'Algorithms|Computer Simulation|Humans|RNA Interference|RNA, Small Interfering|Regression Analysis|Sequence Analysis, RNA', 'Journal Article', '10.1186/s12859-015-0495-2', '25888201', 'Short interfering RNAs (siRNAs) can knockdown target genes and thus have an immense impact on biology and pharmacy research. The key question of which siRNAs have high knockdown ability in siRNA research remains challenging as current known results are still far from expectation.'),
(96661, 2015, 'bmc', 'An evidence-based approach to identify aging-related genes in Caenorhabditis elegans', 'Callahan, Alison|Cifuentes, Juan José|Dumontier, Michel', 'Stanford Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford California, AC, USA. acallaha@stanford.edu.|Molecular Bioinformatics Laboratory, Millennium Institute on Immunology and Immunotherapy, 49 Santiago, CP, 8330025, Portugal. jjcifuentes@uc.cl.|Stanford Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford California, AC, USA. michel.dumontier@stanford.edu.', 'United States|Portugal|United States', 7, 'Aging|Animals|Caenorhabditis elegans|Caenorhabditis elegans Proteins|Computational Biology|Databases, Factual|Gene Expression Profiling|Gene Ontology|High-Throughput Nucleotide Sequencing|Humans|Information Storage and Retrieval|Software', 'Journal Article', '10.1186/s12859-015-0469-4', '25888240', 'Extensive studies have been carried out on Caenorhabditis elegans as a model organism to elucidate mechanisms of aging and the effects of perturbing known aging-related genes on lifespan and behavior. This research has generated large amounts of experimental data that is increasingly difficult to integrate and analyze with existing databases and domain knowledge. To address this challenge, we demonstrate a scalable and effective approach for automatic evidence gathering and evaluation that leverages existing experimental data and literature-curated facts to identify genes involved in aging and lifespan regulation in C. elegans.'),
(96662, 2015, 'bmc', 'Identification of binding sites and favorable ligand binding moieties by virtual screening and self-organizing map analysis', 'Harigua-Souiai, Emna|Cortes-Ciriano, Isidro|Desdouits, Nathan|Malliavin, Thérèse E|Guizani, Ikram|Nilges, Michael|Blondel, Arnaud|Bouvier, Guillaume', 'Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. emna.harigua@pasteur.fr.|Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. isidro.cortes@pasteur.fr.|Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. nathan@pasteur.fr.|Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. terez@pasteur.fr.|Laboratory of Molecular Epidemiology and Experimental Pathology - LR11IPT04, Institut Pasteur de Tunis, Université Tunis el Manar - Tunisia, 13, Place Pasteur, Tunis, 1002, Tunisia. ikram.guizani@pasteur.rns.tn.|Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. nilges@pasteur.fr.|Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. ablondel@pasteur.fr.|Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. guillaume.bouvier@pasteur.fr.', 'France|France|France|France|Tunisia|France|France|France', 0, 'Algorithms|Binding Sites|Drug Design|HIV Reverse Transcriptase|Ligands|Molecular Docking Simulation|Proto-Oncogene Proteins c-abl', 'Journal Article', '10.1186/s12859-015-0518-z', '25888251', 'Identifying druggable cavities on a protein surface is a crucial step in structure based drug design. The cavities have to present suitable size and shape, as well as appropriate chemical complementarity with ligands.'),
(96663, 2015, 'bmc', 'The effect of rare variants on inflation of the test statistics in case-control analyses', 'Pirie, Ailith|Wood, Angela|Lush, Michael|Tyrer, Jonathan|Pharoah, Paul D P', 'Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, 2 Worts Causeway, Cambridge, CB1 8RN, UK. ap736@medschl.cam.ac.uk.|Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, 2 Worts Causeway, Cambridge, CB1 8RN, UK. amw79@medschl.cam.ac.uk.|Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, 2 Worts Causeway, Cambridge, CB1 8RN, UK. mjl81@medschl.cam.ac.uk.|Department of Oncology, Strangeways Research Laboratory, University of Cambridge, 2 Worts Causeway, Cambridge, CB1 8RN, UK. jpt34@medschl.cam.ac.uk.|Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, 2 Worts Causeway, Cambridge, CB1 8RN, UK. pp10001@medschl.cam.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 6, 'Case-Control Studies|Computer Simulation|Data Interpretation, Statistical|Gene Frequency|Genetic Association Studies|Genetic Markers|Genetic Predisposition to Disease|Genetic Variation|Heterozygote|Humans|Models, Genetic|Models, Statistical', 'Journal Article', '10.1186/s12859-015-0496-1', '25888290', 'The detection of bias due to cryptic population structure is an important step in the evaluation of findings of genetic association studies. The standard method of measuring this bias in a genetic association study is to compare the observed median association test statistic to the expected median test statistic. This ratio is inflated in the presence of cryptic population structure. However, inflation may also be caused by the properties of the association test itself particularly in the analysis of rare variants. We compared the properties of the three most commonly used association tests: the likelihood ratio test, the Wald test and the score test when testing rare variants for association using simulated data.'),
(96664, 2015, 'bmc', 'A network model for angiogenesis in ovarian cancer', 'Glass, Kimberly|Quackenbush, John|Spentzos, Dimitrios|Haibe-Kains, Benjamin|Yuan, Guo-Cheng', 'Dana-Farber Cancer Institute, Boston, MA, USA. rekrg@channing.harvard.edu.|Dana-Farber Cancer Institute, Boston, MA, USA. johnq@jimmy.harvard.edu.|Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. dspentzo@bidmc.harvard.edu.|Princess Margaret Cancer Center, University Health Network, Toronto, ON, M5G 2M9, Canada. bhaibeka@uhnresearch.ca.|Dana-Farber Cancer Institute, Boston, MA, USA. gcyuan@jimmy.harvard.edu.', 'United States|United States|Israel|Canada|United States', 35, 'Antineoplastic Agents|Data Interpretation, Statistical|Epigenomics|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|Models, Statistical|Neovascularization, Pathologic|Ovarian Neoplasms|Transcription Factors', 'Journal Article', '10.1186/s12859-015-0551-y', '25888305', 'We recently identified two robust ovarian cancer subtypes, defined by the expression of genes involved in angiogenesis, with significant differences in clinical outcome. To identify potential regulatory mechanisms that distinguish the subtypes we applied PANDA, a method that uses an integrative approach to model information flow in gene regulatory networks.'),
(96665, 2015, 'bmc', 'Identifying module biomarker in type 2 diabetes mellitus by discriminative area of functional activity', 'Zhang, Xindong|Gao, Lin|Liu, Zhi-Ping|Chen, Luonan', 'School of Computer Science and Technology, Xidian University, Xian, 710000, China. zxd841@163.com.|School of Computer Science and Technology, Xidian University, Xian, 710000, China. lgao@mail.xidian.edu.cn.|Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Shandong, 250061, China. zpliu@sdu.edu.cn.|Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China. lnchen@sibs.ac.cn.', 'China|China|China|China', 0, 'Biomarkers|Computational Biology|Diabetes Mellitus, Type 2|Gene Expression Profiling|Gene Regulatory Networks|Humans|Muscle, Skeletal|Protein Interaction Mapping', 'Journal Article', '10.1186/s12859-015-0519-y', '25888350', 'Identifying diagnosis and prognosis biomarkers from expression profiling data is of great significance for achieving personalized medicine and designing therapeutic strategy in complex diseases. However, the reproducibility of identified biomarkers across tissues and experiments is still a challenge for this issue.'),
(96666, 2015, 'bmc', 'GeneDig: a web application for accessing genomic and bioinformatics knowledge', 'Suciu, Radu M|Aydin, Emir|Chen, Brian E', 'Centre for Research in Neuroscience, Research Institute of the McGill University Health Centre, Montreal General Hospital, 1650 Cedar Ave, L7-224, Montréal, H3G 1A4, , Québec, Canada. mihai.suciu@mail.mcgill.ca.|Centre for Research in Neuroscience, Research Institute of the McGill University Health Centre, Montreal General Hospital, 1650 Cedar Ave, L7-224, Montréal, H3G 1A4, , Québec, Canada. emir.aydin@mail.mcgill.ca.|Centre for Research in Neuroscience, Research Institute of the McGill University Health Centre, Montreal General Hospital, 1650 Cedar Ave, L7-224, Montréal, H3G 1A4, , Québec, Canada. brian.chen@mcgill.ca.', 'Canada|Canada|Canada', 3, 'Base Sequence|Computational Biology|Databases, Factual|Genes|Genome, Human|Genomics|Humans|Information Storage and Retrieval|Internet|Molecular Sequence Data|Proteins|Proteomics|Sequence Analysis, DNA|Systems Biology', 'Journal Article', '10.1186/s12859-015-0497-0', '25888373', 'With the exponential increase and widespread availability of genomic, transcriptomic, and proteomic data, accessing these -omics data is becoming increasingly difficult. The current resources for accessing and analyzing these data have been created to perform highly specific functions intended for specialists, and thus typically emphasize functionality over user experience.'),
(96667, 2015, 'bmc', 'Comparative proteomics: assessment of biological variability and dataset comparability', 'Kim, Sa Rang|Nguyen, Tuong Vi|Seo, Na Ri|Jung, Seunghup|An, Hyun Joo|Mills, David A|Kim, Jae Han', 'Department of Food and Nutrition, Chungnam National University, Daejeon, 305-764, South Korea. ksr7744@cnu.ac.kr.|Department of Food and Nutrition, Chungnam National University, Daejeon, 305-764, South Korea. t.vi.nguyen@gmail.com.|Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, South Korea. snr85@cnu.ac.kr.|Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, South Korea. shjeong0512@gmail.com.|Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon, 305-764, South Korea. hjan@cnu.ac.kr.|Robert Mondavi Institute for Wine and Food Science, Department of Food Science, University of California, Davis, CA, 95616, USA. damills@ucdavis.edu.|Department of Food and Nutrition, Chungnam National University, Daejeon, 305-764, South Korea. jaykim@cnu.ac.kr.', 'United States|United States|United States|United States|United States|United States|United States', 1, 'Bacterial Proteins|Chromatography, Liquid|Databases, Protein|Green Fluorescent Proteins|Lactobacillus|Proteomics|Reference Standards|Tandem Mass Spectrometry', 'Comparative Study', '10.1186/s12859-015-0561-9', '25888384', 'Comparative proteomics in bacteria are often hampered by the differential nature of dataset quality and/or inherent biological deviations. Although common practice compensates by reproducing and normalizing datasets from a single sample, the degree of certainty is limited in comparison of multiple dataset. To surmount these limitations, we introduce a two-step assessment criterion using: (1) the relative number of total spectra (R TS ) to determine if two LC-MS/MS datasets are comparable and (2) nine glycolytic enzymes as internal standards for a more accurate calculation of relative amount of proteins. Lactococcus lactis HR279 and JHK24 strains expressing high or low levels (respectively) of green fluorescent protein (GFP) were used for the model system. GFP abundance was determined by spectral counting and direct fluorescence measurements. Statistical analysis determined relative GFP quantity obtained from our approach matched values obtained from fluorescence measurements.'),
(96668, 2015, 'bmc', 'NoDe: a fast error-correction algorithm for pyrosequencing amplicon reads', 'Mysara, Mohamed|Leys, Natalie|Raes, Jeroen|Monsieurs, Pieter', 'Unit of Microbiology, Belgian Nuclear Research Centre (SCK CEN), Mol, Belgium. mohamed.mysara@sckcen.be.|Unit of Microbiology, Belgian Nuclear Research Centre (SCK CEN), Mol, Belgium. natalie.leys@sckcen.be.|Department of Bioscience Engineering, Vrije Universiteit Brussel, Brussels, Belgium. jeroen.raes@gmail.com.|Unit of Microbiology, Belgian Nuclear Research Centre (SCK CEN), Mol, Belgium. pieter.monsieurs@sckcen.be.', 'Belgium|Belgium|Belgium|Belgium', 10, 'Algorithms|Bacteria|Cluster Analysis|Metagenomics|RNA, Ribosomal, 16S|Sequence Analysis, DNA', 'Journal Article', '10.1186/s12859-015-0520-5', '25888405', 'The popularity of new sequencing technologies has led to an explosion of possible applications, including new approaches in biodiversity studies. However each of these sequencing technologies suffers from sequencing errors originating from different factors. For 16S rRNA metagenomics studies, the 454 pyrosequencing technology is one of the most frequently used platforms, but sequencing errors still lead to important data analysis issues (e.g. in clustering in taxonomic units and biodiversity estimation). Moreover, retaining a higher portion of the sequencing data by preserving as much of the read length as possible while maintaining the error rate within an acceptable range, will have important consequences at the level of taxonomic precision.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(96669, 2015, 'bmc', 'IPO: a tool for automated optimization of XCMS parameters', 'Libiseller, Gunnar|Dvorzak, Michaela|Kleb, Ulrike|Gander, Edgar|Eisenberg, Tobias|Madeo, Frank|Neumann, Steffen|Trausinger, Gert|Sinner, Frank|Pieber, Thomas|Magnes, Christoph', 'Joanneum Research Forschungsgesellschaft m.b.H., HEALTH, Institute for Biomedicine and Health Sciences, Graz, Austria. gunnar.libiseller@joanneum.at.|Joanneum Research Forschungsgesellschaft m.b.H., POLICIES, Institute for Economic and Innovation Research, Graz, Austria. michaela.dvorzak@joanneum.at.|Joanneum Research Forschungsgesellschaft m.b.H., POLICIES, Institute for Economic and Innovation Research, Graz, Austria. ulrike.kleb@joanneum.at.|Joanneum Research Forschungsgesellschaft m.b.H., HEALTH, Institute for Biomedicine and Health Sciences, Graz, Austria. edgar.gander@joanneum.at.|Institute of Molecular Biosciences, NAWI Graz, University of Graz, 8010, Graz, Austria. tobias.eisenberg@uni-graz.at.|Institute of Molecular Biosciences, NAWI Graz, University of Graz, 8010, Graz, Austria. frank.madeo@uni-graz.at.|Department of Stress- and Developmental Biology, Leibniz Institute of Plant Biochemistry, Halle, Germany. sneumann@ipb-halle.de.|Joanneum Research Forschungsgesellschaft m.b.H., HEALTH, Institute for Biomedicine and Health Sciences, Graz, Austria. gert.trausinger@joanneum.at.|Joanneum Research Forschungsgesellschaft m.b.H., HEALTH, Institute for Biomedicine and Health Sciences, Graz, Austria. frank.sinner@joanneum.at.|Joanneum Research Forschungsgesellschaft m.b.H., HEALTH, Institute for Biomedicine and Health Sciences, Graz, Austria. thomas.pieber@medunigraz.at.|Joanneum Research Forschungsgesellschaft m.b.H., HEALTH, Institute for Biomedicine and Health Sciences, Graz, Austria. ca.health@joanneum.at.', 'Austria|Austria|Austria|Austria|Austria|Austria|Germany|Austria|Austria|Austria|Austria', 124, 'Algorithms|Animals|Carbon Radioisotopes|Chromatography, Liquid|Electronic Data Processing|Heart|Humans|Lipids|Lung|Mass Spectrometry|Metabolomics|Mice|Muscles|Programming Languages|Reproducibility of Results|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1186/s12859-015-0562-8', '25888443', 'Untargeted metabolomics generates a huge amount of data. Software packages for automated data processing are crucial to successfully process these data. A variety of such software packages exist, but the outcome of data processing strongly depends on algorithm parameter settings. If they are not carefully chosen, suboptimal parameter settings can easily lead to biased results. Therefore, parameter settings also require optimization. Several parameter optimization approaches have already been proposed, but a software package for parameter optimization which is free of intricate experimental labeling steps, fast and widely applicable is still missing.'),
(96670, 2015, 'bmc', 'DomSign: a top-down annotation pipeline to enlarge enzyme space in the protein universe', 'Wang, Tianmin|Mori, Hiroshi|Zhang, Chong|Kurokawa, Ken|Xing, Xin-Hui|Yamada, Takuji', 'Department of Biological Information, Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, 2-12-1 M6-3, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan. wtm12@mails.tsinghua.edu.cn.|Department of Biological Information, Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, 2-12-1 M6-3, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan. mori.h.af@m.titech.ac.jp.|Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China. chongzhang@mail.tsinghua.edu.cn.|Department of Biological Information, Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, 2-12-1 M6-3, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan. ken@bio.titech.ac.jp.|Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China. xhxing@mail.tsinghua.edu.cn.|Department of Biological Information, Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, 2-12-1 M6-3, Ookayama, Meguro-ku, Tokyo, 152-8550, Japan. takuji@bio.titech.ac.jp.', 'Japan|Japan|China|Japan|China|Japan', 5, 'Databases, Protein|Enzymes|Genome, Bacterial|Humans|Metagenomics|Molecular Sequence Annotation|Protein Structure, Tertiary|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/s12859-015-0499-y', '25888481', 'Computational predictions of catalytic function are vital for in-depth understanding of enzymes. Because several novel approaches performing better than the common BLAST tool are rarely applied in research, we hypothesized that there is a large gap between the number of known annotated enzymes and the actual number in the protein universe, which significantly limits our ability to extract additional biologically relevant functional information from the available sequencing data. To reliably expand the enzyme space, we developed DomSign, a highly accurate domain signature-based enzyme functional prediction tool to assign Enzyme Commission (EC) digits.'),
(96671, 2015, 'bmc', 'Comparative interactions of withanolides and sterols with two members of sterol glycosyltransferases from Withania somnifera', 'Pandey, Vibha|Dhar, Yogeshwar Vikram|Gupta, Parul|Bag, Sumit K|Atri, Neelam|Asif, Mehar Hasan|Trivedi, Prabodh Kumar|Misra, Pratibha', 'Council of Scientific and Industrial Research, National Botanical Research Institute (CSIR-NBRI), Rana Pratap Marg, Lucknow, 226 001, India. vibhashekharmishra@gmail.com.|Council of Scientific and Industrial Research, National Botanical Research Institute (CSIR-NBRI), Rana Pratap Marg, Lucknow, 226 001, India. yogi.bioinfo@gmail.com.|Council of Scientific and Industrial Research, National Botanical Research Institute (CSIR-NBRI), Rana Pratap Marg, Lucknow, 226 001, India. gupta.parulnbri@gmail.com.|Council of Scientific and Industrial Research, National Botanical Research Institute (CSIR-NBRI), Rana Pratap Marg, Lucknow, 226 001, India. sumit.bag@nbri.res.in.|Department of Botany, Faculty of Science, Banaras Hindu University, Varanasi, 221005, India. neelam.bhu@gmail.com.|Council of Scientific and Industrial Research, National Botanical Research Institute (CSIR-NBRI), Rana Pratap Marg, Lucknow, 226 001, India. mh.asif@nbri.res.in.|Council of Scientific and Industrial Research, National Botanical Research Institute (CSIR-NBRI), Rana Pratap Marg, Lucknow, 226 001, India. prabodht@nbri.res.in.|Council of Scientific and Industrial Research, National Botanical Research Institute (CSIR-NBRI), Rana Pratap Marg, Lucknow, 226 001, India. pratibhaflora@yahoo.com.', 'India|India|India|India|India|India|India|India', 8, 'Amino Acid Sequence|Catalytic Domain|Glycosyltransferases|Molecular Docking Simulation|Molecular Sequence Data|Protein Conformation|Sequence Homology, Amino Acid|Sterols|Substrate Specificity|Withania|Withanolides', 'Comparative Study', '10.1186/s12859-015-0563-7', '25888493', 'Sterol glycosyltransferases (SGTs) are ubiquitous but one of the most diverse group of enzymes of glycosyltransferases family. Members of this family modulate physical and chemical properties of secondary plant products important for various physiological processes. The role of SGTs has been demonstrated in the biosynthesis of pharmaceutically important molecules of medicinal plants like Withania somnifera.'),
(96672, 2015, 'bmc', 'Quantifying conformational changes in GPCRs: glimpse of a common functional mechanism', 'Dalton, James A R|Lans, Isaias|Giraldo, Jesús', 'Laboratory of Molecular Neuropharmacology and Bioinformatics, Institut de Neurociències and Unitat de Bioestadística, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain. james.dalton@uab.es.|Laboratory of Molecular Neuropharmacology and Bioinformatics, Institut de Neurociències and Unitat de Bioestadística, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain. isaias.lans@uab.es.|Laboratory of Molecular Neuropharmacology and Bioinformatics, Institut de Neurociències and Unitat de Bioestadística, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain. jesus.giraldo@uab.es.', 'Spain|Spain|Spain', 27, 'Adrenergic beta-2 Receptor Agonists|Adrenergic beta-2 Receptor Antagonists|Binding Sites|Catalytic Domain|Computer Simulation|Humans|Hydrogen Bonding|Ligands|Models, Molecular|Protein Binding|Protein Conformation|Receptors, Adrenergic, beta-2|Receptors, G-Protein-Coupled', 'Journal Article', '10.1186/s12859-015-0567-3', '25902715', 'G-protein-coupled receptors (GPCRs) are important drug targets and a better understanding of their molecular mechanisms would be desirable. The crystallization rate of GPCRs has accelerated in recent years as techniques have become more sophisticated, particularly with respect to Class A GPCRs interacting with G-proteins. These developments have made it possible for a quantitative analysis of GPCR geometrical features and binding-site conformations, including a statistical comparison between Class A GPCRs in active (agonist-bound) and inactive (antagonist-bound) states.'),
(96673, 2015, 'bmc', 'DOCKSCORE: a webserver for ranking protein-protein docked poses', 'Malhotra, Sony|Mathew, Oommen K|Sowdhamini, Ramanathan', 'National Centre for Biological Sciences (TIFR), UAS-GKVK Campus, Bellary Road, Bangalore, 560 065, India. sonym@ncbs.res.in.|National Centre for Biological Sciences (TIFR), UAS-GKVK Campus, Bellary Road, Bangalore, 560 065, India. oommenkm@ncbs.res.in.|National Centre for Biological Sciences (TIFR), UAS-GKVK Campus, Bellary Road, Bangalore, 560 065, India. mini@ncbs.res.in.', 'India|India|India', 11, 'Algorithms|Humans|Internet|Molecular Docking Simulation|Protein Binding|Protein Interaction Domains and Motifs|Proteins|Software|ras GTPase-Activating Proteins', 'Journal Article', '10.1186/s12859-015-0572-6', '25902779', 'Proteins interact with a variety of other molecules such as nucleic acids, small molecules and other proteins inside the cell. Structure-determination of protein-protein complexes is challenging due to several reasons such as the large molecular weights of these macromolecular complexes, their dynamic nature, difficulty in purification and sample preparation. Computational docking permits an early understanding of the feasibility and mode of protein-protein interactions. However, docking algorithms propose a number of solutions and it is a challenging task to select the native or near native pose(s) from this pool. DockScore is an objective scoring scheme that can be used to rank protein-protein docked poses. It considers several interface parameters, namely, surface area, evolutionary conservation, hydrophobicity, short contacts and spatial clustering at the interface for scoring.'),
(96674, 2015, 'bmc', 'SomInaClust: detection of cancer genes based on somatic mutation patterns of inactivation and clustering', 'Van den Eynden, Jimmy|Fierro, Ana Carolina|Verbeke, Lieven P C|Marchal, Kathleen', 'Department of Information Technology, Ghent University - iMinds, Ghent, Belgium. jimmy.vandeneynden@intec.ugent.be.|Department of Information Technology, Ghent University - iMinds, Ghent, Belgium. carolina.fierro@intec.ugent.be.|Department of Information Technology, Ghent University - iMinds, Ghent, Belgium. lieven.verbeke@intec.ugent.be.|Department of Information Technology, Ghent University - iMinds, Ghent, Belgium. kathleen.marchal@intec.ugent.be.', 'Belgium|Belgium|Belgium|Belgium', 19, 'Cluster Analysis|Genes, Tumor Suppressor|Humans|Mutation|Neoplasms|Oncogenes|Software', 'Journal Article', '10.1186/s12859-015-0555-7', '25903787', 'With the advances in high throughput technologies, increasing amounts of cancer somatic mutation data are being generated and made available. Only a small number of (driver) mutations occur in driver genes and are responsible for carcinogenesis, while the majority of (passenger) mutations do not influence tumour biology. In this study, SomInaClust is introduced, a method that accurately identifies driver genes based on their mutation pattern across tumour samples and then classifies them into oncogenes or tumour suppressor genes respectively.'),
(96675, 2015, 'bmc', 'KaBOB: ontology-based semantic integration of biomedical databases', 'Livingston, Kevin M|Bada, Michael|Baumgartner, William A|Hunter, Lawrence E', 'Computational Bioscience Program, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. Kevin.Livingston@ucdenver.edu.|Computational Bioscience Program, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. Mike.Bada@ucdenver.edu.|Computational Bioscience Program, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. William.Baumgartner@ucdenver.edu.|Computational Bioscience Program, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. Larry.Hunter@ucdenver.edu.', 'United States|United States|United States|United States', 35, 'Biological Ontologies|Biomedical Research|Computational Biology|Data Collection|Databases, Factual|Humans|Information Storage and Retrieval|Internet|Knowledge Bases|PubMed|Semantics', 'Journal Article', '10.1186/s12859-015-0559-3', '25903923', 'The ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources.'),
(96676, 2015, 'bmc', 'Grammar-based compression approach to extraction of common rules among multiple trees of glycans and RNAs', 'Zhao, Yang|Hayashida, Morihiro|Cao, Yue|Hwang, Jaewook|Akutsu, Tatsuya', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan. tyoyo@kuicr.kyoto-u.ac.jp.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan. morihiro@kuicr.kyoto-u.ac.jp.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan. caoyue@kuicr.kyoto-u.ac.jp.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan. hwangjw@kuicr.kyoto-u.ac.jp.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan. takutsu@kuicr.kyoto-u.ac.jp.', 'Japan|Japan|Japan|Japan|Japan', 2, 'Algorithms|Computational Biology|Data Compression|Humans|Polysaccharides|RNA', 'Journal Article', '10.1186/s12859-015-0558-4', '25907438', 'Many tree structures are found in nature and organisms. Such trees are believed to be constructed on the basis of certain rules. We have previously developed grammar-based compression methods for ordered and unordered single trees, based on bisection-type tree grammars. Here, these methods find construction rules for one single tree. On the other hand, specified construction rules can be utilized to generate multiple similar trees.'),
(96677, 2015, 'bmc', 'Structured learning for spatial information extraction from biomedical text: bacteria biotopes', 'Kordjamshidi, Parisa|Roth, Dan|Moens, Marie-Francine', 'KULeuven, Leuven, Belgium. kordjam@illinois.edu.|University of Illinois at Urbana-Champaign, Urbana-Champaign, USA. danr@illinois.edu.|KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.', 'Belgium|United States|Belgium', 15, 'Artificial Intelligence|Bacteria|Data Mining|Databases, Factual|Information Storage and Retrieval|Language|Models, Theoretical|Natural Language Processing|Periodicals as Topic', 'Journal Article', '10.1186/s12859-015-0542-z', '25909637', 'We aim to automatically extract species names of bacteria and their locations from webpages. This task is important for exploiting the vast amount of biological knowledge which is expressed in diverse natural language texts and putting this knowledge in databases for easy access by biologists. The task is challenging and the previous results are far below an acceptable level of performance, particularly for extraction of localization relationships. Therefore, we aim to design a new system for such extractions, using the framework of structured machine learning techniques.'),
(96678, 2015, 'bmc', 'Sparse conditional logistic regression for analyzing large-scale matched data from epidemiological studies: a simple algorithm', 'Avalos, Marta|Pouyes, Hélène|Grandvalet, Yves|Orriols, Ludivine|Lagarde, Emmanuel', 'KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.|KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.|KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.|KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.|KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.', 'Belgium|Belgium|Belgium|Belgium|Belgium', 10, 'Adolescent|Adult|Age Factors|Aged|Aged, 80 and over|Algorithms|Case-Control Studies|Humans|Likelihood Functions|Logistic Models|Middle Aged|Models, Theoretical|Molecular Epidemiology|Regression Analysis|Sample Size|Young Adult', 'Comparative Study', '10.1186/1471-2105-16-S6-S1', '25916593', 'This paper considers the problem of estimation and variable selection for large high-dimensional data (high number of predictors p and large sample size N, without excluding the possibility that N < p) resulting from an individually matched case-control study. We develop a simple algorithm for the adaptation of the Lasso and related methods to the conditional logistic regression model. Our proposal relies on the simplification of the calculations involved in the likelihood function. Then, the proposed algorithm iteratively solves reweighted Lasso problems using cyclical coordinate descent, computed along a regularization path. This method can handle large problems and deal with sparse features efficiently. We discuss benefits and drawbacks with respect to the existing available implementations. We also illustrate the interest and use of these techniques on a pharmacoepidemiological study of medication use and traffic safety. '),
(96679, 2015, 'bmc', 'Probabilistic topic modeling for the analysis and classification of genomic sequences', 'La Rosa, Massimo|Fiannaca, Antonino|Rizzo, Riccardo|Urso, Alfonso', 'KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.|KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.|KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.|KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.', 'Belgium|Belgium|Belgium|Belgium', 27, 'Algorithms|Bacteria|Genome, Bacterial|Genomics|Models, Statistical|Sequence Alignment|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-16-S6-S2', '25916734', 'Studies on genomic sequences for classification and taxonomic identification have a leading role in the biomedical field and in the analysis of biodiversity. These studies are focusing on the so-called barcode genes, representing a well defined region of the whole genome. Recently, alignment-free techniques are gaining more importance because they are able to overcome the drawbacks of sequence alignment techniques. In this paper a new alignment-free method for DNA sequences clustering and classification is proposed. The method is based on k-mers representation and text mining techniques.'),
(96680, 2015, 'bmc', 'Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins', 'Ashtawy, Hossam M|Mahapatra, Nihar R', 'KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.|KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.', 'Belgium|Belgium', 19, 'Artificial Intelligence|Binding Sites|Drug Design|Drug Discovery|Humans|Ligands|Protein Binding|Proteins|Software', 'Journal Article', '10.1186/1471-2105-16-S6-S3', '25916860', 'Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor proteins binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets.'),
(96681, 2015, 'bmc', 'Computational algorithms to predict Gene Ontology annotations', 'Pinoli, Pietro|Chicco, Davide|Masseroli, Marco', 'KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.|KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.|KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.', 'Belgium|Belgium|Belgium', 17, 'Algorithms|Animals|Cluster Analysis|Computational Biology|Drosophila Proteins|Drosophila melanogaster|Gene Ontology|Molecular Sequence Annotation', 'Journal Article', '10.1186/1471-2105-16-S6-S4', '25916950', 'Gene function annotations, which are associations between a gene and a term of a controlled vocabulary describing gene functional features, are of paramount importance in modern biology. Datasets of these annotations, such as the ones provided by the Gene Ontology Consortium, are used to design novel biological experiments and interpret their results. Despite their importance, these sources of information have some known issues. They are incomplete, since biological knowledge is far from being definitive and it rapidly evolves, and some erroneous annotations may be present. Since the curation process of novel annotations is a costly procedure, both in economical and time terms, computational tools that can reliably predict likely annotations, and thus quicken the discovery of new gene annotations, are very useful.'),
(96682, 2015, 'bmc', 'Inferring slowly-changing dynamic gene-regulatory networks', 'Wit, Ernst C|Abbruzzo, Antonino', 'KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.|KULeuven, Leuven, Belgium. Sien.Moens@cs.kuleuven.be.', 'Belgium|Belgium', 6, 'Algorithms|Computer Simulation|Gene Regulatory Networks|Humans|Lymphocyte Activation|Microarray Analysis|Models, Statistical|T-Lymphocytes', 'Journal Article', '10.1186/1471-2105-16-S6-S5', '25917062', 'Dynamic gene-regulatory networks are complex since the interaction patterns between their components mean that it is impossible to study parts of the network in separation. This holistic character of gene-regulatory networks poses a real challenge to any type of modelling. Graphical models are a class of models that connect the network with a conditional independence relationships between random variables. By interpreting these random variables as gene activities and the conditional independence relationships as functional non-relatedness, graphical models have been used to describe gene-regulatory networks. Whereas the literature has been focused on static networks, most time-course experiments are designed in order to tease out temporal changes in the underlying network. It is typically reasonable to assume that changes in genomic networks are few, because biological systems tend to be stable. We introduce a new model for estimating slow changes in dynamic gene-regulatory networks, which is suitable for high-dimensional data, e.g. time-course microarray data. Our aim is to estimate a dynamically changing genomic network based on temporal activity measurements of the genes in the network. Our method is based on the penalized likelihood with l1-norm, that penalizes conditional dependencies between genes as well as differences between conditional independence elements across time points. We also present a heuristic search strategy to find optimal tuning parameters. We re-write the penalized maximum likelihood problem into a standard convex optimization problem subject to linear equality constraints. We show that our method performs well in simulation studies. Finally, we apply the proposed model to a time-course T-cell dataset.'),
(96683, 2015, 'bmc', 'UrQt: an efficient software for the Unsupervised Quality trimming of NGS data', 'Modolo, Laurent|Lerat, Emmanuelle', 'Université de Lyon, Université Lyon 1, CNRS, UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, 43 bd du 11 novembre 1918, Villeurbanne cedex, 69622, France. laurent.modolo@univ-lyon1.fr.|Université de Lyon, Université Lyon 1, CNRS, UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, 43 bd du 11 novembre 1918, Villeurbanne cedex, 69622, France. emmanuelle.lerat@univ-lyon1.fr.', 'France|France', 22, 'Computational Biology|High-Throughput Nucleotide Sequencing|Humans|Quality Control|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/s12859-015-0546-8', '25924884', 'Quality control is a necessary step of any Next Generation Sequencing analysis. Although customary, this step still requires manual interventions to empirically choose tuning parameters according to various quality statistics. Moreover, current quality control procedures that provide a good quality data set, are not optimal and discard many informative nucleotides. To address these drawbacks, we present a new quality control method, implemented in UrQt software, for Unsupervised Quality trimming of Next Generation Sequencing reads.'),
(96684, 2015, 'bmc', 'plethy: management of whole body plethysmography data in R', 'Bottomly, Daniel|Wilmot, Beth|McWeeney, Shannon K', 'Oregon Clinical and Translational Research Institute, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd97239, Portland, Oregon, US. bottomly@ohsu.edu.|Oregon Clinical and Translational Research Institute, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd97239, Portland, Oregon, US. wilmotb@ohsu.edu.|Oregon Clinical and Translational Research Institute, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd97239, Portland, Oregon, US. mcweeney@ohsu.edu.', '-|-|-', 0, 'Animals|Birds|Computer Graphics|Coronavirus|Genome, Viral|Genomics|Influenza A virus|Influenza in Birds|Mice|Mice, Inbred C57BL|Models, Statistical|Orthomyxoviridae Infections|Phenotype|Plethysmography, Whole Body|Respiration|Severe Acute Respiratory Syndrome|Software', 'Journal Article', '10.1186/s12859-015-0547-7', '25924931', 'Characterization of respiratory phenotypes can enhance complex trait and genomic studies involving allergic/autoimmune and infectious diseases. Many aspects of respiration can be measured using devices known as plethysmographs that can measure thoracic movement. One such approach (the Buxco platform) performs unrestrained whole body plethysmography on mice which infers thoracic movements from pressure differences from the act of inhalation and exhalation. While proprietary software is available to perform basic statistical analysis as part of machines bundled software, it is desirable to be able to incorporate these analyses into high-throughput pipelines and integrate them with other data types, as well as leverage the wealth of analytic and visualization approaches provided by the R statistical computing environment.'),
(96685, 2015, 'bmc', 'Visual analysis of biological data-knowledge networks', 'Vehlow, Corinna|Kao, David P|Bristow, Michael R|Hunter, Lawrence E|Weiskopf, Daniel|Gxc3xb6rg, Carsten', 'VISUS, University of Stuttgart, Allmandring 19, Stuttgart, Germany. corinna.vehlow@visus.uni-stuttgart.de.|School of Medicine, University of Colorado, E 17th Pl, Aurora, CO, USA. david.kao@ucdenver.edu.|School of Medicine, University of Colorado, E 17th Pl, Aurora, CO, USA. michael.bristow@ucdenver.edu.|School of Medicine, University of Colorado, E 17th Pl, Aurora, CO, USA. larry.hunter@ucdenver.edu.|VISUS, University of Stuttgart, Allmandring 19, Stuttgart, Germany. daniel.weiskopf@visus.uni-stuttgart.de.|School of Medicine, University of Colorado, E 17th Pl, Aurora, CO, USA. carsten.goerg@ucdenver.edu.', 'Germany|United States|United States|United States|Germany|United States', 22, 'Adrenergic beta-Antagonists|Cholesterol|Cholesterol Ester Transfer Proteins|Computer Graphics|Data Mining|Databases, Factual|Gene Expression Profiling|Gene Regulatory Networks|Heart Failure|Humans|Software', 'Journal Article', '10.1186/s12859-015-0550-z', '25925016', 'The interpretation of the results from genome-scale experiments is a challenging and important problem in contemporary biomedical research. Biological networks that integrate experimental results with existing knowledge from biomedical databases and published literature can provide a rich resource and powerful basis for hypothesizing about mechanistic explanations for observed gene-phenotype relationships. However, the size and density of such networks often impede their efficient exploration and understanding.'),
(96686, 2015, 'bmc', 'An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition', 'Tsatsaronis, George|Balikas, Georgios|Malakasiotis, Prodromos|Partalas, Ioannis|Zschunke, Matthias|Alvers, Michael R|Weissenborn, Dirk|Krithara, Anastasia|Petridis, Sergios|Polychronopoulos, Dimitris|Almirantis, Yannis|Pavlopoulos, John|Baskiotis, Nicolas|Gallinari, Patrick|Artiéres, Thierry|Ngomo, Axel-Cyrille Ngonga|Heino, Norman|Gaussier, Eric|Barrio-Alvers, Liliana|Schroeder, Michael|Androutsopoulos, Ion|Paliouras, Georgios', 'Biotechnology Center, TU Dresden, 01307, Tatzberg 47-49, Dresden, Germany. george.tsatsaronis@biotec.tu-dresden.de.|Université Pierre et Marie Curie-Paris 6, 4 Place Jussieu, Paris, 75005, France. georgios.balikas@imag.fr.|Athens University of Economics and Business, Patission 76, Athens, 10434, Greece. rulller@gmail.com.|Université Joseph Fourier, 621 Avenue Centrale, Saint-Martin-dHéres, 38041, France. ioannis.partalas@imag.fr.|Transinsight GmbH, Tatzberg 47-49, Dresden, 01307, Germany. mzschunke@transinsight.com.|Transinsight GmbH, Tatzberg 47-49, Dresden, 01307, Germany. malvers@transinsight.com.|Biotechnology Center, TU Dresden, 01307, Tatzberg 47-49, Dresden, Germany. dirk.weissenborn@gmail.com.|NCSR Demokritos, Ag. Paraskevi, Athens, 60228, Greece. akrithara@iit.demokritos.gr.|NCSR Demokritos, Ag. Paraskevi, Athens, 60228, Greece. eserxio@gmail.com.|NCSR Demokritos, Ag. Paraskevi, Athens, 60228, Greece. dpolychr@gmail.com.|NCSR Demokritos, Ag. Paraskevi, Athens, 60228, Greece. yalmir@bio.demokritos.gr.|Athens University of Economics and Business, Patission 76, Athens, 10434, Greece. annis@aueb.gr.|Université Pierre et Marie Curie-Paris 6, 4 Place Jussieu, Paris, 75005, France. nicolas.baskiotis@lip6.fr.|Université Pierre et Marie Curie-Paris 6, 4 Place Jussieu, Paris, 75005, France. Patrick.Gallinari@lip6.fr.|Université Pierre et Marie Curie-Paris 6, 4 Place Jussieu, Paris, 75005, France. thierry.artieres@lip6.fr.|Universität Leipzig, Augustusplatz 10, 04109, Leipzig, Germany. axel.ngonga@gmail.com.|Universität Leipzig, Augustusplatz 10, 04109, Leipzig, Germany. heino@informatik.uni-leipzig.de.|Université Joseph Fourier, 621 Avenue Centrale, Saint-Martin-dHéres, 38041, France. eric.gaussier@imag.fr.|Transinsight GmbH, Tatzberg 47-49, Dresden, 01307, Germany. lalvers@transinsight.com.|Biotechnology Center, TU Dresden, 01307, Tatzberg 47-49, Dresden, Germany. ms@biotec.tu-dresden.de.|Athens University of Economics and Business, Patission 76, Athens, 10434, Greece. ion@aueb.gr.|NCSR Demokritos, Ag. Paraskevi, Athens, 60228, Greece. paliourg@iit.demokritos.gr.', 'Germany|France|Greece|France|Germany|Germany|Germany|Greece|Greece|Greece|Greece|Greece|France|Franc', 105, 'Abstracting and Indexing as Topic|Algorithms|Humans|Medical Subject Headings|National Library of Medicine (U.S.)|Natural Language Processing|PubMed|Semantics|Software|United States', 'Journal Article', '10.1186/s12859-015-0564-6', '25925131', 'This article provides an overview of the first BIOASQ challenge, a competition on large-scale biomedical semantic indexing and question answering (QA), which took place between March and September 2013. BIOASQ assesses the ability of systems to semantically index very large numbers of biomedical scientific articles, and to return concise and user-understandable answers to given natural language questions by combining information from biomedical articles and ontologies.'),
(96687, 2015, 'bmc', 'Principal component analysis-based unsupervised feature extraction applied to in silico drug discovery for posttraumatic stress disorder-mediated heart disease', 'Taguchi, Y-h|Iwadate, Mitsuo|Umeyama, Hideaki', 'Department of Physics, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo, 112-8551, Japan. tag@granular.com.|Department of Biological Science, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo, 112-8551, Japan. iwadate@bio.chuo-u.ac.jp.|Department of Biological Science, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo, 112-8551, Japan. umeyama@bio.chuo-u.ac.jp.', 'Japan|Japan|Japan', 0, 'Algorithms|Animals|Bayes Theorem|Biomarkers|Computational Biology|Computer Simulation|Data Mining|Drug Discovery|Gene Expression Profiling|Gene Expression Regulation|Heart Diseases|Mice|MicroRNAs|Principal Component Analysis|RNA, Messenger|Stress Disorders, Post-Traumatic', 'Journal Article', '10.1186/s12859-015-0574-4', '25925353', 'Feature extraction (FE) is difficult, particularly if there are more features than samples, as small sample numbers often result in biased outcomes or overfitting. Furthermore, multiple sample classes often complicate FE because evaluating performance, which is usual in supervised FE, is generally harder than the two-class problem. Developing sample classification independent unsupervised methods would solve many of these problems.'),
(96688, 2015, 'bmc', 'Customised fragments libraries for protein structure prediction based on structural class annotations', 'Abbass, Jad|Nebel, Jean-Christophe', 'Faculty of Science, Engineering and Computing, Kingston University, London, KT1 2EE, UK. k1064285@kingston.ac.uk.|Faculty of Science, Engineering and Computing, Kingston University, London, KT1 2EE, UK. j.nebel@kingston.ac.uk.', 'United Kingdom|United Kingdom', 14, 'Algorithms|Computer Simulation|Databases, Protein|Humans|Peptide Fragments|Peptide Library|Proteins|Software', 'Journal Article', '10.1186/s12859-015-0576-2', '25925397', 'Since experimental techniques are time and cost consuming, in silico protein structure prediction is essential to produce conformations of protein targets. When homologous structures are not available, fragment-based protein structure prediction has become the approach of choice. However, it still has many issues including poor performance when targets lengths are above 100 residues, excessive running times and sub-optimal energy functions. Taking advantage of the reliable performance of structural class prediction software, we propose to address some of the limitations of fragment-based methods by integrating structural constraints in their fragment selection process.'),
(96689, 2014, 'bmc', 'Abstracts of the Thirteenth Annual UT- KBRIN Bioinformatics Summit 2014, April 11-13, 2014, Cadiz, Kentucky', '-', '-', '-', 14, 'Animals|Computational Biology|Genomics|Humans', 'Congress', '10.1186/s12859-015-0576-2', '25927095', '-'),
(96690, 2015, 'bmc', 'Optimally choosing PWM motif databases and sequence scanning approaches based on ChIP-seq data', 'Dabrowski, Michal|Dojer, Norbert|Krystkowiak, Izabella|Kaminska, Bozena|Wilczynski, Bartek', 'Laboratory of Bioinformatics, Nencki Institute of Experimental Biology, Pasteura 3, Warszawa, 02-093, Poland. m.dabrowski@nencki.gov.pl.|Institute of Informatics, Univeristy of Warsaw, Banacha 2, Warszawa, 02-097, Poland. dojer@mimuw.edu.pl.|Laboratory of Molecular Neurobiology, Nencki Institute of Experimental Biology, Pasteura 3, Warszawa, 02-093, Poland. i.krystkowiak@nencki.gov.pl.|Laboratory of Molecular Neurobiology, Nencki Institute of Experimental Biology, Pasteura 3, Warszawa, 02-093, Poland. b.kaminska@nencki.gov.pl.|Institute of Informatics, Univeristy of Warsaw, Banacha 2, Warszawa, 02-097, Poland. bartek@mimuw.edu.pl.', 'Poland|Poland|Poland|Poland|Poland', 0, 'Binding Sites|Chromatin Immunoprecipitation|Computational Biology|Databases, Factual|Genome, Human|Humans|Nucleotide Motifs|Position-Specific Scoring Matrices|Protein Binding|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1186/s12859-015-0573-5', '25927199', 'For many years now, binding preferences of Transcription Factors have been described by so called motifs, usually mathematically defined by position weight matrices or similar models, for the purpose of predicting potential binding sites. However, despite the availability of thousands of motif models in public and commercial databases, a researcher who wants to use them is left with many competing methods of identifying potential binding sites in a genome of interest and there is little published information regarding the optimality of different choices. Thanks to the availability of large number of different motif models as well as a number of experimental datasets describing actual binding of TFs in hundreds of TF-ChIP-seq pairs, we set out to perform a comprehensive analysis of this matter.'),
(96691, 2015, 'bmc', 'Secondary structural entropy in RNA switch (Riboswitch) identification', 'Manzourolajdad, Amirhossein|Arnold, Jonathan', 'Institute of Bioinformatics, University of Georgia, Davison Life Sciences Bldg, Room B118B, 120 Green St, Athens, 30602, USA. amanzour@uga.edu.|Institute of Bioinformatics, University of Georgia, Davison Life Sciences Bldg, Room B118B, 120 Green St, Athens, 30602, USA. arnold@uga.edu.', 'Georgia|Georgia', 11, 'Bacillus subtilis|Base Pairing|Base Sequence|Binding Sites|Computational Biology|Entropy|Escherichia coli|Molecular Sequence Data|Nucleic Acid Conformation|RNA, Bacterial|Regulatory Sequences, Nucleic Acid|Ribosomes|Riboswitch|Software|Synechococcus', 'Journal Article', '10.1186/s12859-015-0523-2', '25928324', 'RNA regulatory elements play a significant role in gene regulation. Riboswitches, a widespread group of regulatory RNAs, are vital components of many bacterial genomes. These regulatory elements generally function by forming a ligand-induced alternative fold that controls access to ribosome binding sites or other regulatory sites in RNA. Riboswitch-mediated mechanisms are ubiquitous across bacterial genomes. A typical class of riboswitch has its own unique structural and biological complexity, making de novo riboswitch identification a formidable task. Traditionally, riboswitches have been identified through comparative genomics based on sequence and structural homology. The limitations of structural-homology-based approaches, coupled with the assumption that there is a great diversity of undiscovered riboswitches, suggests the need for alternative methods for riboswitch identification, possibly based on features intrinsic to their structure. As of yet, no such reliable method has been proposed.'),
(96692, 2015, 'bmc', 'PaPI: pseudo amino acid composition to score human protein-coding variants', 'Limongelli, Ivan|Marini, Simone|Bellazzi, Riccardo', 'IRCCS Policlinico S. Matteo, Pzz.le Volontari del Sangue 2, 27100, Pavia, Italy. ivan.limongelli@unipv.it.|Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Via Ferrata 1, 27100, Pavia, Italy. simone.marini@unipv.it.|Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Via Ferrata 1, 27100, Pavia, Italy. riccardo.bellazzi@unipv.it.', 'Italy|Italy|Italy', 19, 'Algorithms|Amino Acids|Artificial Intelligence|Exome|Genetic Variation|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Proteins|Software', 'Journal Article', '10.1186/s12859-015-0554-8', '25928477', 'High throughput sequencing technologies are able to identify the whole genomic variation of an individual. Gene-targeted and whole-exome experiments are mainly focused on coding sequence variants related to a single or multiple nucleotides. The analysis of the biological significance of this multitude of genomic variant is challenging and computational demanding.'),
(96693, 2015, 'bmc', 'ContextMap 2: fast and accurate context-based RNA-seq mapping', 'Bonfert, Thomas|Kirner, Evelyn|Csaba, Gergely|Zimmer, Ralf|Friedel, Caroline C', 'Institute for Informatics, Ludwig-Maximilians-Universität München, Amalienstr. 17, Munich, 80333, Germany. thomas.bonfert@bio.ifi.lmu.de.|Institute for Informatics, Ludwig-Maximilians-Universität München, Amalienstr. 17, Munich, 80333, Germany. evelyn.kirner@campus.lmu.de.|Institute for Informatics, Ludwig-Maximilians-Universität München, Amalienstr. 17, Munich, 80333, Germany. gergely.csaba@bio.ifi.lmu.de.|Institute for Informatics, Ludwig-Maximilians-Universität München, Amalienstr. 17, Munich, 80333, Germany. ralf.zimmer@bio.ifi.lmu.de.|Institute for Informatics, Ludwig-Maximilians-Universität München, Amalienstr. 17, Munich, 80333, Germany. caroline.friedel@bio.ifi.lmu.de.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Exons|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|INDEL Mutation|RNA, Messenger|Sequence Analysis, RNA|Transcriptome', 'Journal Article', '10.1186/s12859-015-0557-5', '25928589', 'Mapping of short sequencing reads is a crucial step in the analysis of RNA sequencing (RNA-seq) data. ContextMap is an RNA-seq mapping algorithm that uses a context-based approach to identify the best alignment for each read and allows parallel mapping against several reference genomes.'),
(96694, 2015, 'bmc', 'Elviz - exploration of metagenome assemblies with an interactive visualization tool', 'Cantor, Michael|Nordberg, Henrik|Smirnova, Tatyana|Hess, Matthias|Tringe, Susannah|Dubchak, Inna', 'Department of Energy, Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA, 94598, USA. mncantor@lbl.gov.|Department of Energy, Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA, 94598, USA. henrik.p.nordberg@gmail.com.|Department of Energy, Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA, 94598, USA. tsmirnova@lbl.gov.|University of California at Davis, One Shields Avenue, Davis, CA, 95616-8521, USA. mhess@ucdavis.edu.|Department of Energy, Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA, 94598, USA. sgtringe@lbl.gov.|Department of Energy, Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA, 94598, USA. ildubchak@lbl.gov.', 'United States|United States|United States|United States|United States|United States', 6, 'Computational Biology|Computer Graphics|Databases, Genetic|Genome, Bacterial|Metagenome|Metagenomics|Molecular Sequence Annotation|Petroleum|Phylogeny|Software', 'Journal Article', '10.1186/s12859-015-0566-4', '25928663', 'Metagenomics, the sequencing of DNA collected from an entire microbial community, enables the study of natural microbial consortia in their native habitats. Metagenomics studies produce huge volumes of data, including both the sequences themselves and metadata describing their abundance, assembly, predicted functional characteristics and environmental parameters. The ability to explore these data visually is critically important to meaningful biological interpretation. Current genomics applications cannot effectively integrate sequence data, assembly metadata, and annotation to support both genome and community-level inquiry.'),
(96695, 2015, 'bmc', 'coMET: visualisation of regional epigenome-wide association scan results and DNA co-methylation patterns', 'Martin, Tiphaine C|Yet, Idil|Tsai, Pei-Chien|Bell, Jordana T', 'Department of Twin Research and Genetic Epidemiology, St Thomas Hospital Campus, Kings College London, Westminster Bridge Road, London, UK. tiphaine.martin@kcl.ac.uk.|Department of Twin Research and Genetic Epidemiology, St Thomas Hospital Campus, Kings College London, Westminster Bridge Road, London, UK. idil.erte@kcl.ac.uk.|Department of Twin Research and Genetic Epidemiology, St Thomas Hospital Campus, Kings College London, Westminster Bridge Road, London, UK. pei-chien.tsai@kcl.ac.uk.|Department of Twin Research and Genetic Epidemiology, St Thomas Hospital Campus, Kings College London, Westminster Bridge Road, London, UK. jordana.bell@kcl.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computer Graphics|CpG Islands|DNA|DNA Methylation|Epigenesis, Genetic|Humans|Phenotype|Software', 'Journal Article', '10.1186/s12859-015-0568-2', '25928765', 'Epigenome-wide association scans (EWAS) are an increasingly powerful and widely-used approach to assess the role of epigenetic variation in human complex traits. However, this rapidly emerging field lacks dedicated visualisation tools that can display features specific to epigenetic datasets.'),
(96696, 2015, 'bmc', 'Moment based gene set tests', 'Larson, Jessica L|Owen, Art B', 'Department of Bioinformatics and Computational Biology, Genentech, Inc., South San Francisco, USA. larson.jess@gmail.com.|Department of Statistics, Stanford University, Stanford, USA. owen@stanford.edu.', 'United States|United States', 0, 'Algorithms|Biomarkers|Data Interpretation, Statistical|Gene Expression Profiling|Genomics|Humans|Models, Statistical|Parkinson Disease', 'Journal Article', '10.1186/s12859-015-0571-7', '25928861', 'Permutation-based gene set tests are standard approaches for testing relationships between collections of related genes and an outcome of interest in high throughput expression analyses. Using M random permutations, one can attain p-values as small as 1/(M+1). When many gene sets are tested, we need smaller p-values, hence larger M, to achieve significance while accounting for the number of simultaneous tests being made. As a result, the number of permutations to be done rises along with the cost per permutation. To reduce this cost, we seek parametric approximations to the permutation distributions for gene set tests.'),
(96697, 2015, 'bmc', 'VISIONET: intuitive visualisation of overlapping transcription factor networks, with applications in cardiogenic gene discovery', 'Nim, Hieu T|Furtado, Milena B|Costa, Mauro W|Rosenthal, Nadia A|Kitano, Hiroaki|Boyd, Sarah E', 'Systems Biology Institute (SBI) Australia, Monash University, Clayton, VIC, 3800, Australia. hieu.nim@monash.edu.|Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, 3800, Australia. milena.furtado@monash.edu.|Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, 3800, Australia. mauro.dacosta@monash.edu.|Systems Biology Institute (SBI) Australia, Monash University, Clayton, VIC, 3800, Australia. nadia.rosenthal@monash.edu.|Systems Biology Institute (SBI) Australia, Monash University, Clayton, VIC, 3800, Australia. kitano@sbi.jp.|Systems Biology Institute (SBI) Australia, Monash University, Clayton, VIC, 3800, Australia. sarah.boyd@monash.edu.', 'Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Adult|Cells, Cultured|Computer Graphics|Fibroblasts|GATA4 Transcription Factor|Gene Expression Regulation, Developmental|Gene Regulatory Networks|Genetic Association Studies|Heart|Humans|Software|T-Box Domain Proteins|Transcription Factors', 'Journal Article', '10.1186/s12859-015-0578-0', '25929466', 'Existing de novo software platforms have largely overlooked a valuable resource, the expertise of the intended biologist users. Typical data representations such as long gene lists, or highly dense and overlapping transcription factor networks often hinder biologists from relating these results to their expertise.'),
(96698, 2015, 'bmc', 'Pydna: a simulation and documentation tool for DNA assembly strategies using python', 'Pereira, Filipa|Azevedo, Flávio|Carvalho, Ângela|Ribeiro, Gabriela F|Budde, Mark W|Johansson, Björn', 'CBMA, Campus de Gualtar, University of Minho, Braga, Portugal. filipaabpereira@gmail.com.|CBMA, Campus de Gualtar, University of Minho, Braga, Portugal. flaviodazevedo@gmail.com.|CBMA, Campus de Gualtar, University of Minho, Braga, Portugal. ang.mrcarvalho@gmail.com.|CBMA, Campus de Gualtar, University of Minho, Braga, Portugal. gabrielafribeiro@gmail.com.|Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA. markbudde@gmail.com.|CBMA, Campus de Gualtar, University of Minho, Braga, Portugal. bjorn_johansson@bio.uminho.pt.', 'Portugal|Portugal|Portugal|Portugal|United States|Portugal', 0, 'Computational Biology|Computer Simulation|Gene Library|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software|Synthetic Biology', 'Journal Article', '10.1186/s12859-015-0544-x', '25933606', 'Recent advances in synthetic biology have provided tools to efficiently construct complex DNA molecules which are an important part of many molecular biology and biotechnology projects. The planning of such constructs has traditionally been done manually using a DNA sequence editor which becomes error-prone as scale and complexity of the construction increase. A human-readable formal description of cloning and assembly strategies, which also allows for automatic computer simulation and verification, would therefore be a valuable tool.');
