INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(95742, 2013, 'bmc', 'Pathway-PDT: a flexible pathway analysis tool for nuclear families', 'Park, Yo Son|Schmidt, Michael|Martin, Eden R|Pericak-Vance, Margaret A|Chung, Ren-Hua', 'Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, Taiwan. rchung@nhri.org.tw.|Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, Taiwan. rchung@nhri.org.tw.|Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, Taiwan. rchung@nhri.org.tw.|Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, Taiwan. rchung@nhri.org.tw.|Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, Taiwan. rchung@nhri.org.tw.', '-|-|-|-|-', 0, 'Computational Biology|Genome-Wide Association Study|Genotype|Humans|Nuclear Family|Pedigree|Software', 'Journal Article', '10.1186/1471-2105-14-267', '24006871', 'Pathway analysis based on Genome-Wide Association Studies (GWAS) data has become popular as a secondary analysis strategy. Although many pathway analysis tools have been developed for case-control studies, there is no tool that can use all information from raw genotypes in general nuclear families. We developed Pathway-PDT, which uses the framework of Pedigree Disequilibrium Test (PDT) for general family data, to perform pathway analysis based on raw genotypes in family-based GWAS.'),
(95743, 2013, 'bmc', 'Maximum-parsimony haplotype frequencies inference based on a joint constrained sparse representation of pooled DNA', 'Jajamovich, Guido H|Iliadis, Alexandros|Anastassiou, Dimitris|Wang, Xiaodong', 'Electrical Engineering Department, Columbia University, New York NY 10027, USA. wangx@ee.columbia.edu.|Electrical Engineering Department, Columbia University, New York NY 10027, USA. wangx@ee.columbia.edu.|Electrical Engineering Department, Columbia University, New York NY 10027, USA. wangx@ee.columbia.edu.|Electrical Engineering Department, Columbia University, New York NY 10027, USA. wangx@ee.columbia.edu.', 'United States|United States|United States|United States', 2, 'Algorithms|DNA|Databases, Genetic|Gene Frequency|Genomics|HapMap Project|Haplotypes|Humans|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-14-270', '24010487', 'DNA pooling constitutes a cost effective alternative in genome wide association studies. In DNA pooling, equimolar amounts of DNA from different individuals are mixed into one sample and the frequency of each allele in each position is observed in a single genotype experiment. The identification of haplotype frequencies from pooled data in addition to single locus analysis is of separate interest within these studies as haplotypes could increase statistical power and provide additional insight.'),
(95744, 2013, 'bmc', 'Centroid based clustering of high throughput sequencing reads based on n-mer counts', 'Solovyov, Alexander|Lipkin, W Ian', 'Center for Infection and Immunity, Columbia University, New York, NY, 10032, USA. avs2132@columbia.edu.|Center for Infection and Immunity, Columbia University, New York, NY, 10032, USA. avs2132@columbia.edu.', 'United States|United States', 0, 'Algorithms|Cluster Analysis|Computational Biology|Databases, Genetic|High-Throughput Nucleotide Sequencing|Humans|Internet|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-14-268', '24011402', 'Many problems in computational biology require alignment-free sequence comparisons. One of the common tasks involving sequence comparison is sequence clustering. Here we apply methods of alignment-free comparison (in particular, comparison using sequence composition) to the challenge of sequence clustering.'),
(95745, 2013, 'bmc', 'Efficient alignment of RNA secondary structures using sparse dynamic programming', 'Zhong, Cuncong|Zhang, Shaojie', 'Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816-2362, USA. shzhang@eecs.ucf.edu.|Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816-2362, USA. shzhang@eecs.ucf.edu.', 'United States|United States', 0, 'Algorithms|Computational Biology|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-14-269', '24011432', 'Current advances of the next-generation sequencing technology have revealed a large number of un-annotated RNA transcripts. Comparative study of the RNA structurome is an important approach to assess their biological functionalities. Due to the large sizes and abundance of the RNA transcripts, an efficient and accurate RNA structure-structure alignment algorithm is in urgent need to facilitate the comparative study. Despite the importance of the RNA secondary structure alignment problem, there are no computational tools available that provide high computational efficiency and accuracy. In this case, designing and implementing such an efficient and accurate RNA secondary structure alignment algorithm is highly desirable.'),
(95746, 2013, 'bmc', 'MultiChIPmixHMM: an R package for ChIP-chip data analysis modeling spatial dependencies and multiple replicates', 'Bérard, Caroline|Seifert, Michael|Mary-Huard, Tristan|Martin-Magniette, Marie-Laure', 'INRA, UMR 518 MIA, F-75005 Paris, France. caroline.berard@univ-rouen.fr.|INRA, UMR 518 MIA, F-75005 Paris, France. caroline.berard@univ-rouen.fr.|INRA, UMR 518 MIA, F-75005 Paris, France. caroline.berard@univ-rouen.fr.|INRA, UMR 518 MIA, F-75005 Paris, France. caroline.berard@univ-rouen.fr.', 'France|France|France|France', 1, 'Arabidopsis|Chromatin Immunoprecipitation|Histones|Linear Models|Models, Genetic|Nucleic Acid Hybridization|Oligonucleotide Array Sequence Analysis|Plant Proteins', 'Journal Article', '10.1186/1471-2105-14-271', '24015679', 'Chromatin immunoprecipitation coupled with hybridization to a tiling array (ChIP-chip) is a cost-effective and routinely used method to identify protein-DNA interactions or chromatin/histone modifications. The robust identification of ChIP-enriched regions is frequently complicated by noisy measurements. This identification can be improved by accounting for dependencies between adjacent probes on chromosomes and by modeling of biological replicates.'),
(95747, 2013, 'bmc', 'Levenshtein error-correcting barcodes for multiplexed DNA sequencing', 'Buschmann, Tilo|Bystrykh, Leonid V', 'Institute for Medical Informatics and Biometry (IMB), Faculty of Medicine Carl Gustav Carus, Dresden University of Technology, Dresden, Germany. tilo.buschmann@tu-dresden.de.|Institute for Medical Informatics and Biometry (IMB), Faculty of Medicine Carl Gustav Carus, Dresden University of Technology, Dresden, Germany. tilo.buschmann@tu-dresden.de.', 'Germany|Germany', 0, 'Algorithms|DNA|DNA Primers|High-Throughput Nucleotide Sequencing|Models, Genetic|Nucleic Acid Amplification Techniques|Reproducibility of Results|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-14-272', '24021088', 'High-throughput sequencing technologies are improving in quality, capacity and costs, providing versatile applications in DNA and RNA research. For small genomes or fraction of larger genomes, DNA samples can be mixed and loaded together on the same sequencing track. This so-called multiplexing approach relies on a specific DNA tag or barcode that is attached to the sequencing or amplification primer and hence appears at the beginning of the sequence in every read. After sequencing, each sample read is identified on the basis of the respective barcode sequence.Alterations of DNA barcodes during synthesis, primer ligation, DNA amplification, or sequencing may lead to incorrect sample identification unless the error is revealed and corrected. This can be accomplished by implementing error correcting algorithms and codes. This barcoding strategy increases the total number of correctly identified samples, thus improving overall sequencing efficiency. Two popular sets of error-correcting codes are Hamming codes and Levenshtein codes.'),
(95748, 2013, 'bmc', 'Learning a Markov Logic network for supervised gene regulatory network inference', 'Brouard, Céline|Vrain, Christel|Dubois, Julie|Castel, David|Debily, Marie-Anne|dAlché-Buc, Florence', 'IBISC EA 4526, Université dÉvry-Val dEssonne, 23 Boulevard de France, 91037, Évry, France. celine.brouard@ibisc.univ-evry.fr.|IBISC EA 4526, Université dÉvry-Val dEssonne, 23 Boulevard de France, 91037, Évry, France. celine.brouard@ibisc.univ-evry.fr.|IBISC EA 4526, Université dÉvry-Val dEssonne, 23 Boulevard de France, 91037, Évry, France. celine.brouard@ibisc.univ-evry.fr.|IBISC EA 4526, Université dÉvry-Val dEssonne, 23 Boulevard de France, 91037, Évry, France. celine.brouard@ibisc.univ-evry.fr.|IBISC EA 4526, Université dÉvry-Val dEssonne, 23 Boulevard de France, 91037, Évry, France. celine.brouard@ibisc.univ-evry.fr.|IBISC EA 4526, Université dÉvry-Val dEssonne, 23 Boulevard de France, 91037, Évry, France. celine.brouard@ibisc.univ-evry.fr.', 'France|France|France|France|France|France', 5, 'Computer Simulation|Databases, Genetic|Gene Regulatory Networks|Humans|Logic|Markov Chains|Models, Statistical|ROC Curve|Support Vector Machine|Systems Biology', 'Journal Article', '10.1186/1471-2105-14-273', '24028533', 'Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate. Such a method builds a binary classifier able to assign a class (Regulation/No regulation) to an ordered pair of genes. Once learnt, the pairwise classifier can be used to predict new regulations. In this work, we explore the framework of Markov Logic Networks (MLN) that combine features of probabilistic graphical models with the expressivity of first-order logic rules.'),
(95749, 2013, 'bmc', 'Comparing a few SNP calling algorithms using low-coverage sequencing data', 'Yu, Xiaoqing|Sun, Shuying', 'Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio 44106, USA. ssun5211@yahoo.com.|Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio 44106, USA. ssun5211@yahoo.com.', 'United States|United States', 0, 'Algorithms|Computational Biology|Databases, Genetic|High-Throughput Nucleotide Sequencing|Humans|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-14-274', '24044377', 'Many Single Nucleotide Polymorphism (SNP) calling programs have been developed to identify Single Nucleotide Variations (SNVs) in next-generation sequencing (NGS) data. However, low sequencing coverage presents challenges to accurate SNV identification, especially in single-sample data. Moreover, commonly used SNP calling programs usually include several metrics in their output files for each potential SNP. These metrics are highly correlated in complex patterns, making it extremely difficult to select SNPs for further experimental validations.'),
(95750, 2013, 'bmc', 'A molecular model of the full-length human NOD-like receptor family CARD domain containing 5 (NLRC5) protein', 'Mxc3xb3tyxc3xa1n, Jxc3xa1nos Andrxc3xa1s|Bagossi, Pxc3xa9ter|Benkxc5x91, Szilvia|Txc5x91zsxc3xa9r, Jxc3xb3zsef', 'Department of Biochemistry and Molecular Biology, Faculty of Medicine, Medical and Health Science Center, University of Debrecen, POB 6, H-4012 Debrecen, Hungary. tozser@med.unideb.hu.|Department of Biochemistry and Molecular Biology, Faculty of Medicine, Medical and Health Science Center, University of Debrecen, POB 6, H-4012 Debrecen, Hungary. tozser@med.unideb.hu.|Department of Biochemistry and Molecular Biology, Faculty of Medicine, Medical and Health Science Center, University of Debrecen, POB 6, H-4012 Debrecen, Hungary. tozser@med.unideb.hu.|Department of Biochemistry and Molecular Biology, Faculty of Medicine, Medical and Health Science Center, University of Debrecen, POB 6, H-4012 Debrecen, Hungary. tozser@med.unideb.hu.', 'Hungary|Hungary|Hungary|Hungary', 18, 'Amino Acid Sequence|Animals|Humans|Intracellular Signaling Peptides and Proteins|Models, Molecular|Molecular Sequence Data|Protein Structure, Tertiary|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-14-275', '24044430', 'Pattern recognition receptors of the immune system have key roles in the regulation of pathways after the recognition of microbial- and danger-associated molecular patterns in vertebrates. Members of NOD-like receptor (NLR) family typically function intracellularly. The NOD-like receptor family CARD domain containing 5 (NLRC5) is the largest member of this family that also contains the largest number of leucine-rich repeats (LRRs).Due to the lack of crystal structures of full-length NLRs, projects have been initiated with the aim to model certain or all members of the family, but systematic studies did not model the full-length NLRC5 due to its unique domain architecture.Our aim was to analyze the LRR sequences of NLRC5 and some NLRC5-related proteins and to build a model for the full-length human NLRC5 by homology modeling.'),
(95751, 2013, 'bmc', 'Membrane protein orientation and refinement using a knowledge-based statistical potential', 'Nugent, Timothy|Jones, David T', 'Bioinformatics Group, Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK. d.jones@cs.ucl.ac.uk.|Bioinformatics Group, Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK. d.jones@cs.ucl.ac.uk.', 'United Kingdom|United Kingdom', 0, 'Algorithms|Computational Biology|Knowledge Bases|Lipid Bilayers|Membrane Potentials|Membrane Proteins|Models, Molecular|Reproducibility of Results', 'Journal Article', '10.1186/1471-2105-14-276', '24047460', 'Recent increases in the number of deposited membrane protein crystal structures necessitate the use of automated computational tools to position them within the lipid bilayer. Identifying the correct orientation allows us to study the complex relationship between sequence, structure and the lipid environment, which is otherwise challenging to investigate using experimental techniques due to the difficulty in crystallising membrane proteins embedded within intact membranes.'),
(95752, 2013, 'bmc', 'SynTView - an interactive multi-view genome browser for next-generation comparative microorganism genomics', 'Lechat, Pierre|Souche, Erika|Moszer, Ivan', 'Institut Pasteur, Plate-forme Bioanalyse Génomique, 28 rue du Docteur Roux, Paris, Cedex 15 75724, France. pierre.lechat@pasteur.fr.|Institut Pasteur, Plate-forme Bioanalyse Génomique, 28 rue du Docteur Roux, Paris, Cedex 15 75724, France. pierre.lechat@pasteur.fr.|Institut Pasteur, Plate-forme Bioanalyse Génomique, 28 rue du Docteur Roux, Paris, Cedex 15 75724, France. pierre.lechat@pasteur.fr.', 'France|France|France', 0, 'Animals|Chromosome Mapping|Genomics|High-Throughput Nucleotide Sequencing|Internet|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|User-Computer Interface|Web Browser', 'Journal Article', '10.1186/1471-2105-14-277', '24053737', 'Dynamic visualisation interfaces are required to explore the multiple microbial genome data now available, especially those obtained by high-throughput sequencing - a.k.a. Next-Generation Sequencing (NGS) - technologies, they would also be useful for standard annotated genomes whose chromosome organizations may be compared. Although various software systems are available, few offer an optimal combination of feature-rich capabilities, non-static user interfaces and multi-genome data handling.'),
(95753, 2013, 'bmc', 'Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data', 'Zhu, Mingzhu|Dahmen, Jeremy L|Stacey, Gary|Cheng, Jianlin', 'Department of Computer Science, University of Missouri, Columbia, MO 65211, USA. chengji@missouri.edu.|Department of Computer Science, University of Missouri, Columbia, MO 65211, USA. chengji@missouri.edu.|Department of Computer Science, University of Missouri, Columbia, MO 65211, USA. chengji@missouri.edu.|Department of Computer Science, University of Missouri, Columbia, MO 65211, USA. chengji@missouri.edu.', 'United States|United States|United States|United States', 15, 'Computational Biology|Gene Expression Profiling|Gene Regulatory Networks|High-Throughput Nucleotide Sequencing|Oligonucleotide Array Sequence Analysis|RNA|Root Nodules, Plant|Sequence Analysis, RNA|Soybeans|Transcriptome', 'Journal Article', '10.1186/1471-2105-14-278', '24053776', 'High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed.'),
(95754, 2013, 'bmc', 'Archetypal analysis of diverse Pseudomonas aeruginosa transcriptomes reveals adaptation in cystic fibrosis airways', 'Thøgersen, Juliane Charlotte|Mørup, Morten|Damkiær, Søren|Molin, Søren|Jelsbak, Lars', 'Department of Systems Biology, Technical University of Denmark, DK-2800 Lyngby, Denmark. LJ@bio.dtu.dk.|Department of Systems Biology, Technical University of Denmark, DK-2800 Lyngby, Denmark. LJ@bio.dtu.dk.|Department of Systems Biology, Technical University of Denmark, DK-2800 Lyngby, Denmark. LJ@bio.dtu.dk.|Department of Systems Biology, Technical University of Denmark, DK-2800 Lyngby, Denmark. LJ@bio.dtu.dk.|Department of Systems Biology, Technical University of Denmark, DK-2800 Lyngby, Denmark. LJ@bio.dtu.dk.', 'Denmark|Denmark|Denmark|Denmark|Denmark', 28, 'Adaptation, Biological|Child|Child, Preschool|Cluster Analysis|Cystic Fibrosis|Humans|Infant|Male|Mutation|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Pseudomonas Infections|Pseudomonas aeruginosa|Transcriptome', 'Journal Article', '10.1186/1471-2105-14-279', '24059747', 'Analysis of global gene expression by DNA microarrays is widely used in experimental molecular biology. However, the complexity of such high-dimensional data sets makes it difficult to fully understand the underlying biological features present in the data.The aim of this study is to introduce a method for DNA microarray analysis that provides an intuitive interpretation of data through dimension reduction and pattern recognition. We present the first Archetypal Analysis of global gene expression. The analysis is based on microarray data from five integrated studies of Pseudomonas aeruginosa isolated from the airways of cystic fibrosis patients.'),
(95755, 2013, 'bmc', 'Peak Finder Metaserver - a novel application for finding peaks in ChIP-seq data', 'Kruczyk, Marcin|Umer, Husen M|Enroth, Stefan|Komorowski, Jan', 'Department of Cell and Molecular Biology, Uppsala University, Husargatan 3, Uppsala, Sweden. jan.komorowski@lcb.uu.se.|Department of Cell and Molecular Biology, Uppsala University, Husargatan 3, Uppsala, Sweden. jan.komorowski@lcb.uu.se.|Department of Cell and Molecular Biology, Uppsala University, Husargatan 3, Uppsala, Sweden. jan.komorowski@lcb.uu.se.|Department of Cell and Molecular Biology, Uppsala University, Husargatan 3, Uppsala, Sweden. jan.komorowski@lcb.uu.se.', 'Sweden|Sweden|Sweden|Sweden', 0, 'Chromatin Immunoprecipitation|Computational Biology|Databases, Genetic|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1186/1471-2105-14-280', '24059758', 'Finding peaks in ChIP-seq is an important process in biological inference. In some cases, such as positioning nucleosomes with specific histone modifications or finding transcription factor binding specificities, the precision of the detected peak plays a significant role. There are several applications for finding peaks (called peak finders) based on different algorithms (e.g. MACS, Erange and HPeak). Benchmark studies have shown that the existing peak finders identify different peaks for the same dataset and it is not known which one is the most accurate. We present the first meta-server called Peak Finder MetaServer (PFMS) that collects results from several peak finders and produces consensus peaks. Our application accepts three standard ChIP-seq data formats: BED, BAM, and SAM.'),
(95756, 2013, 'bmc', 'A modular framework for biomedical concept recognition', 'Campos, David|Matos, Sérgio|Oliveira, José Luís', 'IEETA/DETI, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal. david.campos@ua.pt.|IEETA/DETI, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal. david.campos@ua.pt.|IEETA/DETI, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal. david.campos@ua.pt.', 'Portugal|Portugal|Portugal', 0, 'Computational Biology|Databases, Factual|Information Storage and Retrieval|Natural Language Processing|Pattern Recognition, Automated|Software', 'Journal Article', '10.1186/1471-2105-14-281', '24063607', 'Concept recognition is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. The development of such solutions is typically performed in an ad-hoc manner or using general information extraction frameworks, which are not optimized for the biomedical domain and normally require the integration of complex external libraries and/or the development of custom tools.'),
(95757, 2013, 'bmc', 'Large-scale multiple testing in genome-wide association studies via region-specific hidden Markov models', 'Xiao, Jian|Zhu, Wensheng|Guo, Jianhua', 'Key Laboratory for Applied Statistics of MOE, School of Mathematics and Statistics, Northeast Normal University, Changchun 130024, China. wszhu@nenu.edu.cn.|Key Laboratory for Applied Statistics of MOE, School of Mathematics and Statistics, Northeast Normal University, Changchun 130024, China. wszhu@nenu.edu.cn.|Key Laboratory for Applied Statistics of MOE, School of Mathematics and Statistics, Northeast Normal University, Changchun 130024, China. wszhu@nenu.edu.cn.', 'China|China|China', 4, 'Algorithms|Genetic Predisposition to Disease|Genome-Wide Association Study|Genomics|Humans|Markov Chains|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-14-282', '24067069', 'Identifying genetic variants associated with complex human diseases is a great challenge in genome-wide association studies (GWAS). Single nucleotide polymorphisms (SNPs) arising from genetic background are often dependent. The existing methods, i.e., local index of significance (LIS) and pooled local index of significance (PLIS), were both proposed for modeling SNP dependence and assumed that the whole chromosome follows a hidden Markov model (HMM). However, the fact that SNP data are often collected from separate heterogeneous regions of a single chromosome encourages different chromosomal regions to follow different HMMs. In this research, we developed a data-driven penalized criterion combined with a dynamic programming algorithm to find change points that divide the whole chromosome into more homogeneous regions. Furthermore, we extended PLIS to analyze the dependent tests obtained from multiple chromosomes with different regions for GWAS.'),
(95758, 2013, 'bmc', 'BGFit: management and automated fitting of biological growth curves', 'Veríssimo, André|Paixão, Laura|Neves, Ana Rute|Vinga, Susana', 'INESC-ID, R Alves Redol 9, 1000-029 Lisbon, Portugal. svinga@kdbio.inesc-id.pt.|INESC-ID, R Alves Redol 9, 1000-029 Lisbon, Portugal. svinga@kdbio.inesc-id.pt.|INESC-ID, R Alves Redol 9, 1000-029 Lisbon, Portugal. svinga@kdbio.inesc-id.pt.|INESC-ID, R Alves Redol 9, 1000-029 Lisbon, Portugal. svinga@kdbio.inesc-id.pt.', 'Portugal|Portugal|Portugal|Portugal', 9, 'Algorithms|Cell Proliferation|Computational Biology|Databases, Factual|Internet|Models, Biological|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-14-283', '24067087', 'Existing tools to model cell growth curves do not offer a flexible integrative approach to manage large datasets and automatically estimate parameters. Due to the increase of experimental time-series from microbiology and oncology, the need for a software that allows researchers to easily organize experimental data and simultaneously extract relevant parameters in an efficient way is crucial.'),
(95759, 2013, 'bmc', 'DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures', 'Mazandu, Gaston K|Mulder, Nicola J', 'Computational Biology Group, Department of Clinical Laboratory Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Medical School, Observatory, Cape Town, 7925, South Africa. gmazandu@cbio.uct.ac.za.|Computational Biology Group, Department of Clinical Laboratory Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Medical School, Observatory, Cape Town, 7925, South Africa. gmazandu@cbio.uct.ac.za.', 'South Africa|South Africa', 23, 'Cluster Analysis|Computational Biology|Databases, Genetic|Gene Ontology|Genes|Molecular Sequence Annotation|Proteins|Semantics|Software', 'Journal Article', '10.1186/1471-2105-14-284', '24067102', 'The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications.'),
(95760, 2013, 'bmc', 'Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction', 'Stojanova, Daniela|Ceci, Michelangelo|Malerba, Donato|Dzeroski, Saso', 'Department of Knowledge Technologies, JoŽef Stefan Institute, Jamova cesta 39, Ljubljana, Slovenia. daniela.stojanova@ijs.si.|Department of Knowledge Technologies, JoŽef Stefan Institute, Jamova cesta 39, Ljubljana, Slovenia. daniela.stojanova@ijs.si.|Department of Knowledge Technologies, JoŽef Stefan Institute, Jamova cesta 39, Ljubljana, Slovenia. daniela.stojanova@ijs.si.|Department of Knowledge Technologies, JoŽef Stefan Institute, Jamova cesta 39, Ljubljana, Slovenia. daniela.stojanova@ijs.si.', 'Slovenia|Slovenia|Slovenia|Slovenia', 0, 'Algorithms|Artificial Intelligence|Computational Biology|Databases, Genetic|Gene Ontology|Molecular Sequence Annotation|Protein Interaction Maps|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/1471-2105-14-285', '24070402', 'Ontologies and catalogs of gene functions, such as the Gene Ontology (GO) and MIPS-FUN, assume that functional classes are organized hierarchically, that is, general functions include more specific ones. This has recently motivated the development of several machine learning algorithms for gene function prediction that leverages on this hierarchical organization where instances may belong to multiple classes. In addition, it is possible to exploit relationships among examples, since it is plausible that related genes tend to share functional annotations. Although these relationships have been identified and extensively studied in the area of protein-protein interaction (PPI) networks, they have not received much attention in hierarchical and multi-class gene function prediction. Relations between genes introduce autocorrelation in functional annotations and violate the assumption that instances are independently and identically distributed (i.i.d.), which underlines most machine learning algorithms. Although the explicit consideration of these relations brings additional complexity to the learning process, we expect substantial benefits in predictive accuracy of learned classifiers.'),
(95761, 2013, 'bmc', 'The scoring of poses in protein-protein docking: current capabilities and future directions', 'Moal, Iain H|Torchala, Mieczyslaw|Bates, Paul A|Fernández-Recio, Juan', 'Joint BSC-IRB Research Program in Computational Biology, Life Science Department, Barcelona Super computing Center, Barcelona 08034, Spain. juanf@bsc.es.|Joint BSC-IRB Research Program in Computational Biology, Life Science Department, Barcelona Super computing Center, Barcelona 08034, Spain. juanf@bsc.es.|Joint BSC-IRB Research Program in Computational Biology, Life Science Department, Barcelona Super computing Center, Barcelona 08034, Spain. juanf@bsc.es.|Joint BSC-IRB Research Program in Computational Biology, Life Science Department, Barcelona Super computing Center, Barcelona 08034, Spain. juanf@bsc.es.', 'Spain|Spain|Spain|Spain', 0, 'Cluster Analysis|Computational Biology|Ligands|Molecular Docking Simulation|Protein Binding|Proteins', 'Journal Article', '10.1186/1471-2105-14-286', '24079540', 'Protein-protein docking, which aims to predict the structure of a protein-protein complex from its unbound components, remains an unresolved challenge in structural bioinformatics. An important step is the ranking of docked poses using a scoring function, for which many methods have been developed. There is a need to explore the differences and commonalities of these methods with each other, as well as with functions developed in the fields of molecular dynamics and homology modelling.'),
(95762, 2013, 'bmc', 'Statistical analysis of dendritic spine distributions in rat hippocampal cultures', 'Jammalamadaka, Aruna|Banerjee, Sourav|Manjunath, Bangalore S|Kosik, Kenneth S', 'Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, CA, USA. arunaj@ece.ucsb.edu.|Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, CA, USA. arunaj@ece.ucsb.edu.|Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, CA, USA. arunaj@ece.ucsb.edu.|Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, CA, USA. arunaj@ece.ucsb.edu.', 'United States|United States|United States|United States', 17, 'Animals|Cells, Cultured|Computational Biology|Dendritic Spines|Hippocampus|Logistic Models|Models, Neurological|Neurons|Rats', 'Journal Article', '10.1186/1471-2105-14-287', '24088199', 'Dendritic spines serve as key computational structures in brain plasticity. Much remains to be learned about their spatial and temporal distribution among neurons. Our aim in this study was to perform exploratory analyses based on the population distributions of dendritic spines with regard to their morphological characteristics and period of growth in dissociated hippocampal neurons. We fit a log-linear model to the contingency table of spine features such as spine type and distance from the soma to first determine which features were important in modeling the spines, as well as the relationships between such features. A multinomial logistic regression was then used to predict the spine types using the features suggested by the log-linear model, along with neighboring spine information. Finally, an important variant of Ripleys K-function applicable to linear networks was used to study the spatial distribution of spines along dendrites.'),
(95763, 2013, 'bmc', 'Drug repositioning for orphan genetic diseases through Conserved Anticoexpressed Gene Clusters (CAGCs)', 'Molineris, Ivan|Ala, Ugo|Provero, Paolo|Di Cunto, Ferdinando', 'Molecular Biotechnology Centre, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126, Torino, Italy. paolo.provero@unito.it.|Molecular Biotechnology Centre, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126, Torino, Italy. paolo.provero@unito.it.|Molecular Biotechnology Centre, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126, Torino, Italy. paolo.provero@unito.it.|Molecular Biotechnology Centre, Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126, Torino, Italy. paolo.provero@unito.it.', 'Italy|Italy|Italy|Italy', 0, 'Computational Biology|Disease|Drug Repositioning|Drug Therapy|Gene Expression|Gene Expression Profiling|Humans|Multigene Family|Phenotype', 'Journal Article', '10.1186/1471-2105-14-288', '24088245', 'The development of new therapies for orphan genetic diseases represents an extremely important medical and social challenge. Drug repositioning, i.e. finding new indications for approved drugs, could be one of the most cost- and time-effective strategies to cope with this problem, at least in a subset of cases. Therefore, many computational approaches based on the analysis of high throughput gene expression data have so far been proposed to reposition available drugs. However, most of these methods require gene expression profiles directly relevant to the pathologic conditions under study, such as those obtained from patient cells and/or from suitable experimental models. In this work we have developed a new approach for drug repositioning, based on identifying known drug targets showing conserved anti-correlated expression profiles with human disease genes, which is completely independent from the availability of ad hoc gene expression data-sets.'),
(95764, 2013, 'bmc', 'Calculation of Tajimas D and other neutrality test statistics from low depth next-generation sequencing data', 'Korneliussen, Thorfinn Sand|Moltke, Ida|Albrechtsen, Anders|Nielsen, Rasmus', 'Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Oestervoldgade 5-7, DK-1350, Copenhagen, Denmark. thorfinn@binf.ku.dk.|Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Oestervoldgade 5-7, DK-1350, Copenhagen, Denmark. thorfinn@binf.ku.dk.|Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Oestervoldgade 5-7, DK-1350, Copenhagen, Denmark. thorfinn@binf.ku.dk.|Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Oestervoldgade 5-7, DK-1350, Copenhagen, Denmark. thorfinn@binf.ku.dk.', 'Denmark|Denmark|Denmark|Denmark', 74, 'Base Sequence|Bayes Theorem|Bias|Feasibility Studies|Gene Frequency|Genetic Variation|Genetics, Population|Genome, Human|Genotype|High-Throughput Nucleotide Sequencing|Humans|Likelihood Functions|Polymorphism, Single Nucleotide|Selection, Genetic|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-14-289', '24088262', 'A number of different statistics are used for detecting natural selection using DNA sequencing data, including statistics that are summaries of the frequency spectrum, such as Tajimas D. These statistics are now often being applied in the analysis of Next Generation Sequencing (NGS) data. However, estimates of frequency spectra from NGS data are strongly affected by low sequencing coverage, the inherent technology dependent variation in sequencing depth causes systematic differences in the value of the statistic among genomic regions.'),
(95765, 2013, 'bmc', 'ScreenSifter: analysis and visualization of RNAi screening data', 'Kumar, Pankaj|Goh, Germaine|Wongphayak, Sarawut|Moreau, Dimitri|Bard, Frédéric', 'Institute of Molecular and Cell Biology, 61 Biopolis Drive, Proteos 138673, Singapore. fbard@imcb.a-star.edu.sg.|Institute of Molecular and Cell Biology, 61 Biopolis Drive, Proteos 138673, Singapore. fbard@imcb.a-star.edu.sg.|Institute of Molecular and Cell Biology, 61 Biopolis Drive, Proteos 138673, Singapore. fbard@imcb.a-star.edu.sg.|Institute of Molecular and Cell Biology, 61 Biopolis Drive, Proteos 138673, Singapore. fbard@imcb.a-star.edu.sg.|Institute of Molecular and Cell Biology, 61 Biopolis Drive, Proteos 138673, Singapore. fbard@imcb.a-star.edu.sg.', 'Singapore|Singapore|Singapore|Singapore|Singapore', 16, 'Computational Biology|Data Mining|Databases, Nucleic Acid|Internet|RNA Interference|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-14-290', '24088301', 'RNAi screening is a powerful method to study the genetics of intracellular processes in metazoans. Technically, the approach has been largely inspired by techniques and tools developed for compound screening, including those for data analysis. However, by contrast with compounds, RNAi inducing agents can be linked to a large body of gene-centric, publically available data. However, the currently available software applications to analyze RNAi screen data usually lack the ability to visualize associated gene information in an interactive fashion.'),
(95766, 2013, 'bmc', 'BIOCAT: a pattern recognition platform for customizable biological image classification and annotation', 'Zhou, Jie|Lamichhane, Santosh|Sterne, Gabriella|Ye, Bing|Peng, Hanchuan', 'Department of Computer Science, Northern Illinois University, DeKalb, IL 60115, USA. jzhou@niu.edu.|Department of Computer Science, Northern Illinois University, DeKalb, IL 60115, USA. jzhou@niu.edu.|Department of Computer Science, Northern Illinois University, DeKalb, IL 60115, USA. jzhou@niu.edu.|Department of Computer Science, Northern Illinois University, DeKalb, IL 60115, USA. jzhou@niu.edu.|Department of Computer Science, Northern Illinois University, DeKalb, IL 60115, USA. jzhou@niu.edu.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Computational Biology|Drosophila melanogaster|Imaging, Three-Dimensional|Models, Biological|Neurons|Pattern Recognition, Automated|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-14-291', '24090164', 'Pattern recognition algorithms are useful in bioimage informatics applications such as quantifying cellular and subcellular objects, annotating gene expressions, and classifying phenotypes. To provide effective and efficient image classification and annotation for the ever-increasing microscopic images, it is desirable to have tools that can combine and compare various algorithms, and build customizable solution for different biological problems. However, current tools often offer a limited solution in generating user-friendly and extensible tools for annotating higher dimensional images that correspond to multiple complicated categories.'),
(95767, 2013, 'bmc', 'Unsupervised automated high throughput phenotyping of RNAi time-lapse movies', 'Failmezger, Henrik|Fröhlich, Holger|Tresch, Achim', 'Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, 50829, Cologne, Germany. tresch@mpipz.mpg.de.|Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, 50829, Cologne, Germany. tresch@mpipz.mpg.de.|Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, 50829, Cologne, Germany. tresch@mpipz.mpg.de.', 'Germany|Germany|Germany', 9, 'Cell Line|Computational Biology|Databases, Factual|Gene Knockdown Techniques|Humans|Image Processing, Computer-Assisted|Microscopy|Phenotype|RNA Interference|Time-Lapse Imaging', 'Journal Article', '10.1186/1471-2105-14-292', '24090185', 'Gene perturbation experiments in combination with fluorescence time-lapse cell imaging are a powerful tool in reverse genetics. High content applications require tools for the automated processing of the large amounts of data. These tools include in general several image processing steps, the extraction of morphological descriptors, and the grouping of cells into phenotype classes according to their descriptors. This phenotyping can be applied in a supervised or an unsupervised manner. Unsupervised methods are suitable for the discovery of formerly unknown phenotypes, which are expected to occur in high-throughput RNAi time-lapse screens.'),
(95768, 2013, 'bmc', 'Automated image computing reshapes computational neuroscience', 'Peng, Hanchuan|Roysam, Badrinath|Ascoli, Giorgio A', 'Allen Institute for Brain Science, Seattle, WA, USA. hanchuan.peng@gmail.com.|Allen Institute for Brain Science, Seattle, WA, USA. hanchuan.peng@gmail.com.|Allen Institute for Brain Science, Seattle, WA, USA. hanchuan.peng@gmail.com.', 'United States|United States|United States', 16, 'Animals|Brain Mapping|Caenorhabditis elegans|Computational Biology|Databases, Factual|Humans|Image Processing, Computer-Assisted|Models, Neurological|Neurosciences', 'Journal Article', '10.1186/1471-2105-14-293', '24090217', 'We briefly identify several critical issues in current computational neuroscience, and present our opinions on potential solutions based on bioimage informatics, especially automated image computing. '),
(95769, 2013, 'bmc', 'Unsupervised segmentation of noisy electron microscopy images using salient watersheds and region merging', 'Navlakha, Saket|Ahammad, Parvez|Myers, Eugene W', 'School of Computer Science, Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA. navlakha@cs.cmu.edu.|School of Computer Science, Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA. navlakha@cs.cmu.edu.|School of Computer Science, Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA. navlakha@cs.cmu.edu.', 'United States|United States|United States', 0, 'Algorithms|Animals|Cerebral Cortex|Drosophila|Histocytochemistry|Image Processing, Computer-Assisted|Mice|Microscopy, Electron|Nerve Tissue|Pattern Recognition, Automated', 'Journal Article', '10.1186/1471-2105-14-294', '24090265', 'Segmenting electron microscopy (EM) images of cellular and subcellular processes in the nervous system is a key step in many bioimaging pipelines involving classification and labeling of ultrastructures. However, fully automated techniques to segment images are often susceptible to noise and heterogeneity in EM images (e.g. different histological preparations, different organisms, different brain regions, etc.). Supervised techniques to address this problem are often helpful but require large sets of training data, which are often difficult to obtain in practice, especially across many conditions.'),
(95770, 2013, 'bmc', 'Evaluation of the effectiveness of simple nuclei-segmentation methods on Caenorhabditis elegans embryogenesis images', 'Azuma, Yusuke|Onami, Shuichi', 'Laboratory for Developmental Dynamics, RIKEN Quantitative Biology Center, 2-2-3 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan. sonami@riken.jp.|Laboratory for Developmental Dynamics, RIKEN Quantitative Biology Center, 2-2-3 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan. sonami@riken.jp.', 'Japan|Japan', 0, 'Animals|Caenorhabditis elegans|Cell Nucleus|Computational Biology|Image Processing, Computer-Assisted', 'Journal Article', '10.1186/1471-2105-14-295', '24090283', 'For the analysis of spatio-temporal dynamics, various automated processing methods have been developed for nuclei segmentation. These methods tend to be complex for segmentation of images with crowded nuclei, preventing the simple reapplication of the methods to other problems. Thus, it is useful to evaluate the ability of simple methods to segment images with various degrees of crowded nuclei.'),
(95771, 2013, 'bmc', '3D time series analysis of cell shape using Laplacian approaches', 'Du, Cheng-Jin|Hawkins, Phillip T|Stephens, Len R|Bretschneider, Till', 'Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK. c.du@warwick.ac.uk.|Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK. c.du@warwick.ac.uk.|Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK. c.du@warwick.ac.uk.|Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK. c.du@warwick.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Cell Movement|Cell Shape|Computational Biology|Imaging, Three-Dimensional|Models, Biological|Neutrophils|Time-Lapse Imaging', 'Journal Article', '10.1186/1471-2105-14-296', '24090312', 'Fundamental cellular processes such as cell movement, division or food uptake critically depend on cells being able to change shape. Fast acquisition of three-dimensional image time series has now become possible, but we lack efficient tools for analysing shape deformations in order to understand the real three-dimensional nature of shape changes.'),
(95772, 2013, 'bmc', 'An automatic method for robust and fast cell detection in bright field images from high-throughput microscopy', 'Buggenthin, Felix|Marr, Carsten|Schwarzfischer, Michael|Hoppe, Philipp S|Hilsenbeck, Oliver|Schroeder, Timm|Theis, Fabian J', 'Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany. fabian.theis@helmholtz-muenchen.de.|Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany. fabian.theis@helmholtz-muenchen.de.|Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany. fabian.theis@helmholtz-muenchen.de.|Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany. fabian.theis@helmholtz-muenchen.de.|Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany. fabian.theis@helmholtz-muenchen.de.|Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany. fabian.theis@helmholtz-muenchen.de.|Institute of Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany. fabian.theis@helmholtz-muenchen.de.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Animals|Cells, Cultured|Computational Biology|Cytological Techniques|Hematopoietic Stem Cells|High-Throughput Screening Assays|Image Processing, Computer-Assisted|Mice|Microscopy|Software', 'Journal Article', '10.1186/1471-2105-14-297', '24090363', 'In recent years, high-throughput microscopy has emerged as a powerful tool to analyze cellular dynamics in an unprecedentedly high resolved manner. The amount of data that is generated, for example in long-term time-lapse microscopy experiments, requires automated methods for processing and analysis. Available software frameworks are well suited for high-throughput processing of fluorescence images, but they often do not perform well on bright field image data that varies considerably between laboratories, setups, and even single experiments.'),
(95773, 2013, 'bmc', 'Flanking sequence context-dependent transcription factor binding in early Drosophila development', 'Stringham, Jessica L|Brown, Adam S|Drewell, Robert A|Dresch, Jacqueline M', 'Mathematics Department, Harvey Mudd College, 301 Platt Boulevard, Claremont, CA 91711, USA. jdresch@amherst.edu.|Mathematics Department, Harvey Mudd College, 301 Platt Boulevard, Claremont, CA 91711, USA. jdresch@amherst.edu.|Mathematics Department, Harvey Mudd College, 301 Platt Boulevard, Claremont, CA 91711, USA. jdresch@amherst.edu.|Mathematics Department, Harvey Mudd College, 301 Platt Boulevard, Claremont, CA 91711, USA. jdresch@amherst.edu.', 'United States|United States|United States|United States', 0, 'Animals|Binding Sites|Drosophila melanogaster|Gene Expression Regulation|Genome|Genomics|Position-Specific Scoring Matrices|Protein Binding|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1186/1471-2105-14-298', '24093548', 'Gene expression in the Drosophila embryo is controlled by functional interactions between a large network of protein transcription factors (TFs) and specific sequences in DNA cis-regulatory modules (CRMs). The binding site sequences for any TF can be experimentally determined and represented in a position weight matrix (PWM). PWMs can then be used to predict the location of TF binding sites in other regions of the genome, although there are limitations to this approach as currently implemented.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(95774, 2013, 'bmc', 'A sampling framework for incorporating quantitative mass spectrometry data in protein interaction analysis', 'Tucker, George|Loh, Po-Ru|Berger, Bonnie', 'Mathematics Department and Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. bab@mit.edu.|Mathematics Department and Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. bab@mit.edu.|Mathematics Department and Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. bab@mit.edu.', 'United States|United States|United States', 2, 'Chromatography, Affinity|Computational Biology|Databases, Protein|Mass Spectrometry|Protein Interaction Mapping|Proteins', 'Journal Article', '10.1186/1471-2105-14-299', '24093595', 'Comprehensive protein-protein interaction (PPI) maps are a powerful resource for uncovering the molecular basis of genetic interactions and providing mechanistic insights. Over the past decade, high-throughput experimental techniques have been developed to generate PPI maps at proteome scale, first using yeast two-hybrid approaches and more recently via affinity purification combined with mass spectrometry (AP-MS). Unfortunately, data from both protocols are prone to both high false positive and false negative rates. To address these issues, many methods have been developed to post-process raw PPI data. However, with few exceptions, these methods only analyze binary experimental data (in which each potential interaction tested is deemed either observed or unobserved), neglecting quantitative information available from AP-MS such as spectral counts.'),
(95775, 2013, 'bmc', 'MFSPSSMpred: identifying short disorder-to-order binding regions in disordered proteins based on contextual local evolutionary conservation', 'Fang, Chun|Noguchi, Tamotsu|Tominaga, Daisuke|Yamana, Hayato', 'Department of Computer Science and Engineering, Waseda University, Tokyo, Japan. fangchun@yama.info.waseda.ac.jp.|Department of Computer Science and Engineering, Waseda University, Tokyo, Japan. fangchun@yama.info.waseda.ac.jp.|Department of Computer Science and Engineering, Waseda University, Tokyo, Japan. fangchun@yama.info.waseda.ac.jp.|Department of Computer Science and Engineering, Waseda University, Tokyo, Japan. fangchun@yama.info.waseda.ac.jp.', 'Japan|Japan|Japan|Japan', 0, 'Binding Sites|Computational Biology|Humans|Intrinsically Disordered Proteins|Position-Specific Scoring Matrices|Protein Binding|Protein Structure, Tertiary|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-14-300', '24093637', 'Molecular recognition features (MoRFs) are short binding regions located in longer intrinsically disordered protein regions. Although these short regions lack a stable structure in the natural state, they readily undergo disorder-to-order transitions upon binding to their partner molecules. MoRFs play critical roles in the molecular interaction network of a cell, and are associated with many human genetic diseases. Therefore, identification of MoRFs is an important step in understanding functional aspects of these proteins and in finding applications in drug design.'),
(95776, 2013, 'bmc', 'afterParty: turning raw transcriptomes into permanent resources', 'Jones, Martin|Blaxter, Mark', 'Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3JT, UK. martin.jones@ed.ac.uk.|Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3JT, UK. martin.jones@ed.ac.uk.', 'United Kingdom|United Kingdom', 0, 'Computational Biology|Databases, Genetic|Internet|Molecular Sequence Annotation|Sequence Analysis, DNA|Software|Transcriptome', 'Journal Article', '10.1186/1471-2105-14-301', '24093729', 'Next-generation DNA sequencing technologies have made it possible to generate transcriptome data for novel organisms quickly and cheaply, to the extent that the effort required to annotate and publish a new transcriptome is greater than the effort required to sequence it. Often, following publication, details of the annotation effort are only available in summary form, hindering subsequent exploitation of the data. To promote best-practice in annotation and to ensure that data remain accessible, we have written afterParty, a web application that allows users to assemble, annotate and publish novel transcriptomes using only a web browser.'),
(95777, 2013, 'bmc', 'Advances in the REDCAT software package', 'Schmidt, Chris|Irausquin, Stephanie J|Valafar, Homayoun', 'Department of Computer Science & Engineering, University of South Carolina, Columbia, SC 29208, USA. homayoun@cec.sc.edu.|Department of Computer Science & Engineering, University of South Carolina, Columbia, SC 29208, USA. homayoun@cec.sc.edu.|Department of Computer Science & Engineering, University of South Carolina, Columbia, SC 29208, USA. homayoun@cec.sc.edu.', 'United States|United States|United States', 12, 'Models, Molecular|Molecular Structure|Nuclear Magnetic Resonance, Biomolecular|Proteins|Software|United States|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-14-302', '24098943', 'Residual Dipolar Couplings (RDCs) have emerged in the past two decades as an informative source of experimental restraints for the study of structure and dynamics of biological macromolecules and complexes. The REDCAT software package was previously introduced for the analysis of molecular structures using RDC data. Here we report additional features that have been included in this software package in order to expand the scope of its analyses. We first discuss the features that enhance REDCATs user-friendly nature, such as the integration of a number of analyses into one single operation and enabling convenient examination of a structural ensemble in order to identify the most suitable structure. We then describe the new features which expand the scope of RDC analyses, performing exercises that utilize both synthetic and experimental data to illustrate and evaluate different features with regard to structure refinement and structure validation.'),
(95778, 2013, 'bmc', 'KNIME-CDK: Workflow-driven cheminformatics', 'Beisken, Stephan|Meinl, Thorsten|Wiswedel, Bernd|de Figueiredo, Luis F|Berthold, Michael|Steinbeck, Christoph', 'European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. beisken@ebi.ac.uk.|European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. beisken@ebi.ac.uk.|European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. beisken@ebi.ac.uk.|European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. beisken@ebi.ac.uk.|European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. beisken@ebi.ac.uk.|European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. beisken@ebi.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Biochemistry|Computational Biology|Small Molecule Libraries|Software|Workflow', 'Journal Article', '10.1186/1471-2105-14-257', '24103053', 'Cheminformaticians have to routinely process and analyse libraries of small molecules. Among other things, that includes the standardization of molecules, calculation of various descriptors, visualisation of molecular structures, and downstream analysis. For this purpose, scientific workflow platforms such as the Konstanz Information Miner can be used if provided with the right plug-in. A workflow-based cheminformatics tool provides the advantage of ease-of-use and interoperability between complementary cheminformatics packages within the same framework, hence facilitating the analysis process.'),
(95779, 2013, 'bmc', 'A Hidden Markov Model for identifying essential and growth-defect regions in bacterial genomes from transposon insertion sequencing data', 'DeJesus, Michael A|Ioerger, Thomas R', 'Department of Computer Science, Texas A&M University, College Station, TX 77843, USA. mad@cs.tamu.edu.|Department of Computer Science, Texas A&M University, College Station, TX 77843, USA. mad@cs.tamu.edu.', 'United States|United States', 41, 'DNA Transposable Elements|Databases, Genetic|Genome, Bacterial|High-Throughput Nucleotide Sequencing|Markov Chains|Mutation|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-14-303', '24103077', 'Knowledge of which genes are essential to the survival of an organism is critical to understanding the function of genes, and for the identification of potential drug targets for antimicrobial treatment. Previous statistical methods for assessing essentiality based on sequencing of tranposon libraries have usually limited their assessment to strict essential or non-essential categories. However, this binary view of essentiality does not accurately represent the more nuanced ways the growth of an organism might be affected by the disruption of its genes. In addition, these methods often limit their analysis to open-reading frames. We propose a novel method for analyzing sequence data from transposon mutant libraries using a Hidden Markov Model (HMM), along with formulas to adapt the parameters of the model to different datasets for robustness. This approach allows for the clustering of insertion sites into distinct regions of essentiality across the entire genome in a statistically rigorous manner, while also allowing for the detection of growth-defect and growth-advantage regions.'),
(95780, 2013, 'bmc', 'Lipid exposure prediction enhances the inference of rotational angles of transmembrane helices', 'Lai, Jhih-Siang|Cheng, Cheng-Wei|Lo, Allan|Sung, Ting-Yi|Hsu, Wen-Lian', 'Institute of Information Science, Academia Sinica, Taipei, Taiwan. alo1@illumina.com.|Institute of Information Science, Academia Sinica, Taipei, Taiwan. alo1@illumina.com.|Institute of Information Science, Academia Sinica, Taipei, Taiwan. alo1@illumina.com.|Institute of Information Science, Academia Sinica, Taipei, Taiwan. alo1@illumina.com.|Institute of Information Science, Academia Sinica, Taipei, Taiwan. alo1@illumina.com.', '-|-|-|-|-', 0, 'Amino Acid Sequence|Computational Biology|Hydrophobic and Hydrophilic Interactions|Membrane Lipids|Membrane Proteins|Molecular Sequence Data|Protein Structure, Secondary|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-14-304', '24112406', 'Since membrane protein structures are challenging to crystallize, computational approaches are essential for elucidating the sequence-to-structure relationships. Structural modeling of membrane proteins requires a multidimensional approach, and one critical geometric parameter is the rotational angle of transmembrane helices. Rotational angles of transmembrane helices are characterized by their folded structures and could be inferred by the hydrophobic moment, however, the folding mechanism of membrane proteins is not yet fully understood. The rotational angle of a transmembrane helix is related to the exposed surface of a transmembrane helix, since lipid exposure gives the degree of accessibility of each residue in lipid environment. To the best of our knowledge, there have been few advances in investigating whether an environment descriptor of lipid exposure could infer a geometric parameter of rotational angle.'),
(95781, 2013, 'bmc', 'cudaMap: a GPU accelerated program for gene expression connectivity mapping', 'McArt, Darragh G|Bankhead, Peter|Dunne, Philip D|Salto-Tellez, Manuel|Hamilton, Peter|Zhang, Shu-Dong', 'Centre for Cancer Research and Cell Biology (CCRCB), Queens University Belfast (QUB), Belfast, Northern Ireland, UK. s.zhang@qub.ac.uk.|Centre for Cancer Research and Cell Biology (CCRCB), Queens University Belfast (QUB), Belfast, Northern Ireland, UK. s.zhang@qub.ac.uk.|Centre for Cancer Research and Cell Biology (CCRCB), Queens University Belfast (QUB), Belfast, Northern Ireland, UK. s.zhang@qub.ac.uk.|Centre for Cancer Research and Cell Biology (CCRCB), Queens University Belfast (QUB), Belfast, Northern Ireland, UK. s.zhang@qub.ac.uk.|Centre for Cancer Research and Cell Biology (CCRCB), Queens University Belfast (QUB), Belfast, Northern Ireland, UK. s.zhang@qub.ac.uk.|Centre for Cancer Research and Cell Biology (CCRCB), Queens University Belfast (QUB), Belfast, Northern Ireland, UK. s.zhang@qub.ac.uk.', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland', 19, 'Antineoplastic Agents|Computational Biology|Computer Graphics|Drug Repositioning|Gene Expression|Humans|Neoplasms|Software', 'Journal Article', '10.1186/1471-2105-14-305', '24112435', 'Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take > 2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping.'),
(95782, 2013, 'bmc', 'Jimena: efficient computing and system state identification for genetic regulatory networks', 'Karl, Stefan|Dandekar, Thomas', 'Department of Bioinformatics, University of Würzburg, Am Hubland, Würzburg, Germany. dandekar@biozentrum.uni-wuerzburg.de.|Department of Bioinformatics, University of Würzburg, Am Hubland, Würzburg, Germany. dandekar@biozentrum.uni-wuerzburg.de.', 'Germany|Germany', 0, 'Algorithms|Computational Biology|Databases, Factual|Gene Regulatory Networks|Models, Biological|Models, Statistical', 'Journal Article', '10.1186/1471-2105-14-306', '24118878', 'Boolean networks capture switching behavior of many naturally occurring regulatory networks. For semi-quantitative modeling, interpolation between ON and OFF states is necessary. The high degree polynomial interpolation of Boolean genetic regulatory networks (GRNs) in cellular processes such as apoptosis or proliferation allows for the modeling of a wider range of node interactions than continuous activator-inhibitor models, but suffers from scaling problems for networks which contain nodes with more than ~10 inputs. Many GRNs from literature or new gene expression experiments exceed those limitations and a new approach was developed.'),
(95783, 2013, 'bmc', 'Modeling the next generation sequencing sample processing pipeline for the purposes of classification', 'Ghaffari, Noushin|Yousefi, Mohammadmahdi R|Johnson, Charles D|Ivanov, Ivan|Dougherty, Edward R', 'AgriLife Genomics and Bioinformatics Services, Texas AgriLife Research, Texas A&M System, College Station, Texas, TX, 77843, USA. nghaffari@tamu.edu.|AgriLife Genomics and Bioinformatics Services, Texas AgriLife Research, Texas A&M System, College Station, Texas, TX, 77843, USA. nghaffari@tamu.edu.|AgriLife Genomics and Bioinformatics Services, Texas AgriLife Research, Texas A&M System, College Station, Texas, TX, 77843, USA. nghaffari@tamu.edu.|AgriLife Genomics and Bioinformatics Services, Texas AgriLife Research, Texas A&M System, College Station, Texas, TX, 77843, USA. nghaffari@tamu.edu.|AgriLife Genomics and Bioinformatics Services, Texas AgriLife Research, Texas A&M System, College Station, Texas, TX, 77843, USA. nghaffari@tamu.edu.', 'United States|United States|United States|United States|United States', 0, 'Gene Expression Profiling|Genome|Genomics|High-Throughput Nucleotide Sequencing|Models, Genetic|RNA, Messenger|Systems Biology', 'Journal Article', '10.1186/1471-2105-14-307', '24118904', 'A key goal of systems biology and translational genomics is to utilize high-throughput measurements of cellular states to develop expression-based classifiers for discriminating among different phenotypes. Recent developments of Next Generation Sequencing (NGS) technologies can facilitate classifier design by providing expression measurements for tens of thousands of genes simultaneously via the abundance of their mRNA transcripts. Because NGS technologies result in a nonlinear transformation of the actual expression distributions, their application can result in data that are less discriminative than would be the actual expression levels themselves, were they directly observable.'),
(95784, 2013, 'bmc', 'Dynamical modelling of phenotypes in a genome-wide RNAi live-cell imaging assay', 'Pau, Gregoire|Walter, Thomas|Neumann, Beate|Hériché, Jean-Karim|Ellenberg, Jan|Huber, Wolfgang', 'AgriLife Genomics and Bioinformatics Services, Texas AgriLife Research, Texas A&M System, College Station, Texas, TX, 77843, USA. nghaffari@tamu.edu.|AgriLife Genomics and Bioinformatics Services, Texas AgriLife Research, Texas A&M System, College Station, Texas, TX, 77843, USA. nghaffari@tamu.edu.|AgriLife Genomics and Bioinformatics Services, Texas AgriLife Research, Texas A&M System, College Station, Texas, TX, 77843, USA. nghaffari@tamu.edu.|AgriLife Genomics and Bioinformatics Services, Texas AgriLife Research, Texas A&M System, College Station, Texas, TX, 77843, USA. nghaffari@tamu.edu.|AgriLife Genomics and Bioinformatics Services, Texas AgriLife Research, Texas A&M System, College Station, Texas, TX, 77843, USA. nghaffari@tamu.edu.|EMBL, Heidelberg, 69117 Germany. whuber@embl.de.', 'United States|United States|United States|United States|United States|Germany', 9, 'Cell Cycle|Computational Biology|HeLa Cells|Humans|Image Processing, Computer-Assisted|Mitosis|Models, Biological|Phenotype|RNA Interference|RNA, Small Interfering|Software', 'Journal Article', '10.1186/1471-2105-14-308', '24131777', 'The combination of time-lapse imaging of live cells with high-throughput perturbation assays is a powerful tool for genetics and cell biology. The Mitocheck project employed this technique to associate thousands of genes with transient biological phenotypes in cell division, cell death and migration. The original analysis of these data proceeded by assigning nuclear morphologies to cells at each time-point using automated image classification, followed by description of population frequencies and temporal distribution of cellular states through event-order maps. One of the choices made by that analysis was not to rely on temporal tracking of the individual cells, due to the relatively low image sampling frequency, and to focus on effects that could be discerned from population-level behaviour.'),
(95785, 2013, 'bmc', 'High variance in reproductive success generates a false signature of a genetic bottleneck in populations of constant size: a simulation study', 'Hoban, Sean M|Mezzavilla, Massimo|Gaggiotti, Oscar E|Benazzo, Andrea|van Oosterhout, Cock|Bertorelle, Giorgio', 'EMBL, Heidelberg, 69117 Germany. whuber@embl.de.|EMBL, Heidelberg, 69117 Germany. whuber@embl.de.|EMBL, Heidelberg, 69117 Germany. whuber@embl.de.|EMBL, Heidelberg, 69117 Germany. whuber@embl.de.|EMBL, Heidelberg, 69117 Germany. whuber@embl.de.|Department of Life Sciences and Biotechnology, University of Ferrara, via Borsari 46, Ferrara I-44121, Italy. ggb@unife.it.', 'Germany|Germany|Germany|Germany|Germany|Italy', 0, 'Computer Simulation|Gene Frequency|Genetic Variation|Genetics, Population|Humans|Models, Genetic|Population Density|Reproduction', 'Journal Article', '10.1186/1471-2105-14-309', '24131797', 'Demographic bottlenecks can severely reduce the genetic variation of a population or a species. Establishing whether low genetic variation is caused by a bottleneck or a constantly low effective number of individuals is important to understand a species ecology and evolution, and it has implications for conservation management. Recent studies have evaluated the power of several statistical methods developed to identify bottlenecks. However, the false positive rate, i.e. the rate with which a bottleneck signal is misidentified in demographically stable populations, has received little attention. We analyse this type of error (type I) in forward computer simulations of stable populations having greater than Poisson variance in reproductive success (i.e., variance in family sizes). The assumption of Poisson variance underlies bottleneck tests, yet it is commonly violated in species with high fecundity.'),
(95786, 2013, 'bmc', 'A method to identify differential expression profiles of time-course gene data with Fourier transformation', 'Kim, Jaehee|Ogden, Robert Todd|Kim, Haseong', 'Department of Statistics, Duksung Womens University, Seoul, South Korea. jaehee@duksung.ac.kr.|Department of Statistics, Duksung Womens University, Seoul, South Korea. jaehee@duksung.ac.kr.|Department of Statistics, Duksung Womens University, Seoul, South Korea. jaehee@duksung.ac.kr.', '-|-|-', 12, 'Cell Cycle|Cluster Analysis|Computational Biology|Fourier Analysis|Gene Expression Profiling|Models, Genetic|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Sensitivity and Specificity|Time Factors', 'Journal Article', '10.1186/1471-2105-14-310', '24134721', 'Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis.'),
(95787, 2013, 'bmc', 'Parametric sensitivity analysis for biochemical reaction networks based on pathwise information theory', 'Pantazis, Yannis|Katsoulakis, Markos A|Vlachos, Dionisios G', 'Department of Statistics, Duksung Womens University, Seoul, South Korea. jaehee@duksung.ac.kr.|Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA 01002, USA. markos@math.umass.edu.|Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA 01002, USA. markos@math.umass.edu.', 'United States|United States|United States', 0, 'Entropy|Information Theory|Models, Biological|Proteins|Stochastic Processes|Systems Biology', 'Journal Article', '10.1186/1471-2105-14-311', '24148216', 'Stochastic modeling and simulation provide powerful predictive methods for the intrinsic understanding of fundamental mechanisms in complex biochemical networks. Typically, such mathematical models involve networks of coupled jump stochastic processes with a large number of parameters that need to be suitably calibrated against experimental data. In this direction, the parameter sensitivity analysis of reaction networks is an essential mathematical and computational tool, yielding information regarding the robustness and the identifiability of model parameters. However, existing sensitivity analysis approaches such as variants of the finite difference method can have an overwhelming computational cost in models with a high-dimensional parameter space.'),
(95788, 2013, 'bmc', 'A scalable, knowledge-based analysis framework for genetic association studies', 'Baurley, James W|Conti, David V', 'Bioinformatics Research Group, Bina Nusantara University, Jakarta, Indonesia. baurley@gmail.com.|Bioinformatics Research Group, Bina Nusantara University, Jakarta, Indonesia. baurley@gmail.com.', 'Indonesia|Indonesia', 0, 'Algorithms|Asthma|Bayes Theorem|Case-Control Studies|Child|Computational Biology|Genetic Association Studies|Humans|Knowledge Bases|Markov Chains|Models, Genetic|Monte Carlo Method|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-14-312', '24152222', 'Testing for marginal associations between numerous genetic variants and disease may miss complex relationships among variables (e.g., gene-gene interactions). Bayesian approaches can model multiple variables together and offer advantages over conventional model building strategies, including using existing biological evidence as modeling priors and acknowledging that many models may fit the data well. With many candidate variables, Bayesian approaches to variable selection rely on algorithms to approximate the posterior distribution of models, such as Markov-Chain Monte Carlo (MCMC). Unfortunately, MCMC is difficult to parallelize and requires many iterations to adequately sample the posterior. We introduce a scalable algorithm called PEAK that improves the efficiency of MCMC by dividing a large set of variables into related groups using a rooted graph that resembles a mountain peak. Our algorithm takes advantage of parallel computing and existing biological databases when available.'),
(95789, 2013, 'bmc', 'Compact representation of k-mer de Bruijn graphs for genome read assembly', 'Rødland, Einar Andreas', 'Center for Cancer Biomedicine & Departement of Informatics, University of Oslo, 0316 Oslo, Norway. einarro@ifi.uio.no.', 'Norway', 11, 'Algorithms|Genomics|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-14-313', '24152242', 'Processing of reads from high throughput sequencing is often done in terms of edges in the de Bruijn graph representing all k-mers from the reads. The memory requirements for storing all k-mers in a lookup table can be demanding, even after removal of read errors, but can be alleviated by using a memory efficient data structure.'),
(95790, 2013, 'bmc', 'Identification of properties important to protein aggregation using feature selection', 'Fang, Yaping|Gao, Shan|Tai, David|Middaugh, C Russell|Fang, Jianwen', 'Center for Cancer Biomedicine & Departement of Informatics, University of Oslo, 0316 Oslo, Norway. einarro@ifi.uio.no.|Center for Cancer Biomedicine & Departement of Informatics, University of Oslo, 0316 Oslo, Norway. einarro@ifi.uio.no.|Center for Cancer Biomedicine & Departement of Informatics, University of Oslo, 0316 Oslo, Norway. einarro@ifi.uio.no.|Center for Cancer Biomedicine & Departement of Informatics, University of Oslo, 0316 Oslo, Norway. einarro@ifi.uio.no.|Applied Bioinformatics Laboratory, University of Kansas, 2034 Becker Drive, Lawrence, KS 66047, USA. jianwen.fang@nih.gov.', 'Norway|Norway|Norway|Norway|United States', 0, 'Amino Acid Sequence|Amyloid|Computational Biology|Computer Simulation|Humans|Peptides|Proteins|Reproducibility of Results|Sequence Analysis, Protein|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-14-314', '24165390', 'Protein aggregation is a significant problem in the biopharmaceutical industry (protein drug stability) and is associated medically with over 40 human diseases. Although a number of computational models have been developed for predicting aggregation propensity and identifying aggregation-prone regions in proteins, little systematic research has been done to determine physicochemical properties relevant to aggregation and their relative importance to this important process. Such studies may result in not only accurately predicting peptide aggregation propensities and identifying aggregation prone regions in proteins, but also aid in discovering additional underlying mechanisms governing this process.'),
(95791, 2013, 'bmc', 'A novel strategy for classifying the output from an in silico vaccine discovery pipeline for eukaryotic pathogens using machine learning algorithms', 'Goodswen, Stephen J|Kennedy, Paul J|Ellis, John T', 'Applied Bioinformatics Laboratory, University of Kansas, 2034 Becker Drive, Lawrence, KS 66047, USA. jianwen.fang@nih.gov.|Applied Bioinformatics Laboratory, University of Kansas, 2034 Becker Drive, Lawrence, KS 66047, USA. jianwen.fang@nih.gov.|School of Medical and Molecular Biosciences, ithree institute at the University of Technology Sydney (UTS), Sydney, Australia. John.Ellis@uts.edu.au.', 'United States|United States|Australia', 18, 'Algorithms|Animals|Antigens|Artificial Intelligence|Caenorhabditis elegans Proteins|Computational Biology|Computer Simulation|Drug Discovery|Protozoan Proteins|Sensitivity and Specificity|Vaccines', 'Journal Article', '10.1186/1471-2105-14-315', '24180526', 'An in silico vaccine discovery pipeline for eukaryotic pathogens typically consists of several computational tools to predict protein characteristics. The aim of the in silico approach to discovering subunit vaccines is to use predicted characteristics to identify proteins which are worthy of laboratory investigation. A major challenge is that these predictions are inherent with hidden inaccuracies and contradictions. This study focuses on how to reduce the number of false candidates using machine learning algorithms rather than relying on expensive laboratory validation. Proteins from Toxoplasma gondii, Plasmodium sp., and Caenorhabditis elegans were used as training and test datasets.'),
(95792, 2013, 'bmc', 'DCE@urLAB: a dynamic contrast-enhanced MRI pharmacokinetic analysis tool for preclinical data', 'Ortuño, Juan E|Ledesma-Carbayo, María J|Simões, Rui V|Candiota, Ana P|Arús, Carles|Santos, Andrés', 'CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 50018 Zaragoza, Spain. juanen@die.upm.es.|CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 50018 Zaragoza, Spain. juanen@die.upm.es.|CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 50018 Zaragoza, Spain. juanen@die.upm.es.|CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 50018 Zaragoza, Spain. juanen@die.upm.es.|CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 50018 Zaragoza, Spain. juanen@die.upm.es.|CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 50018 Zaragoza, Spain. juanen@die.upm.es.', 'Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Animals|Brain Neoplasms|Computer Simulation|Contrast Media|Disease Models, Animal|Least-Squares Analysis|Magnetic Resonance Imaging|Mice|Software', 'Journal Article', '10.1186/1471-2105-14-316', '24180558', 'DCE@urLAB is a software application for analysis of dynamic contrast-enhanced magnetic resonance imaging data (DCE-MRI). The tool incorporates a friendly graphical user interface (GUI) to interactively select and analyze a region of interest (ROI) within the image set, taking into account the tissue concentration of the contrast agent (CA) and its effect on pixel intensity.'),
(95793, 2013, 'bmc', 'Automated analysis of phylogenetic clusters', 'Ragonnet-Cronin, Manon|Hodcroft, Emma|Hué, Stéphane|Fearnhill, Esther|Delpech, Valerie|Brown, Andrew J Leigh|Lycett, Samantha|UK HIV Drug Resistance Database', 'University of Edinburgh, Edinburgh, UK. manon.ragonnet@ed.ac.uk.|University of Edinburgh, Edinburgh, UK. manon.ragonnet@ed.ac.uk.|University of Edinburgh, Edinburgh, UK. manon.ragonnet@ed.ac.uk.|University of Edinburgh, Edinburgh, UK. manon.ragonnet@ed.ac.uk.|University of Edinburgh, Edinburgh, UK. manon.ragonnet@ed.ac.uk.|University of Edinburgh, Edinburgh, UK. manon.ragonnet@ed.ac.uk.|University of Edinburgh, Edinburgh, UK. manon.ragonnet@ed.ac.uk.|University of Edinburgh, Edinburgh, UK. manon.ragonnet@ed.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 145, 'Cluster Analysis|Computational Biology|HIV Infections|HIV-1|Humans|Molecular Epidemiology|Phylogeny|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-14-317', '24191891', 'As sequence data sets used for the investigation of pathogen transmission patterns increase in size, automated tools and standardized methods for cluster analysis have become necessary. We have developed an automated Cluster Picker which identifies monophyletic clades meeting user-input criteria for bootstrap support and maximum genetic distance within large phylogenetic trees. A second tool, the Cluster Matcher, automates the process of linking genetic data to epidemiological or clinical data, and matches clusters between runs of the Cluster Picker.'),
(95794, 2013, 'bmc', 'Comparison and improvement of algorithms for computing minimal cut sets', 'Jungreuthmayer, Christian|Nair, Govind|Klamt, Steffen|Zanghellini, Jürgen', 'University of Edinburgh, Edinburgh, UK. manon.ragonnet@ed.ac.uk.|University of Edinburgh, Edinburgh, UK. manon.ragonnet@ed.ac.uk.|University of Edinburgh, Edinburgh, UK. manon.ragonnet@ed.ac.uk.|Austrian Centre of Industrial Biotechnology, Vienna, Austria. juergen.zanghellini@acib.at.', 'United Kingdom|United Kingdom|United Kingdom|Austria', 17, 'Algorithms|Computational Biology|Computer Simulation|Escherichia coli|Gene Deletion|Gene Knockout Techniques|Humans|Image Processing, Computer-Assisted|Metabolic Networks and Pathways|Models, Genetic|Software|Thermodynamics', 'Comparative Study', '10.1186/1471-2105-14-318', '24191903', 'Constrained minimal cut sets (cMCSs) have recently been introduced as a framework to enumerate minimal genetic intervention strategies for targeted optimization of metabolic networks. Two different algorithmic schemes (adapted Berge algorithm and binary integer programming) have been proposed to compute cMCSs from elementary modes. However, in their original formulation both algorithms are not fully comparable.'),
(95795, 2013, 'bmc', 'Benchmark for multi-cellular segmentation of bright field microscopy images', 'Zaritsky, Assaf|Manor, Nathan|Wolf, Lior|Ben-Jacob, Eshel|Tsarfaty, Ilan', 'Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, 69978, Israel. assafzar@gmail.com.|Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, 69978, Israel. assafzar@gmail.com.|Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, 69978, Israel. assafzar@gmail.com.|Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, 69978, Israel. assafzar@gmail.com.|Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, 69978, Israel. assafzar@gmail.com.', 'Israel|Israel|Israel|Israel|Israel', 0, 'Algorithms|Animals|Cell Movement|Cytological Techniques|Dogs|HEK293 Cells|Humans|Image Processing, Computer-Assisted|Madin Darby Canine Kidney Cells|Microscopy', 'Journal Article', '10.1186/1471-2105-14-319', '24195722', 'Multi-cellular segmentation of bright field microscopy images is an essential computational step when quantifying collective migration of cells in vitro. Despite the availability of various tools and algorithms, no publicly available benchmark has been proposed for evaluation and comparison between the different alternatives.'),
(95796, 2013, 'bmc', 'Design of RNA splicing analysis null models for post hoc filtering of Drosophila head RNA-Seq data with the splicing analysis kit (Spanki)', 'Sturgill, David|Malone, John H|Sun, Xia|Smith, Harold E|Rabinow, Leonard|Samson, Marie-Laure|Oliver, Brian', 'National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 50 South Drive, Bethesda, MD 20892, USA. dave.sturgill@gmail.com.|National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 50 South Drive, Bethesda, MD 20892, USA. dave.sturgill@gmail.com.|National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 50 South Drive, Bethesda, MD 20892, USA. dave.sturgill@gmail.com.|National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 50 South Drive, Bethesda, MD 20892, USA. dave.sturgill@gmail.com.|National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 50 South Drive, Bethesda, MD 20892, USA. dave.sturgill@gmail.com.|National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 50 South Drive, Bethesda, MD 20892, USA. dave.sturgill@gmail.com.|National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 50 South Drive, Bethesda, MD 20892, USA. dave.sturgill@gmail.com.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Alternative Splicing|Animals|Base Sequence|Computational Biology|Computer Simulation|Drosophila|Female|Gene Expression Profiling|Male|Models, Genetic|Molecular Sequence Data|Protein Isoforms|RNA, Messenger|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-14-320', '24209455', 'The production of multiple transcript isoforms from one gene is a major source of transcriptome complexity. RNA-Seq experiments, in which transcripts are converted to cDNA and sequenced, allow the resolution and quantification of alternative transcript isoforms. However, methods to analyze splicing are underdeveloped and errors resulting in incorrect splicing calls occur in every experiment.'),
(95797, 2013, 'bmc', 'PlantTFcat: an online plant transcription factor and transcriptional regulator categorization and analysis tool', 'Dai, Xinbin|Sinharoy, Senjuti|Udvardi, Michael|Zhao, Patrick Xuechun', 'Plant Biology Division, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway 73401 Ardmore, OK, USA. pzhao@noble.org.|Plant Biology Division, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway 73401 Ardmore, OK, USA. pzhao@noble.org.|Plant Biology Division, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway 73401 Ardmore, OK, USA. pzhao@noble.org.|Plant Biology Division, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway 73401 Ardmore, OK, USA. pzhao@noble.org.', 'United States|United States|United States|United States', 0, 'Arabidopsis|Chromatin|Computational Biology|Forecasting|Gene Expression Regulation, Plant|Genome, Plant|Internet|Medicago truncatula|Plant Proteins|Predictive Value of Tests|Software|Transcription Factors|Zea mays', 'Journal Article', '10.1186/1471-2105-14-321', '24219505', 'Plants regulate intrinsic gene expression through transcription factors (TFs), transcriptional regulators (TRs), chromatin regulators (CRs), and the basal transcription machinery. An understanding of plant gene regulatory mechanisms at a systems level requires the identification of these regulatory elements on a genomic scale.'),
(95798, 2013, 'bmc', '3DScapeCS: application of three dimensional, parallel, dynamic network visualization in Cytoscape', 'Wang, Qi|Tang, Biao|Song, Lifu|Ren, Biao|Liang, Qun|Xie, Feng|Zhuo, Ying|Liu, Xueting|Zhang, Lixin', 'Plant Biology Division, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway 73401 Ardmore, OK, USA. pzhao@noble.org.|Plant Biology Division, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway 73401 Ardmore, OK, USA. pzhao@noble.org.|Plant Biology Division, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway 73401 Ardmore, OK, USA. pzhao@noble.org.|Plant Biology Division, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway 73401 Ardmore, OK, USA. pzhao@noble.org.|Plant Biology Division, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway 73401 Ardmore, OK, USA. pzhao@noble.org.|Plant Biology Division, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway 73401 Ardmore, OK, USA. pzhao@noble.org.|Plant Biology Division, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway 73401 Ardmore, OK, USA. pzhao@noble.org.|Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100190, Peoples Republic of China. liuxueting_cn@hotmail.com.|Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100190, Peoples Republic of China. liuxueting_cn@hotmail.com.', 'United States|United States|United States|United States|United States|United States|United States|China|China', 9, 'Computational Biology|Computer Graphics|Databases, Factual|Imaging, Three-Dimensional|Mass Spectrometry|Models, Biological|Protein Interaction Mapping|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-14-322', '24225050', 'The exponential growth of gigantic biological data from various sources, such as protein-protein interaction (PPI), genome sequences scaffolding, Mass spectrometry (MS) molecular networking and metabolic flux, demands an efficient way for better visualization and interpretation beyond the conventional, two-dimensional visualization tools.'),
(95799, 2013, 'bmc', 'CoMAGC: a corpus with multi-faceted annotations of gene-cancer relations', 'Lee, Hee-Jin|Shim, Sang-Hyung|Song, Mi-Ryoung|Lee, Hyunju|Park, Jong C', 'Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100190, Peoples Republic of China. liuxueting_cn@hotmail.com.|Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100190, Peoples Republic of China. liuxueting_cn@hotmail.com.|Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100190, Peoples Republic of China. liuxueting_cn@hotmail.com.|Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100190, Peoples Republic of China. liuxueting_cn@hotmail.com.|Department of Computer Science, KAIST, 291 Daehak-ro, Daejeon, Republic of Korea. park@cs.kaist.ac.kr.', 'China|China|China|China|-', 0, 'Computational Biology|Data Mining|Female|Genetic Predisposition to Disease|Humans|Male|Molecular Sequence Annotation|Neoplasms|Semantics', 'Journal Article', '10.1186/1471-2105-14-323', '24225062', 'In order to access the large amount of information in biomedical literature about genes implicated in various cancers both efficiently and accurately, the aid of text mining (TM) systems is invaluable. Current TM systems do target either gene-cancer relations or biological processes involving genes and cancers, but the former type produces information not comprehensive enough to explain how a gene affects a cancer, and the latter does not provide a concise summary of gene-cancer relations.'),
(95800, 2013, 'bmc', 'SUNPLIN: simulation with uncertainty for phylogenetic investigations', 'Martins, Wellington S|Carmo, Welton C|Longo, Humberto J|Rosa, Thierson C|Rangel, Thiago F', 'Institute of Informatics, Federal University of Goiás, Goiânia, Brazil. wellington@inf.ufg.br.|Institute of Informatics, Federal University of Goiás, Goiânia, Brazil. wellington@inf.ufg.br.|Institute of Informatics, Federal University of Goiás, Goiânia, Brazil. wellington@inf.ufg.br.|Institute of Informatics, Federal University of Goiás, Goiânia, Brazil. wellington@inf.ufg.br.|Institute of Informatics, Federal University of Goiás, Goiânia, Brazil. wellington@inf.ufg.br.', 'Brazil|Brazil|Brazil|Brazil|Brazil', 8, 'Algorithms|Amphibian Proteins|Animals|Avian Proteins|Biological Evolution|Carnivora|Chiroptera|Computational Biology|Computer Simulation|Consensus Sequence|Evolution, Molecular|Phylogeny|Software|Uncertainty', 'Journal Article', '10.1186/1471-2105-14-324', '24229408', 'Phylogenetic comparative analyses usually rely on a single consensus phylogenetic tree in order to study evolutionary processes. However, most phylogenetic trees are incomplete with regard to species sampling, which may critically compromise analyses. Some approaches have been proposed to integrate non-molecular phylogenetic information into incomplete molecular phylogenies. An expanded tree approach consists of adding missing species to random locations within their clade. The information contained in the topology of the resulting expanded trees can be captured by the pairwise phylogenetic distance between species and stored in a matrix for further statistical analysis. Thus, the random expansion and processing of multiple phylogenetic trees can be used to estimate the phylogenetic uncertainty through a simulation procedure. Because of the computational burden required, unless this procedure is efficiently implemented, the analyses are of limited applicability.'),
(95801, 2013, 'bmc', 'Identification of single nucleotide polymorphisms from the transcriptome of an organism with a whole genome duplication', 'Christensen, Kris A|Brunelli, Joseph P|Lambert, Matthew J|DeKoning, Jenefer|Phillips, Ruth B|Thorgaard, Gary H', 'School of Molecular Biosciences, Washington State University, Pullman WA 99164-4660, USA. kris.christensen@email.wsu.edu.|School of Molecular Biosciences, Washington State University, Pullman WA 99164-4660, USA. kris.christensen@email.wsu.edu.|School of Molecular Biosciences, Washington State University, Pullman WA 99164-4660, USA. kris.christensen@email.wsu.edu.|School of Molecular Biosciences, Washington State University, Pullman WA 99164-4660, USA. kris.christensen@email.wsu.edu.|School of Molecular Biosciences, Washington State University, Pullman WA 99164-4660, USA. kris.christensen@email.wsu.edu.|School of Molecular Biosciences, Washington State University, Pullman WA 99164-4660, USA. kris.christensen@email.wsu.edu.', 'United States|United States|United States|United States|United States|United States', 14, 'Animals|Base Sequence|Gene Duplication|Genome|Genomics|Humans|Molecular Sequence Data|Oncorhynchus mykiss|Polymorphism, Single Nucleotide|Polyploidy|Sequence Alignment|Transcriptome', 'Journal Article', '10.1186/1471-2105-14-325', '24237905', 'The common ancestor of salmonid fishes, including rainbow trout (Oncorhynchus mykiss), experienced a whole genome duplication between 20 and 100 million years ago, and many of the duplicated genes have been retained in the trout genome. This retention complicates efforts to detect allelic variation in salmonid fishes. Specifically, single nucleotide polymorphism (SNP) detection is problematic because nucleotide variation can be found between the duplicate copies (paralogs) of a gene as well as between alleles.'),
(95802, 2013, 'bmc', 'snp-search: simple processing, manipulation and searching of SNPs from high-throughput sequencing', 'Al-Shahib, Ali|Underwood, Anthony', 'School of Molecular Biosciences, Washington State University, Pullman WA 99164-4660, USA. kris.christensen@email.wsu.edu.|School of Molecular Biosciences, Washington State University, Pullman WA 99164-4660, USA. kris.christensen@email.wsu.edu.', 'United States|United States', 0, 'Algorithms|Genome, Bacterial|High-Throughput Nucleotide Sequencing|Phylogeny|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software|Streptococcus pyogenes', 'Journal Article', '10.1186/1471-2105-14-326', '24246037', 'A typical bacterial pathogen genome mapping project can identify thousands of single nucleotide polymorphisms (SNP). Interpreting SNP data is complex and it is difficult to conceptualise the data contained within the large flat files that are the typical output from most SNP calling algorithms. One solution to this problem is to construct a database that can be queried using simple commands so that SNP interrogation and output is both easy and comprehensible.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(95803, 2013, 'bmc', 'Filling out the structural map of the NTF2-like superfamily', 'Eberhardt, Ruth Y|Chang, Yuanyuan|Bateman, Alex|Murzin, Alexey G|Axelrod, Herbert L|Hwang, William C|Aravind, L', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK. re3@sanger.ac.uk.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK. re3@sanger.ac.uk.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK. re3@sanger.ac.uk.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK. re3@sanger.ac.uk.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK. re3@sanger.ac.uk.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK. re3@sanger.ac.uk.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK. re3@sanger.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 20, 'Bacterial Proteins|Bacteroides|Campylobacter jejuni|Catalytic Domain|Crystallography, X-Ray|Ligands|Nucleocytoplasmic Transport Proteins|Peptide Mapping|Protein Folding|Protein Multimerization|Protein Structure, Tertiary|Ruminococcus', 'Journal Article', '10.1186/1471-2105-14-327', '24246060', 'The NTF2-like superfamily is a versatile group of protein domains sharing a common fold. The sequences of these domains are very diverse and they share no common sequence motif. These domains serve a range of different functions within the proteins in which they are found, including both catalytic and non-catalytic versions. Clues to the function of protein domains belonging to such a diverse superfamily can be gleaned from analysis of the proteins and organisms in which they are found.'),
(95804, 2013, 'bmc', 'A novel cell nuclei segmentation method for 3D C elegans embryonic time-lapse images', 'Chen, Long|Chan, Leanne Lai Hang|Zhao, Zhongying|Yan, Hong', 'Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong. longchen5@alumni.cityu.edu.hk.|Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong. longchen5@alumni.cityu.edu.hk.|Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong. longchen5@alumni.cityu.edu.hk.|Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong. longchen5@alumni.cityu.edu.hk.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong', 0, 'Algorithms|Animals|Caenorhabditis elegans|Cell Nucleus|Imaging, Three-Dimensional|Microscopy, Confocal|Time-Lapse Imaging', 'Journal Article', '10.1186/1471-2105-14-328', '24252066', 'Recently a series of algorithms have been developed, providing automatic tools for tracing C. elegans embryonic cell lineage. In these algorithms, 3D images collected from a confocal laser scanning microscope were processed, the output of which is cell lineage with cell division history and cell positions with time. However, current image segmentation algorithms suffer from high error rate especially after 350-cell stage because of low signal-noise ratio as well as low resolution along the Z axis (0.5-1 microns). As a result, correction of the errors becomes a huge burden. These errors are mainly produced in the segmentation of nuclei. Thus development of a more accurate image segmentation algorithm will alleviate the hurdle for automated analysis of cell lineage.'),
(95805, 2013, 'bmc', 'Cheminformatic models based on machine learning for pyruvate kinase inhibitors of Leishmania mexicana', 'Jamal, Salma|Scaria, Vinod', 'GN Ramachandran Knowledge Center for Genome Informatics, CSIR Institute of Genomics and Integrative Biology, Mall Road, Delhi, 110007, India. vinods@igib.in.|GN Ramachandran Knowledge Center for Genome Informatics, CSIR Institute of Genomics and Integrative Biology, Mall Road, Delhi, 110007, India. vinods@igib.in.', 'India|India', 19, 'Algorithms|Antiprotozoal Agents|Artificial Intelligence|Computer Simulation|Drug Discovery|Humans|Leishmania mexicana|Leishmaniasis|Predictive Value of Tests|Pyruvate Kinase|Small Molecule Libraries', 'Journal Article', '10.1186/1471-2105-14-329', '24252103', 'Leishmaniasis is a neglected tropical disease which affects approx. 12 million individuals worldwide and caused by parasite Leishmania. The current drugs used in the treatment of Leishmaniasis are highly toxic and has seen widespread emergence of drug resistant strains which necessitates the need for the development of new therapeutic options. The high throughput screen data available has made it possible to generate computational predictive models which have the ability to assess the active scaffolds in a chemical library followed by its ADME/toxicity properties in the biological trials.'),
(95806, 2013, 'bmc', 'Agalma: an automated phylogenomics workflow', 'Dunn, Casey W|Howison, Mark|Zapata, Felipe', 'Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, USA. casey_dunn@brown.edu.|Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, USA. casey_dunn@brown.edu.|Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, USA. casey_dunn@brown.edu.', 'United States|United States|United States', 0, 'Gene Expression Profiling|Genome|Genomics|Phylogeny|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-14-330', '24252138', 'In the past decade, transcriptome data have become an important component of many phylogenetic studies. They are a cost-effective source of protein-coding gene sequences, and have helped projects grow from a few genes to hundreds or thousands of genes. Phylogenetic studies now regularly include genes from newly sequenced transcriptomes, as well as publicly available transcriptomes and genomes. Implementing such a phylogenomic study, however, is computationally intensive, requires the coordinated use of many complex software tools, and includes multiple steps for which no published tools exist. Phylogenomic studies have therefore been manual or semiautomated. In addition to taking considerable user time, this makes phylogenomic analyses difficult to reproduce, compare, and extend. In addition, methodological improvements made in the context of one study often cannot be easily applied and evaluated in the context of other studies.'),
(95807, 2013, 'bmc', 'YHap: a population model for probabilistic assignment of Y haplogroups from re-sequencing data', 'Zhang, Fan|Chen, Ruoyan|Liu, Dongbing|Yao, Xiaotian|Li, Guoqing|Jin, Yabin|Yu, Chang|Li, Yingrui|Coin, Lachlan J M', 'BGI-shenzhen, Shenzhen, China. yuchang@genomics.org.cn.|BGI-shenzhen, Shenzhen, China. yuchang@genomics.org.cn.|BGI-shenzhen, Shenzhen, China. yuchang@genomics.org.cn.|BGI-shenzhen, Shenzhen, China. yuchang@genomics.org.cn.|BGI-shenzhen, Shenzhen, China. yuchang@genomics.org.cn.|BGI-shenzhen, Shenzhen, China. yuchang@genomics.org.cn.|BGI-shenzhen, Shenzhen, China. yuchang@genomics.org.cn.|BGI-shenzhen, Shenzhen, China. yuchang@genomics.org.cn.|BGI-shenzhen, Shenzhen, China. yuchang@genomics.org.cn.', 'China|China|China|China|China|China|China|China|China', 0, 'Algorithms|Chromosomes, Human, Y|Genetic Variation|Genetics, Population|Genome, Human|Genotype|Haplotypes|Humans|Male|Mutation|Predictive Value of Tests|Probability|Sequence Analysis, DNA|Tandem Repeat Sequences', 'Journal Article', '10.1186/1471-2105-14-331', '24252171', 'Y haplogroup analyses are an important component of genealogical reconstruction, population genetic analyses, medical genetics and forensics. These fields are increasingly moving towards use of low-coverage, high throughput sequencing. While there have been methods recently proposed for assignment of Y haplogroups on the basis of high-coverage sequence data, assignment on the basis of low-coverage data remains challenging.'),
(95808, 2013, 'bmc', 'Reconciliation-based detection of co-evolving gene families', 'Chan, Yao-ban|Ranwez, Vincent|Scornavacca, Celine', 'BGI-shenzhen, Shenzhen, China. yuchang@genomics.org.cn.|BGI-shenzhen, Shenzhen, China. yuchang@genomics.org.cn.|ISEM, Université Montpellier 2, Montpellier, 34095, France. celine.scornavacca@univ-montp2.fr.', 'China|China|France', 0, 'Computer Simulation|Evolution, Molecular|Genome, Bacterial|Multigene Family|Phylogeny|Probability|Proteobacteria|Random Allocation|Segmental Duplications, Genomic', 'Comparative Study', '10.1186/1471-2105-14-332', '24252193', 'Genes located in the same chromosome region share common evolutionary events more often than other genes (e.g. a segmental duplication of this region). Their evolution may also be related if they are involved in the same protein complex or biological process. Identifying co-evolving genes can thus shed light on ancestral genome structures and functional gene interactions.'),
(95809, 2013, 'bmc', 'Similarity maps and hierarchical clustering for annotating FT-IR spectral images', 'Zhong, Qiaoyong|Yang, Chen|Großerüschkamp, Frederik|Kallenbach-Thieltges, Angela|Serocka, Peter|Gerwert, Klaus|Mosig, Axel', 'Department of Biophysics, Ruhr University Bochum, Universitätsstraße 150, 44801 Bochum, Germany. axel.mosig@bph.rub.de.|Department of Biophysics, Ruhr University Bochum, Universitätsstraße 150, 44801 Bochum, Germany. axel.mosig@bph.rub.de.|Department of Biophysics, Ruhr University Bochum, Universitätsstraße 150, 44801 Bochum, Germany. axel.mosig@bph.rub.de.|Department of Biophysics, Ruhr University Bochum, Universitätsstraße 150, 44801 Bochum, Germany. axel.mosig@bph.rub.de.|Department of Biophysics, Ruhr University Bochum, Universitätsstraße 150, 44801 Bochum, Germany. axel.mosig@bph.rub.de.|Department of Biophysics, Ruhr University Bochum, Universitätsstraße 150, 44801 Bochum, Germany. axel.mosig@bph.rub.de.|Department of Biophysics, Ruhr University Bochum, Universitätsstraße 150, 44801 Bochum, Germany. axel.mosig@bph.rub.de.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 9, 'Adenocarcinoma|Algorithms|Cluster Analysis|Colorectal Neoplasms|Database Management Systems|Databases, Factual|Humans|Microscopy, Fluorescence|Monte Carlo Method|Reproducibility of Results|Spectroscopy, Fourier Transform Infrared|Spectrum Analysis, Raman|Tissue Engineering', 'Comparative Study', '10.1186/1471-2105-14-333', '24255945', 'Unsupervised segmentation of multi-spectral images plays an important role in annotating infrared microscopic images and is an essential step in label-free spectral histopathology. In this context, diverse clustering approaches have been utilized and evaluated in order to achieve segmentations of Fourier Transform Infrared (FT-IR) microscopic images that agree with histopathological characterization.'),
(95810, 2013, 'bmc', 'Fastphylo: fast tools for phylogenetics', 'Khan, Mehmood Alam|Elias, Isaac|Sjölund, Erik|Nylander, Kristina|Guimera, Roman Valls|Schobesberger, Richard|Schmitzberger, Peter|Lagergren, Jens|Arvestad, Lars', 'KTH Royal Institute of Technology, Science for Life Laboratory, School of Computer Science and Communication, Department of Computational Biology, Solna, Sweden. malagori@kth.se.|KTH Royal Institute of Technology, Science for Life Laboratory, School of Computer Science and Communication, Department of Computational Biology, Solna, Sweden. malagori@kth.se.|KTH Royal Institute of Technology, Science for Life Laboratory, School of Computer Science and Communication, Department of Computational Biology, Solna, Sweden. malagori@kth.se.|KTH Royal Institute of Technology, Science for Life Laboratory, School of Computer Science and Communication, Department of Computational Biology, Solna, Sweden. malagori@kth.se.|KTH Royal Institute of Technology, Science for Life Laboratory, School of Computer Science and Communication, Department of Computational Biology, Solna, Sweden. malagori@kth.se.|KTH Royal Institute of Technology, Science for Life Laboratory, School of Computer Science and Communication, Department of Computational Biology, Solna, Sweden. malagori@kth.se.|KTH Royal Institute of Technology, Science for Life Laboratory, School of Computer Science and Communication, Department of Computational Biology, Solna, Sweden. malagori@kth.se.|KTH Royal Institute of Technology, Science for Life Laboratory, School of Computer Science and Communication, Department of Computational Biology, Solna, Sweden. malagori@kth.se.|KTH Royal Institute of Technology, Science for Life Laboratory, School of Computer Science and Communication, Department of Computational Biology, Solna, Sweden. malagori@kth.se.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 6, 'Algorithms|Amino Acid Sequence|Biological Evolution|Computational Biology|Language|Memory|Multigene Family|Phylogeny|Software', 'Comparative Study', '10.1186/1471-2105-14-334', '24255987', 'Distance methods are ubiquitous tools in phylogenetics. Their primary purpose may be to reconstruct evolutionary history, but they are also used as components in bioinformatic pipelines. However, poor computational efficiency has been a constraint on the applicability of distance methods on very large problem instances.'),
(95811, 2013, 'bmc', 'Detecting small plant peptides using SPADA (Small Peptide Alignment Discovery Application)', 'Zhou, Peng|Silverstein, Kevin At|Gao, Liangliang|Walton, Jonathan D|Nallu, Sumitha|Guhlin, Joseph|Young, Nevin D', 'Department of Plant Pathology, University of Minnesota, St, Paul, Minnesota 55108, USA. neviny@umn.edu.|Department of Plant Pathology, University of Minnesota, St, Paul, Minnesota 55108, USA. neviny@umn.edu.|Department of Plant Pathology, University of Minnesota, St, Paul, Minnesota 55108, USA. neviny@umn.edu.|Department of Plant Pathology, University of Minnesota, St, Paul, Minnesota 55108, USA. neviny@umn.edu.|Department of Plant Pathology, University of Minnesota, St, Paul, Minnesota 55108, USA. neviny@umn.edu.|Department of Plant Pathology, University of Minnesota, St, Paul, Minnesota 55108, USA. neviny@umn.edu.|Department of Plant Pathology, University of Minnesota, St, Paul, Minnesota 55108, USA. neviny@umn.edu.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Amanita|Amino Acid Sequence|Arabidopsis|Genome, Plant|Medicago truncatula|Peptides|Predictive Value of Tests|Sequence Alignment|Sequence Homology|Software', 'Journal Article', '10.1186/1471-2105-14-335', '24256031', 'Small peptides encoded as one- or two-exon genes in plants have recently been shown to affect multiple aspects of plant development, reproduction and defense responses. However, popular similarity search tools and gene prediction techniques generally fail to identify most members belonging to this class of genes. This is largely due to the high sequence divergence among family members and the limited availability of experimentally verified small peptides to use as training sets for homology search and ab initio prediction. Consequently, there is an urgent need for both experimental and computational studies in order to further advance the accurate prediction of small peptides.'),
(95812, 2013, 'bmc', 'A novel phenotypic dissimilarity method for image-based high-throughput screens', 'Zhang, Xian|Boutros, Michael', 'German Cancer Research Center (DKFZ), Div, Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. xianzhang@gmail.com.|German Cancer Research Center (DKFZ), Div, Signaling and Functional Genomics and Department of Cell and Molecular Biology, Medical Faculty Mannheim, Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. xianzhang@gmail.com.', 'Germany|Germany', 10, 'Animals|Caenorhabditis elegans|Cluster Analysis|Databases, Factual|Drosophila melanogaster|HeLa Cells|High-Throughput Screening Assays|Humans|Phenotype|RNA Interference|RNA, Small Interfering|Reproducibility of Results|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-14-336', '24256072', 'Discovering functional relationships of genes through cell-based phenotyping has become an important approach in functional genomics. High-throughput imaging offers the ability to quantitatively assess complex phenotypes after perturbation by RNA interference (RNAi). Such image-based high-throughput RNAi screening studies have facilitated the discovery of novel components of gene networks and their interactions. Images generated by automated microscopy are typically analyzed by extracting quantitative features of individual cells, resulting in large multidimensional data sets. Robust and sensitive methods to interpret these data sets and to derive biologically relevant information in a high-throughput and unbiased manner remain to be developed.'),
(95813, 2013, 'bmc', 'Probabilistic alignment leads to improved accuracy and read coverage for bisulfite sequencing data', 'Hong, Changjin|Clement, Nathan L|Clement, Spencer|Hammoud, Saher Sue|Carrell, Douglas T|Cairns, Bradley R|Snell, Quinn|Clement, Mark J|Johnson, William Evan', 'Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA. wej@bu.edu.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA. wej@bu.edu.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA. wej@bu.edu.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA. wej@bu.edu.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA. wej@bu.edu.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA. wej@bu.edu.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA. wej@bu.edu.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA. wej@bu.edu.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA. wej@bu.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Base Sequence|Computer Simulation|DNA Methylation|Genome, Human|Humans|Probability|Sequence Alignment|Sequence Analysis, DNA|Software|Sulfites', 'Journal Article', '10.1186/1471-2105-14-337', '24261665', 'DNA methylation has been linked to many important biological phenomena. Researchers have recently begun to sequence bisulfite treated DNA to determine its pattern of methylation. However, sequencing reads from bisulfite-converted DNA can vary significantly from the reference genome because of incomplete bisulfite conversion, genome variation, sequencing errors, and poor quality bases. Therefore, it is often difficult to align reads to the correct locations in the reference genome. Furthermore, bisulfite sequencing experiments have the additional complexity of having to estimate the DNA methylation levels within the sample.'),
(95814, 2013, 'bmc', 'MetSizeR: selecting the optimal sample size for metabolomic studies using an analysis based approach', 'Nyamundanda, Gift|Gormley, Isobel Claire|Fan, Yue|Gallagher, William M|Brennan, Lorraine', 'School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.', 'Ireland|Ireland|Ireland|Ireland|Ireland', 0, 'Algorithms|Animals|Computer Simulation|Longitudinal Studies|Metabolomics|Models, Statistical|Nuclear Magnetic Resonance, Biomolecular|Pilot Projects|Principal Component Analysis|Sample Size|Software', 'Journal Article', '10.1186/1471-2105-14-338', '24261687', 'Determining sample sizes for metabolomic experiments is important but due to the complexity of these experiments, there are currently no standard methods for sample size estimation in metabolomics. Since pilot studies are rarely done in metabolomics, currently existing sample size estimation approaches which rely on pilot data can not be applied.'),
(95815, 2013, 'bmc', 'VarBin, a novel method for classifying true and false positive variants in NGS data', 'Durtschi, Jacob|Margraf, Rebecca L|Coonrod, Emily M|Mallempati, Kalyan C|Voelkerding, Karl V', 'School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.', 'Ireland|Ireland|Ireland|Ireland|Ireland', 7, 'Cluster Analysis|Exome|Female|Genetic Predisposition to Disease|Genetic Variation|Genome|Genomic Library|Heterozygote|Humans|Likelihood Functions|Male|Pedigree|Polymorphism, Single Nucleotide|Predictive Value of Tests|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-14-S13-S2', '24266885', 'Variant discovery for rare genetic diseases using Illumina genome or exome sequencing involves screening of up to millions of variants to find only the one or few causative variant(s). Sequencing or alignment errors create false positive variants, which are often retained in the variant screening process. Methods to remove false positive variants often retain many false positive variants. This report presents VarBin, a method to prioritize variants based on a false positive variant likelihood prediction.'),
(95816, 2013, 'bmc', 'A cross disciplinary study of link decay and the effectiveness of mitigation techniques', 'Hennessey, Jason|Ge, Steven', 'School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.', 'Ireland|Ireland', 0, 'Archives|Bibliography as Topic|Databases, Factual|Humans|Internet|Publishing|Software Design|Time Factors', 'Journal Article', '10.1186/1471-2105-14-S14-S5', '24266891', 'The dynamic, decentralized world-wide-web has become an essential part of scientific research and communication. Researchers create thousands of web sites every year to share software, data and services. These valuable resources tend to disappear over time. The problem has been documented in many subject areas. Our goal is to conduct a cross-disciplinary investigation of the problem and test the effectiveness of existing remedies.'),
(95817, 2013, 'bmc', 'Breast cancer prediction using genome wide single nucleotide polymorphism data', 'Hajiloo, Mohsen|Damavandi, Babak|Hooshsadat, Metanat|Sangi, Farzad|Mackey, John R|Cass, Carol E|Greiner, Russell|Damaraju, Sambasivarao', 'School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland', 10, 'Adult|Algorithms|Area Under Curve|Breast Neoplasms|Canada|Case-Control Studies|Female|Gene Frequency|Genetic Predisposition to Disease|Genome-Wide Association Study|Humans|Phenotype|Polymorphism, Single Nucleotide|Risk Factors', 'Journal Article', '10.1186/1471-2105-14-S13-S3', '24266904', 'This paper introduces and applies a genome wide predictive study to learn a model that predicts whether a new subject will develop breast cancer or not, based on her SNP profile.'),
(95818, 2013, 'bmc', 'Homology modeling, molecular docking, and molecular dynamics simulations elucidated xcexb1-fetoprotein binding modes', 'Shen, Jie|Zhang, Wenqian|Fang, Hong|Perkins, Roger|Tong, Weida|Hong, Huixiao', 'School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.|School of Mathematical Sciences, University College Dublin, Dublin, Ireland. claire.gormley@ucd.ie.', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland', 54, 'Amino Acid Sequence|Animals|Binding Sites|Ligands|Models, Molecular|Molecular Dynamics Simulation|Molecular Sequence Data|Protein Structure, Tertiary|Rabbits|Rats|Sequence Alignment|alpha-Fetoproteins', 'Journal Article', '10.1186/1471-2105-14-S14-S6', '24266910', 'An important mechanism of endocrine activity is chemicals entering target cells via transport proteins and then interacting with hormone receptors such as the estrogen receptor (ER). xcexb1-Fetoprotein (AFP) is a major transport protein in rodent serum that can bind and sequester estrogens, thus preventing entry to the target cell and where they could otherwise induce ER-mediated endocrine activity. Recently, we reported rat AFP binding affinities for a large set of structurally diverse chemicals, including 53 binders and 72 non-binders. However, the lack of three-dimensional (3D) structures of rat AFP hinders further understanding of the structural dependence for binding. Therefore, a 3D structure of rat AFP was built using homology modeling in order to elucidate rat AFP-ligand binding modes through docking analyses and molecular dynamics (MD) simulations.'),
(95819, 2013, 'bmc', 'zipHMMlib: a highly optimised HMM library exploiting repetitions in the input to speed up the forward algorithm', 'Sand, Andreas|Kristiansen, Martin|Pedersen, Christian N S|Mailund, Thomas', 'Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.', 'Denmark|Denmark|Denmark|Denmark', 0, 'Algorithms|Animals|Computer Simulation|Gorilla gorilla|Humans|Likelihood Functions|Markov Chains|Observational Studies as Topic|Pan troglodytes|Peptide Library|Pongo|Probability|Software|Time Factors', 'Journal Article', '10.1186/1471-2105-14-339', '24266924', 'Hidden Markov models are widely used for genome analysis as they combine ease of modelling with efficient analysis algorithms. Calculating the likelihood of a model using the forward algorithm has worst case time complexity linear in the length of the sequence and quadratic in the number of states in the model. For genome analysis, however, the length runs to millions or billions of observations, and when maximising the likelihood hundreds of evaluations are often needed. A time efficient forward algorithm is therefore a key ingredient in an efficient hidden Markov model library.'),
(95820, 2013, 'bmc', 'Fuzzy support vector machine: an efficient rule-based classification technique for microarrays', 'Hajiloo, Mohsen|Rabiee, Hamid R|Anooshahpour, Mahdi', 'Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.', 'Denmark|Denmark|Denmark', 9, 'Algorithms|Cluster Analysis|Colonic Neoplasms|Computational Biology|Decision Trees|Fuzzy Logic|Gene Expression|Gene Expression Profiling|Humans|Leukemia|Male|Prostatic Neoplasms|Protein Array Analysis|Software|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-14-S13-S4', '24266942', 'The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification.'),
(95821, 2013, 'bmc', 'Identification and characterization of plastid-type proteins from sequence-attributed features using machine learning', 'Kaundal, Rakesh|Sahu, Sitanshu S|Verma, Ruchi|Weirick, Tyler', 'Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.', 'Denmark|Denmark|Denmark|Denmark', 8, 'Amino Acids|Artificial Intelligence|Chloroplast Proteins|Databases, Protein|Dipeptides|Plastids|Protein Structure, Tertiary|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-14-S14-S7', '24266945', 'Plastids are an important component of plant cells, being the site of manufacture and storage of chemical compounds used by the cell, and contain pigments such as those used in photosynthesis, starch synthesis/storage, cell color etc. They are essential organelles of the plant cell, also present in algae. Recent advances in genomic technology and sequencing efforts is generating a huge amount of DNA sequence data every day. The predicted proteome of these genomes needs annotation at a faster pace. In view of this, one such annotation need is to develop an automated system that can distinguish between plastid and non-plastid proteins accurately, and further classify plastid-types based on their functionality. We compared the amino acid compositions of plastid proteins with those of non-plastid ones and found significant differences, which were used as a basis to develop various feature-based prediction models using similarity-search and machine learning.'),
(95822, 2013, 'bmc', 'BinAligner: a heuristic method to align biological networks', 'Yang, Jialiang|Li, Jun|Grünewald, Stefan|Wan, Xiu-Feng', 'Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. asand@birc.au.dk.', 'Denmark|Denmark|Denmark|Denmark', 5, 'Algorithms|Herpesvirus 3, Human|Herpesvirus 8, Human|Open Reading Frames|Viral Proteins', 'Journal Article', '10.1186/1471-2105-14-S14-S8', '24266981', 'The advances in high throughput omics technologies have made it possible to characterize molecular interactions within and across various species. Alignments and comparison of molecular networks across species will help detect orthologs and conserved functional modules and provide insights on the evolutionary relationships of the compared species. However, such analyses are not trivial due to the complexity of network and high computational cost. Here we develop a mixture of global and local algorithm, BinAligner, for network alignments. Based on the hypotheses that the similarity between two vertices across networks would be context dependent and that the information from the edges and the structures of subnetworks can be more informative than vertices alone, two scoring schema, 1-neighborhood subnetwork and graphlet, were introduced to derive the scoring matrices between networks, besides the commonly used scoring scheme from vertices. Then the alignment problem is formulated as an assignment problem, which is solved by the combinatorial optimization algorithm, such as the Hungarian method. The proposed algorithm was applied and validated in aligning the protein-protein interaction network of Kaposis sarcoma associated herpesvirus (KSHV) and that of varicella zoster virus (VZV). Interestingly, we identified several putative functional orthologous proteins with similar functions but very low sequence similarity between the two viruses. For example, KSHV open reading frame 56 (ORF56) and VZV ORF55 are helicase-primase subunits with sequence identity 14.6%, and KSHV ORF75 and VZV ORF44 are tegument proteins with sequence identity 15.3%. These functional pairs can not be identified if one restricts the alignment into orthologous protein pairs. In addition, BinAligner identified a conserved pathway between two viruses, which consists of 7 orthologous protein pairs and these proteins are connected by conserved links. This pathway might be crucial for virus packing and infection. '),
(95823, 2013, 'bmc', 'Reverse causal reasoning: applying qualitative causal knowledge to the interpretation of high-throughput data', 'Catlett, Natalie L|Bargnesi, Anthony J|Ungerer, Stephen|Seagaran, Toby|Ladd, William|Elliston, Keith O|Pratt, Dexter', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States|United States|United States', 62, 'Algorithms|Animals|Breast|Endothelium, Vascular|Epithelial Cells|Gene Expression Profiling|Genome, Human|High-Throughput Nucleotide Sequencing|Histone-Lysine N-Methyltransferase|Humans|Insulin Resistance|Knowledge Bases|Mice|Microarray Analysis|Molecular Probes|Nuclear Proteins', 'Journal Article', '10.1186/1471-2105-14-340', '24266983', 'Gene expression profiling and other genome-scale measurement technologies provide comprehensive information about molecular changes resulting from a chemical or genetic perturbation, or disease state. A critical challenge is the development of methods to interpret these large-scale data sets to identify specific biological mechanisms that can provide experimentally verifiable hypotheses and lead to the understanding of disease and drug action.'),
(95824, 2013, 'bmc', 'Probabilistic inference and ranking of gene regulatory pathways as a shortest-path problem', 'Jensen, James D|Jensen, Daniel M|Clement, Mark J|Snell, Quinn O', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States', 0, 'Algorithms|Computational Biology|Decision Trees|Gene Expression|Gene Expression Regulation|Gene Regulatory Networks|Humans|Linear Models|Species Specificity', 'Comparative Study', '10.1186/1471-2105-14-S13-S5', '24266986', 'Since the advent of microarray technology, numerous methods have been devised to infer gene regulatory relationships from gene expression data. Many approaches that infer entire regulatory networks. This produces results that are rich in information and yet so complex that they are often of limited usefulness for researchers. One alternative unit of regulatory interactions is a linear path between genes. Linear paths are more comprehensible than networks and still contain important information. Such paths can be extracted from inferred regulatory networks or inferred directly. Since criteria for inferring networks generally differs from criteria for inferring paths, indirect and direct inference of paths may achieve different results.'),
(95825, 2013, 'bmc', 'PHDcleav: a SVM based method for predicting human Dicer cleavage sites using sequence and secondary structure of miRNA precursors', 'Ahmed, Firoz|Kaundal, Rakesh|Raghava, Gajendra P S', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States', 0, 'Base Sequence|Gene Silencing|MicroRNAs|Nucleic Acid Conformation|RNA Precursors|Ribonuclease III|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-14-S14-S9', '24267009', 'Dicer, an RNase III enzyme, plays a vital role in the processing of pre-miRNAs for generating the miRNAs. The structural and sequence features on pre-miRNA which can facilitate position and efficiency of cleavage are not well known. A precise cleavage by Dicer is crucial because an inaccurate processing can produce miRNA with different seed regions which can alter the repertoire of target genes.'),
(95826, 2013, 'bmc', 'Classification of genomic signals using dynamic time warping', 'Skutkova, Helena|Vitek, Martin|Babula, Petr|Kizek, Rene|Provaznik, Ivo', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States', 22, 'Actins|Animals|Base Sequence|Biological Evolution|Chickens|Genetic Phenomena|Genomics|Humans|Macaca mulatta|Molecular Dynamics Simulation|Phylogeny|Sequence Alignment|Signal Transduction|Time Factors', 'Journal Article', '10.1186/1471-2105-14-S10-S1', '24267034', 'Classification methods of DNA most commonly use comparison of the differences in DNA symbolic records, which requires the global multiple sequence alignment. This solution is often inappropriate, causing a number of imprecisions and requires additional user intervention for exact alignment of the similar segments. The similar segments in DNA represented as a signal are characterized by a similar shape of the curve. The DNA alignment in genomic signals may adjust whole sections not only individual symbols. The dynamic time warping (DTW) is suitable for this purpose and can replace the multiple alignment of symbolic sequences in applications, such as phylogenetic analysis.'),
(95827, 2013, 'bmc', 'Directional Darwinian Selection in proteins', 'McClellan, David A', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States', 0, 'Confidence Intervals|Evolution, Molecular|Genetic Speciation|Genome, Mitochondrial|Humans|Selection, Genetic|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1186/1471-2105-14-S13-S6', '24267049', 'Molecular evolution is a very active field of research, with several complementary approaches, including dN/dS, HON90, MM01, and others. Each has documented strengths and weaknesses, and no one approach provides a clear picture of how natural selection works at the molecular level. The purpose of this work is to present a simple new method that uses quantitative amino acid properties to identify and characterize directional selection in proteins.'),
(95828, 2013, 'bmc', 'Evaluating a linear k-mer model for protein-DNA interactions using high-throughput SELEX data', 'Kähärä, Juhani|Lähdesmäki, Harri', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States', 5, 'Algorithms|DNA|DNA-Binding Proteins|GATA1 Transcription Factor|High-Throughput Nucleotide Sequencing|Humans|Linear Models|NFATC Transcription Factors|Oligonucleotide Array Sequence Analysis|Protein Binding|Protein Interaction Mapping|Proteins|Regulatory Factor X Transcription Factors|Transcription Factors', 'Journal Article', '10.1186/1471-2105-14-S10-S2', '24267147', 'Transcription factor (TF) binding to DNA can be modeled in a number of different ways. It is highly debated which modeling methods are the best, how the models should be built and what can they be applied to. In this study a linear k-mer model proposed for predicting TF specificity in protein binding microarrays (PBM) is applied to a high-throughput SELEX data and the question of how to choose the most informative k-mers to the binding model is studied. We implemented the standard cross-validation scheme to reduce the number of k-mers in the model and observed that the number of k-mers can often be reduced significantly without a great negative effect on prediction accuracy. We also found that the later SELEX enrichment cycles provide a much better discrimination between bound and unbound sequences as model prediction accuracies increased for all proteins together with the cycle number. We compared prediction performance of k-mer and position specific weight matrix (PWM) models derived from the same SELEX data. Consistent with previous results on PBM data, performance of the k-mer model was on average 9%-units better. For the 15 proteins in the SELEX data set with medium enrichment cycles, classification accuracies were on average 71% and 62% for k-mer and PWMs, respectively. Finally, the k-mer model trained with SELEX data was evaluated on ChIP-seq data demonstrating substantial improvements for some proteins. For protein GATA1 the model can distinquish between true ChIP-seq peaks and negative peaks. For proteins RFX3 and NFATC1 the performance of the model was no better than chance. '),
(95829, 2013, 'bmc', 'A Bayesian approach for parameter estimation in the extended clock gene circuit of Arabidopsis thaliana', 'Higham, Catherine F|Husmeier, Dirk', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States', 0, 'Arabidopsis|Arabidopsis Proteins|Bayes Theorem|Circadian Clocks|DNA-Binding Proteins|Gene Expression Regulation, Plant|Promoter Regions, Genetic|Protein Binding|Protein Processing, Post-Translational|Repressor Proteins|Transcription Factors', 'Journal Article', '10.1186/1471-2105-14-S10-S3', '24267177', 'The circadian clock is an important molecular mechanism that enables many organisms to anticipate and adapt to environmental change. Pokhilko et al. recently built a deterministic ODE mathematical model of the plant circadian clock in order to understand the behaviour, mechanisms and properties of the system. The model comprises 30 molecular species (genes, mRNAs and proteins) and over 100 parameters. The parameters have been fitted heuristically to available gene expression time series data and the calibrated model has been shown to reproduce the behaviour of the clock components. Ongoing work is extending the clock model to cover downstream effects, in particular metabolism, necessitating further parameter estimation and model selection. This work investigates the challenges facing a full Bayesian treatment of parameter estimation. Using an efficient adaptive MCMC proposed by Haario et al. and working in a high performance computing setting, we quantify the posterior distribution around the proposed parameter values and explore the basin of attraction. We investigate if Bayesian inference is feasible in this high dimensional setting and thoroughly assess convergence and mixing with different statistical diagnostics, to prevent apparent convergence in some domains masking poor mixing in others. '),
(95830, 2013, 'bmc', 'Comparative studies of differential gene calling using RNA-Seq data', 'Zheng, Ximeng|Moriyama, Etsuko N', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States', 21, 'Animals|Aphids|Chlamydomonas reinhardtii|Gene Expression|Humans|Models, Statistical|Molecular Dynamics Simulation|Molecular Sequence Data|RNA Splice Sites|Sequence Alignment|Sequence Analysis, RNA|Species Specificity|Transcription, Genetic', 'Comparative Study', '10.1186/1471-2105-14-S13-S7', '24267181', 'With its massive amount of data, gene-expression profiling by RNA-Seq has many advantanges compared with microarray experiments. RNA-Seq analysis, however, is fundamentally different from microarray data analysis. Techniques developed for analyzing microarray data thus cannot be directly applicable for the digital gene expression data. Several statistical methods have been developed for identifying differentially expressed genes specifically from RNA-Seq data over the past few years.'),
(95831, 2013, 'bmc', 'Computing preimages of Boolean networks', 'Klotz, Johannes|Bossert, Martin|Schober, Steffen', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States', 0, 'Algorithms|Computational Biology|Computer Simulation|Escherichia coli|Gene Regulatory Networks|Models, Genetic|Probability', 'Journal Article', '10.1186/1471-2105-14-S10-S4', '24267277', 'In this paper we present an algorithm based on the sum-product algorithm that finds elements in the preimage of a feed-forward Boolean networks given an output of the network. Our probabilistic method runs in linear time with respect to the number of nodes in the network. We evaluate our algorithm for randomly constructed Boolean networks and a regulatory network of Escherichia coli and found that it gives a valid solution in most cases. '),
(95832, 2013, 'bmc', 'Integrative network-based Bayesian analysis of diverse genomics data', 'Wang, Wenting|Baladandayuthapani, Veerabhadran|Holmes, Chris C|Do, Kim-Anh', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States', 8, 'Atlases as Topic|Bayes Theorem|Computer Simulation|Genomics|Glioblastoma|Humans|MicroRNAs|Neoplasms|Normal Distribution|RNA, Messenger|Software|Survival Analysis|Systems Integration', 'Journal Article', '10.1186/1471-2105-14-S13-S8', '24267288', 'In order to better understand cancer as a complex disease with multiple genetic and epigenetic factors, it is vital to model the fundamental biological relationships among these alterations as well as their relationships with important clinical outcomes.'),
(95833, 2013, 'bmc', 'ZebIAT, an image analysis tool for registering zebrafish embryos and quantifying cancer metastasis', 'Annila, Teppo|Lihavainen, Eero|Marques, Ines J|Williams, Darren R|Yli-Harja, Olli|Ribeiro, Andre', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States|United States', 10, 'Animals|Animals, Genetically Modified|Automation|Cell Line, Tumor|Disease Models, Animal|Disease Progression|Embryonic Development|Humans|Image Processing, Computer-Assisted|Organisms, Genetically Modified|Pancreatic Neoplasms|Random Allocation|Zebrafish', 'Journal Article', '10.1186/1471-2105-14-S10-S5', '24267347', 'Zebrafish embryos have recently been established as a xenotransplantation model of the metastatic behaviour of primary human tumours. Current tools for automated data extraction from the microscope images are restrictive concerning the developmental stage of the embryos, usually require laborious manual image preprocessing, and, in general, cannot characterize the metastasis as a function of the internal organs.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(95834, 2013, 'bmc', 'Dinosolve: a protein disulfide bonding prediction server using context-based features to enhance prediction accuracy', 'Yaseen, Ashraf|Li, Yaohang', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States', 14, 'Algorithms|Amino Acid Sequence|Cysteine|Disulfides|Neural Networks (Computer)|Predictive Value of Tests|Protein Folding', 'Journal Article', '10.1186/1471-2105-14-S13-S9', '24267383', 'Disulfide bonds play an important role in protein folding and structure stability. Accurately predicting disulfide bonds from protein sequences is important for modeling the structural and functional characteristics of many proteins.'),
(95835, 2013, 'bmc', 'Proceedings of the 2013 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference', 'Wren, Jonathan D|Dozmorov, Mikhail G|Burian, Dennis|Kaundal, Rakesh|Perkins, Andy|Perkins, Ed|Kupfer, Doris M|Springer, Gordon K', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Awards and Prizes|Computational Biology|Congresses as Topic|Humans|Proteins|Transcriptome', 'Introductory Journal Article', '10.1186/1471-2105-14-S14-S1', '24267415', 'The tenth annual conference of the MidSouth Computational Biology and Bioinformatics Society (MCBIOS 2013), The 10th Anniversary in a Decade of Change: Discovery in a Sea of Data, took place at the Stoney Creek Inn & Conference Center in Columbia, Missouri on April 5-6, 2013. This years Conference Chairs were Gordon Springer and Chi-Ren Shyu from the University of Missouri and Edward Perkins from the US Army Corps of Engineers Engineering Research and Development Center, who is also the current MCBIOS President (2012-3). There were 151 registrants and a total of 111 abstracts (51 oral presentations and 60 poster session abstracts). '),
(95836, 2013, 'bmc', 'Towards human-computer synergetic analysis of large-scale biological data', 'Singh, Rahul|Yang, Hui|Dalziel, Ben|Asarnow, Daniel|Murad, William|Foote, David|Gormley, Matthew|Stillman, Jonathan|Fisher, Susan', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Computers|Female|Gene Expression|Genomics|Humans|Models, Molecular|Pregnancy|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1186/1471-2105-14-S14-S10', '24267485', 'Advances in technology have led to the generation of massive amounts of complex and multifarious biological data in areas ranging from genomics to structural biology. The volume and complexity of such data leads to significant challenges in terms of its analysis, especially when one seeks to generate hypotheses or explore the underlying biological processes. At the state-of-the-art, the application of automated algorithms followed by perusal and analysis of the results by an expert continues to be the predominant paradigm for analyzing biological data. This paradigm works well in many problem domains. However, it also is limiting, since domain experts are forced to apply their instincts and expertise such as contextual reasoning, hypothesis formulation, and exploratory analysis after the algorithm has produced its results. In many areas where the organization and interaction of the biological processes is poorly understood and exploratory analysis is crucial, what is needed is to integrate domain expertise during the data analysis process and use it to drive the analysis itself.'),
(95837, 2013, 'bmc', 'Multi-scale Gaussian representation and outline-learning based cell image segmentation', 'Farhan, Muhammad|Ruusuvuori, Pekka|Emmenlauer, Mario|Rämö, Pauli|Dehio, Christoph|Yli-Harja, Olli', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Cell Division|Cells, Cultured|Cytoplasm|Drosophila melanogaster|HeLa Cells|High-Throughput Screening Assays|Humans|Image Enhancement|Microscopy, Fluorescence|Normal Distribution|Protein Processing, Post-Translational|Random Allocation', 'Journal Article', '10.1186/1471-2105-14-S10-S6', '24267488', 'High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation.'),
(95838, 2013, 'bmc', 'A systems approach for analysis of high content screening assay data with topic modeling', 'Bisgin, Halil|Chen, Minjun|Wang, Yuping|Kelly, Reagan|Fang, Hong|Xu, Xiaowei|Tong, Weida', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Apoptosis|Cells, Cultured|DNA Damage|Data Mining|Databases, Genetic|Hepatocytes|High-Throughput Screening Assays|Lysosomes|Male|Mitochondria|Necrosis|Rats|Rats, Sprague-Dawley|Toxicogenetics', 'Journal Article', '10.1186/1471-2105-14-S14-S11', '24267543', 'High Content Screening (HCS) has become an important tool for toxicity assessment, partly due to its advantage of handling multiple measurements simultaneously. This approach has provided insight and contributed to the understanding of systems biology at cellular level. To fully realize this potential, the simultaneously measured multiple endpoints from a live cell should be considered in a probabilistic relationship to assess the cells condition to response stress from a treatment, which poses a great challenge to extract hidden knowledge and relationships from these measurements.'),
(95839, 2013, 'bmc', 'Modeling of 2D diffusion processes based on microscopy data: parameter estimation and practical identifiability analysis', 'Hock, Sabrina|Hasenauer, Jan|Theis, Fabian J', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States', 13, 'Cell Membrane Permeability|Cell Movement|Chemokine CCL21|Dendritic Cells|Diffusion|Likelihood Functions|Lymphatic Vessels|Microscopy, Fluorescence|Models, Molecular|Signal Transduction', 'Journal Article', '10.1186/1471-2105-14-S10-S7', '24267545', 'Diffusion is a key component of many biological processes such as chemotaxis, developmental differentiation and tissue morphogenesis. Since recently, the spatial gradients caused by diffusion can be assessed in-vitro and in-vivo using microscopy based imaging techniques. The resulting time-series of two dimensional, high-resolutions images in combination with mechanistic models enable the quantitative analysis of the underlying mechanisms. However, such a model-based analysis is still challenging due to measurement noise and sparse observations, which result in uncertainties of the model parameters.'),
(95840, 2013, 'bmc', 'A study and benchmark of DNcon: a method for protein residue-residue contact prediction using deep networks', 'Eickholt, Jesse|Cheng, Jianlin', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States', 0, 'Computational Biology|Models, Molecular|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-14-S14-S12', '24267585', 'In recent years, the use and importance of predicted protein residue-residue contacts has grown considerably with demonstrated applications such as drug design, protein tertiary structure prediction and model quality assessment. Nevertheless, reported accuracies in the range of 25-35% stubbornly remain the norm for sequence based, long range contact predictions on hard targets. This is in spite of a prolonged effort on behalf of the community to improve the performance of residue-residue contact prediction. A thorough study of the quality of current residue-residue contact predictions and the evaluation metrics used as well as an analysis of current methods is needed to stimulate further advancement in contact prediction and its application. Such a study will better explain the quality and nature of residue-residue contact predictions generated by current methods and as a result lead to better use of this contact information.'),
(95841, 2013, 'bmc', 'Cell segmentation by multi-resolution analysis and maximum likelihood estimation (MAMLE)', 'Chowdhury, Sharif|Kandhavelu, Meenakshisundaram|Yli-Harja, Olli|Ribeiro, Andre S', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States', 25, 'Algorithms|Cell Division|Escherichia coli|Genetic Vectors|Green Fluorescent Proteins|Humans|Likelihood Functions|Microscopy, Confocal|Microscopy, Phase-Contrast|Software|Staphylococcus aureus', 'Journal Article', '10.1186/1471-2105-14-S10-S8', '24267594', 'Cell imaging is becoming an indispensable tool for cell and molecular biology research. However, most processes studied are stochastic in nature, and require the observation of many cells and events. Ideally, extraction of information from these images ought to rely on automatic methods. Here, we propose a novel segmentation method, MAMLE, for detecting cells within dense clusters.'),
(95842, 2013, 'bmc', 'SASD: the Synthetic Alternative Splicing Database for identifying novel isoform from proteomics', 'Zhang, Fan|Drabier, Renee', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States', 0, 'Alternative Splicing|Amino Acid Sequence|Base Sequence|Computational Biology|Databases, Nucleic Acid|Exons|Humans|Introns|Molecular Sequence Data|Organ Specificity|Peptides|Protein Isoforms|Proteins|Proteomics|RNA, Messenger|Tandem Mass Spectrometry', 'Journal Article', '10.1186/1471-2105-14-S14-S13', '24267658', 'Alternative splicing is an important and widespread mechanism for generating protein diversity and regulating protein expression. High-throughput identification and analysis of alternative splicing in the protein level has more advantages than in the mRNA level. The combination of alternative splicing database and tandem mass spectrometry provides a powerful technique for identification, analysis and characterization of potential novel alternative splicing protein isoforms from proteomics.'),
(95843, 2013, 'bmc', 'Mapping behavioral specifications to model parameters in synthetic biology', 'Koeppl, Heinz|Hafner, Marc|Lu, James', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States', 0, 'Algorithms|Computer Simulation|Dimerization|Kinetics|Models, Biological|Molecular Dynamics Simulation|Monte Carlo Method|Plasmids|Synthetic Biology|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-14-S10-S9', '24267662', 'With recent improvements of protocols for the assembly of transcriptional parts, synthetic biological devices can now more reliably be assembled according to a given design. The standardization of parts open up the way for in silico design tools that improve the construct and optimize devices with respect to given formal design specifications. The simplest such optimization is the selection of kinetic parameters and protein abundances such that the specified design constraints are robustly satisfied. In this work we address the problem of determining parameter values that fulfill specifications expressed in terms of a functional on the trajectories of a dynamical model. We solve this inverse problem by linearizing the forward operator that maps parameter sets to specifications, and then inverting it locally. This approach has two advantages over brute-force random sampling. First, the linearization approach allows us to map back intervals instead of points and second, every obtained value in the parameter region is satisfying the specifications by construction. The method is general and can hence be incorporated in a pipeline for the rational forward design of arbitrary devices in synthetic biology. '),
(95844, 2013, 'bmc', 'Circles within circles: crosstalk between protein Ser/Thr/Tyr-phosphorylation and Met oxidation', 'Rao, R|Xu, Dong|Thelen, Jay J|Miernyk, Ján A', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States', 0, 'Amino Acid Sequence|Amino Acids|Animals|Oxidation-Reduction|Phosphorylation|Protein Kinases|Protein Processing, Post-Translational|Proteome|Signal Transduction', 'Journal Article', '10.1186/1471-2105-14-S14-S14', '24267725', 'Reversible posttranslational protein modifications such as phosphorylation of Ser/Thr/Tyr and Met oxidation are critical for both metabolic regulation and cellular signalling. Although these modifications are typically studied individually, herein we describe the potential for cross-talk and hierarchical regulation.'),
(95845, 2013, 'bmc', 'Using context-specific effect of miRNAs to identify functional associations between miRNAs and gene signatures', 'Alshalalfa, Mohammed|Alhajj, Reda', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States', 0, 'Gene Expression Regulation|Humans|Male|MicroRNAs|Prostatic Neoplasms|Regression Analysis|Signal Transduction', 'Journal Article', '10.1186/1471-2105-14-S12-S1', '24267745', 'MicroRNAs are a class of short regulatory RNAs that act as post-transcriptional fine-tune regulators of a large host of genes that play key roles in many cellular processes and signaling pathways. A useful step for understanding their functional role is characterizing their influence on the protein context of the targets. Using miRNA context-specific influence as a functional signature is promising to identify functional associations between miRNAs and other gene signatures, and thus advance our understanding of miRNA mode of action.'),
(95846, 2013, 'bmc', 'Data mining tools for Salmonella characterization: application to gel-based fingerprinting analysis', 'Zou, Wen|Tang, Hailin|Zhao, Weizhong|Meehan, Joe|Foley, Steven L|Lin, Wei-Jiun|Chen, Hung-Chia|Fang, Hong|Nayak, Rajesh|Chen, James J', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 9, 'Cluster Analysis|Computational Biology|Data Mining|Databases, Genetic|Electrophoresis, Gel, Pulsed-Field|Humans|Salmonella|Serotyping', 'Journal Article', '10.1186/1471-2105-14-S14-S15', '24267777', 'Pulsed field gel electrophoresis (PFGE) is currently the most widely and routinely used method by the Centers for Disease Control and Prevention (CDC) and state health labs in the United States for Salmonella surveillance and outbreak tracking. Major drawbacks of commercially available PFGE analysis programs have been their difficulty in dealing with large datasets and the limited availability of analysis tools. There exists a need to develop new analytical tools for PFGE data mining in order to make full use of valuable data in large surveillance databases.'),
(95847, 2013, 'bmc', 'A novel subnetwork alignment approach predicts new components of the cell cycle regulatory apparatus in Plasmodium falciparum', 'Cai, Hong|Hong, Changjin|Lilburn, Timothy G|Rodriguez, Armando L|Chen, Sheng|Gu, Jianying|Kuang, Rui|Wang, Yufeng', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Cell Cycle|Escherichia coli|Plasmodium falciparum|Protein Interaction Maps|Protozoan Proteins', 'Journal Article', '10.1186/1471-2105-14-S12-S2', '24267797', 'According to the World Health organization, half the worlds population is at risk of contracting malaria. They estimated that in 2010 there were 219 million cases of malaria, resulting in 660,000 deaths and an enormous economic burden on the countries where malaria is endemic. The adoption of various high-throughput genomics-based techniques by malaria researchers has meant that new avenues to the study of this disease are being explored and new targets for controlling the disease are being developed. Here, we apply a novel neighborhood subnetwork alignment approach to identify the interacting elements that help regulate the cell cycle of the malaria parasite Plasmodium falciparum.'),
(95848, 2013, 'bmc', 'Drug activity prediction using multiple-instance learning via joint instance and feature selection', 'Zhao, Zhendong|Fu, Gang|Liu, Sheng|Elokely, Khaled M|Doerksen, Robert J|Chen, Yixin|Wilkins, Dawn E', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Drug Discovery|Humans|Imaging, Three-Dimensional|Ligands|Models, Molecular|Molecular Conformation', 'Journal Article', '10.1186/1471-2105-14-S14-S16', '24267824', 'In drug discovery and development, it is crucial to determine which conformers (instances) of a given molecule are responsible for its observed biological activity and at the same time to recognize the most representative subset of features (molecular descriptors). Due to experimental difficulty in obtaining the bioactive conformers, computational approaches such as machine learning techniques are much needed. Multiple Instance Learning (MIL) is a machine learning method capable of tackling this type of problem. In the MIL framework, each instance is represented as a feature vector, which usually resides in a high-dimensional feature space. The high dimensionality may provide significant information for learning tasks, but at the same time it may also include a large number of irrelevant or redundant features that might negatively affect learning performance. Reducing the dimensionality of data will hence facilitate the classification task and improve the interpretability of the model.'),
(95849, 2013, 'bmc', 'mirCoX: a database of miRNA-mRNA expression correlations derived from RNA-seq meta-analysis', 'Giles, Cory B|Girija-Devi, Reshmi|Dozmorov, Mikhail G|Wren, Jonathan D', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States', 0, 'Base Sequence|Computational Biology|Databases, Nucleic Acid|Gene Expression|Gene Expression Profiling|Humans|Internet|MicroRNAs|Models, Molecular|Nucleic Acid Conformation|RNA, Messenger|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-14-S14-S17', '24267917', 'Experimentally validated co-expression correlations between miRNAs and genes are a valuable resource to corroborate observations about miRNA/mRNA changes after experimental perturbations, as well as compare miRNA target predictions with empirical observations. For example, when a given miRNA is transcribed, true targets of that miRNA should tend to have lower expression levels relative to when the miRNA is not expressed.'),
(95850, 2013, 'bmc', 'An efficient method for mining cross-timepoint gene regulation sequential patterns from time course gene expression datasets', 'Cheng, Chun-Pei|Liu, Yu-Cheng|Tsai, Yi-Lin|Tseng, Vincent S', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States', 0, 'Algorithms|Cluster Analysis|Data Mining|Gene Expression Regulation|Humans|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-14-S12-S3', '24267918', 'Observation of gene expression changes implying gene regulations using a repetitive experiment in time course has become more and more important. However, there is no effective method which can handle such kind of data. For instance, in a clinical/biological progression like inflammatory response or cancer formation, a great number of differentially expressed genes at different time points could be identified through a large-scale microarray approach. For each repetitive experiment with different samples, converting the microarray datasets into transactional databases with significant singleton genes at each time point would allow sequential patterns implying gene regulations to be identified. Although traditional sequential pattern mining methods have been successfully proposed and widely used in different interesting topics, like mining customer purchasing sequences from a transactional database, to our knowledge, the methods are not suitable for such biological dataset because every transaction in the converted database may contain too many items/genes.'),
(95851, 2013, 'bmc', 'Systematic classification of non-coding RNAs by epigenomic similarity', 'Dozmorov, Mikhail G|Giles, Cory B|Koelsch, Kristi A|Wren, Jonathan D', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States', 0, 'Algorithms|Binding Sites|Chromatin|Epigenomics|Genome, Human|Histones|Humans|RNA, Untranslated|Transcription Factors', 'Journal Article', '10.1186/1471-2105-14-S14-S2', '24267974', 'Even though only 1.5% of the human genome is translated into proteins, recent reports indicate that most of it is transcribed into non-coding RNAs (ncRNAs), which are becoming the subject of increased scientific interest. We hypothesized that examining how different classes of ncRNAs co-localized with annotated epigenomic elements could help understand the functions, regulatory mechanisms, and relationships among ncRNA families.'),
(95852, 2013, 'bmc', 'Protein function prediction by collective classification with explicit and implicit edges in protein-protein interaction networks', 'Xiong, Wei|Liu, Hui|Guan, Jihong|Zhou, Shuigeng', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States', 0, 'Algorithms|Genomics|Hepatitis C|Humans|Molecular Sequence Annotation|Pneumonia, Ventilator-Associated|Protein Interaction Maps|Proteins|Transcription, Genetic|Transcriptome', 'Journal Article', '10.1186/1471-2105-14-S12-S4', '24267980', 'Protein function prediction is an important problem in the post-genomic era. Recent advances in experimental biology have enabled the production of vast amounts of protein-protein interaction (PPI) data. Thus, using PPI data to functionally annotate proteins has been extensively studied. However, most existing network-based approaches do not work well when annotation and interaction information is inadequate in the networks.'),
(95853, 2013, 'bmc', 'Differential reconstructed gene interaction networks for deriving toxicity threshold in chemical risk assessment', 'Yang, Yi|Maxwell, Andrew|Zhang, Xiaowei|Wang, Nan|Perkins, Edward J|Zhang, Chaoyang|Gong, Ping', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States|United States|United States', 12, 'Cell Cycle|Epistasis, Genetic|Escherichia coli|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Risk Assessment', 'Journal Article', '10.1186/1471-2105-14-S14-S3', '24268022', 'Pathway alterations reflected as changes in gene expression regulation and gene interaction can result from cellular exposure to toxicants. Such information is often used to elucidate toxicological modes of action. From a risk assessment perspective, alterations in biological pathways are a rich resource for setting toxicant thresholds, which may be more sensitive and mechanism-informed than traditional toxicity endpoints. Here we developed a novel differential networks (DNs) approach to connect pathway perturbation with toxicity threshold setting.'),
(95854, 2013, 'bmc', 'Learning by aggregating experts and filtering novices: a solution to crowdsourcing problems in bioinformatics', 'Zhang, Ping|Cao, Weidan|Obradovic, Zoran', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States', 0, 'Algorithms|Computational Biology|Crowdsourcing|Logistic Models|Proteins', 'Journal Article', '10.1186/1471-2105-14-S12-S5', '24268030', 'In many biomedical applications, there is a need for developing classification models based on noisy annotations. Recently, various methods addressed this scenario by relaying on unreliable annotations obtained from multiple sources.'),
(95855, 2013, 'bmc', 'Towards the integration, annotation and association of historical microarray experiments with RNA-seq', 'Chavan, Shweta S|Bauer, Michael A|Peterson, Erich A|Heuck, Christoph J|Johann, Donald J', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Cell Line|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Molecular Sequence Annotation|RNA|Sequence Analysis, RNA|Software Design|Transcriptome', 'Journal Article', '10.1186/1471-2105-14-S14-S4', '24268045', 'Transcriptome analysis by microarrays has produced important advances in biomedicine. For instance in multiple myeloma (MM), microarray approaches led to the development of an effective disease subtyping via cluster assignment, and a 70 gene risk score. Both enabled an improved molecular understanding of MM, and have provided prognostic information for the purposes of clinical management. Many researchers are now transitioning to Next Generation Sequencing (NGS) approaches and RNA-seq in particular, due to its discovery-based nature, improved sensitivity, and dynamic range. Additionally, RNA-seq allows for the analysis of gene isoforms, splice variants, and novel gene fusions. Given the voluminous amounts of historical microarray data, there is now a need to associate and integrate microarray and RNA-seq data via advanced bioinformatic approaches.'),
(95856, 2013, 'bmc', 'Ensemble classifier based on context specific miRNA regulation modules: a new method for cancer outcome prediction', 'Zhou, Xionghui|Liu, Juan|Ye, Xinghuo|Wang, Wei|Xiong, Jianghui', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States|United States', 0, 'Breast Neoplasms|Female|Gene Expression Regulation, Neoplastic|Genetic Markers|Humans|MicroRNAs|Neoplasm Metastasis|Prognosis|Software|Transcriptome', 'Journal Article', '10.1186/1471-2105-14-S12-S6', '24268063', 'Many classifiers which are constructed with chosen gene markers have been proposed to forecast the prognosis of patients who suffer from breast cancer. However, few of them has been applied in clinical practice because of the bad generalization, which results from the situation that markers selected by one method are very different from those obtained by another method, and thus such markers always lack discriminative capability in the other data sets.'),
(95857, 2013, 'bmc', 'VarRanker: rapid prioritization of sequence variations associated with human disease', 'OFallon, Brendan D|Wooderchak-Donahue, Whitney|Bayrak-Toydemir, Pinar|Crockett, David', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States|United States', 4, 'Algorithms|Anemia, Diamond-Blackfan|Computational Biology|Genomic Structural Variation|Humans|Information Storage and Retrieval|Linear Models|Mutation|Phenotype|Sequence Analysis, Protein|Telangiectasia, Hereditary Hemorrhagic|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-14-S13-S1', '24268183', 'Identification of the genetic alterations responsible for human disease is a central challenge facing medical genetics. While many algorithms have been developed to predict the degree of damage caused by a given sequence alteration, few tools are able to incorporate information about a given phenotype of interest.'),
(95858, 2013, 'bmc', 'Fuzzy clustering of CPP family in plants with evolution and interaction analyses', 'Lu, Tao|Dou, Yongchao|Zhang, Chi', 'Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.|Selventa, One Alewife Center, Cambridge, MA 02140, USA. ncatlett@selventa.com.', 'United States|United States|United States', 8, 'Arabidopsis Proteins|Cluster Analysis|Cysteine|Fuzzy Logic|Gene Expression Profiling|Molecular Sequence Data|Phylogeny|Plant Proteins|Protein Interaction Mapping|Transcription Factors', 'Comparative Study', '10.1186/1471-2105-14-S13-S10', '24268301', 'Transcription factors have been studied intensively because they play an important role in gene expression regulation. However, the transcription factors in the CPP family (cystein-rich polycomb-like protein), compared with other transcription factor families, have not received sufficient attention, despite their wide prevalence in a broad spectrum of species, from plants to animals. The total number of known CPP transcription factors in plants is 111 from 16 plants, but only 2 of them have been studied so far, namely TSO1 and CPP1 in Arabidopsis thaliana and soybean, respectively.'),
(95859, 2013, 'bmc', 'LUD, a new protein domain associated with lactate utilization', 'Hwang, William C|Bakolitsa, Constantina|Punta, Marco|Coggill, Penelope C|Bateman, Alex|Axelrod, Herbert L|Rawlings, Neil D|Sedova, Mayya|Peterson, Scott N|Eberhardt, Ruth Y|Aravind, L|Pascual, Jaime|Godzik, Adam', 'Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.org.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.org.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.org.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.org.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.org.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.org.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.org.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.org.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.org.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.org.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.org.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.org.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA. wchwang@sanfordburnham.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|United States', 4, 'Amino Acid Sequence|Bacterial Proteins|Crystallography, X-Ray|Deinococcus|Humans|Lactic Acid|Microbiota|Molecular Sequence Data|Protein Structure, Tertiary', 'Journal Article', '10.1186/1471-2105-14-341', '24274019', 'A novel highly conserved protein domain, DUF162 [Pfam: PF02589], can be mapped to two proteins: LutB and LutC. Both proteins are encoded by a highly conserved LutABC operon, which has been implicated in lactate utilization in bacteria. Based on our analysis of its sequence, structure, and recent experimental evidence reported by other groups, we hereby redefine DUF162 as the LUD domain family.'),
(95860, 2013, 'bmc', 'A novel approach for protein subcellular location prediction using amino acid exposure', 'Mer, Arvind Singh|Andrade-Navarro, Miguel A', 'Computational Biology and Data Mining, Max Delbrück Center for Molecular Medicine, Robert-Rössle-Str, 10, Berlin 13125, Germany. miguel.andrade@mdc-berlin.de.|Computational Biology and Data Mining, Max Delbrück Center for Molecular Medicine, Robert-Rössle-Str, 10, Berlin 13125, Germany. miguel.andrade@mdc-berlin.de.', 'Germany|Germany', 14, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Computational Biology|Databases, Protein|Humans|Neural Networks (Computer)|Nucleocytoplasmic Transport Proteins|Predictive Value of Tests|Principal Component Analysis|Proteins|Subcellular Fractions|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-14-342', '24283794', 'Proteins perform their functions in associated cellular locations. Therefore, the study of protein function can be facilitated by predictions of protein location. Protein location can be predicted either from the sequence of a protein alone by identification of targeting peptide sequences and motifs, or by homology to proteins of known location. A third approach, which is complementary, exploits the differences in amino acid composition of proteins associated to different cellular locations, and can be useful if motif and homology information are missing. Here we expand this approach taking into account amino acid composition at different levels of amino acid exposure.'),
(95861, 2013, 'bmc', 'Transferring functional annotations of membrane transporters on the basis of sequence similarity and sequence motifs', 'Barghash, Ahmad|Helms, Volkhard', 'Center for Bioinformatics, Saarland University, Postfach 15 11 50, 66041 Saarbrücken, Germany. volkhard.helms@bioinformatik.uni-saarland.de.|Center for Bioinformatics, Saarland University, Postfach 15 11 50, 66041 Saarbrücken, Germany. volkhard.helms@bioinformatik.uni-saarland.de.', 'Germany|Germany', 11, 'Amino Acid Motifs|Amino Acid Sequence|Arabidopsis|Biological Transport, Active|Escherichia coli|Humans|Membrane Transport Proteins|Molecular Sequence Data|Multigene Family|Proteomics|Saccharomyces cerevisiae|Sequence Homology, Amino Acid', 'Comparative Study', '10.1186/1471-2105-14-343', '24283849', 'Membrane transporters catalyze the transport of small solute molecules across biological barriers such as lipid bilayer membranes. Experimental identification of the transported substrates is very tedious. Once a particular transport mechanism has been identified in one organism, it is thus highly desirable to transfer this information to related transporter sequences in different organisms based on bioinformatics evidence.'),
(95862, 2013, 'bmc', 'Partial inhibition and bilevel optimization in flux balance analysis', 'Facchetti, Giuseppe|Altafini, Claudio', 'SISSA (International School for Advanced Studies) Functional Analysis Dept, - Via Bonomea 265 - 34136, Trieste, Italy. altafini@sissa.it.|SISSA (International School for Advanced Studies) Functional Analysis Dept, - Via Bonomea 265 - 34136, Trieste, Italy. altafini@sissa.it.', 'Italy|Italy', 2, 'Aldose-Ketose Isomerases|Algorithms|Computer Simulation|Drug Combinations|Drug Interactions|Escherichia coli|Glutamate Dehydrogenase|Humans|Metabolic Engineering|Metabolic Flux Analysis|Neural Networks (Computer)|Software|Support Vector Machine|Transketolase', 'Journal Article', '10.1186/1471-2105-14-344', '24286232', 'Within Flux Balance Analysis, the investigation of complex subtasks, such as finding the optimal perturbation of the network or finding an optimal combination of drugs, often requires to set up a bilevel optimization problem. In order to keep the linearity and convexity of these nested optimization problems, an ON/OFF description of the effect of the perturbation (i.e. Boolean variable) is normally used. This restriction may not be realistic when one wants, for instance, to describe the partial inhibition of a reaction induced by a drug.'),
(95863, 2013, 'bmc', 'wKinMut: an integrated tool for the analysis and interpretation of mutations in human protein kinases', 'Izarzugaza, Jose M G|Vazquez, Miguel|del Pozo, Angela|Valencia, Alfonso', 'Structural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), C/Melchor Fernandez Almagro, 3, E-28029 Madrid, Spain. josemgizarzugaza@cbs.dtu.dk.|Structural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), C/Melchor Fernandez Almagro, 3, E-28029 Madrid, Spain. josemgizarzugaza@cbs.dtu.dk.|Structural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), C/Melchor Fernandez Almagro, 3, E-28029 Madrid, Spain. josemgizarzugaza@cbs.dtu.dk.|Structural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), C/Melchor Fernandez Almagro, 3, E-28029 Madrid, Spain. josemgizarzugaza@cbs.dtu.dk.', 'Spain|Spain|Spain|Spain', 6, 'Computational Biology|Databases, Protein|ErbB Receptors|Humans|Information Storage and Retrieval|Leukemia, Lymphocytic, Chronic, B-Cell|Mutation|Phenotype|Predictive Value of Tests|Protein Kinases|Protein Stability', 'Journal Article', '10.1186/1471-2105-14-345', '24289158', 'Protein kinases are involved in relevant physiological functions and a broad number of mutations in this superfamily have been reported in the literature to affect protein function and stability. Unfortunately, the exploration of the consequences on the phenotypes of each individual mutation remains a considerable challenge.'),
(95864, 2013, 'bmc', 'Disulfide by Design 20: a web-based tool for disulfide engineering in proteins', 'Craig, Douglas B|Dombkowski, Alan A', 'Structural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), C/Melchor Fernandez Almagro, 3, E-28029 Madrid, Spain. josemgizarzugaza@cbs.dtu.dk.|Department of Pediatrics, Wayne State University School of Medicine, Detroit, Michigan 48201, USA. domski@wayne.edu.', 'Spain|United States', 117, 'Computational Biology|Disulfides|Internet|Protein Engineering|Proteins|Software', 'Journal Article', '10.1186/1471-2105-14-346', '24289175', 'Disulfide engineering is an important biotechnological tool that has advanced a wide range of research. The introduction of novel disulfide bonds into proteins has been used extensively to improve protein stability, modify functional characteristics, and to assist in the study of protein dynamics. Successful use of this technology is greatly enhanced by software that can predict pairs of residues that will likely form a disulfide bond if mutated to cysteines.'),
(95865, 2013, 'bmc', 'Heterodimeric protein complex identification by naïve Bayes classifiers', 'Maruyama, Osamu', 'Institute of Mathematics for Industry, Kyushu University, Fukuoka, Japan. om@imi.kyushu-u.ac.jp.', 'Japan', 6, 'Algorithms|Bayes Theorem|Databases, Factual|Forecasting|Likelihood Functions|Predictive Value of Tests|Protein Interaction Mapping|Protein Interaction Maps|Protein Multimerization|Proteins|Research Design|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-14-347', '24299017', 'Protein complexes are basic cellular entities that carry out the functions of their components. It can be found that in databases of protein complexes of yeast like CYC2008, the major type of known protein complexes is heterodimeric complexes. Although a number of methods for trying to predict sets of proteins that form arbitrary types of protein complexes simultaneously have been proposed, it can be found that they often fail to predict heterodimeric complexes.'),
(95866, 2013, 'bmc', 'Selecting informative subsets of sparse supermatrices increases the chance to find correct trees', 'Misof, Bernhard|Meyer, Benjamin|von Reumont, Björn Marcus|Kück, Patrick|Misof, Katharina|Meusemann, Karen', ', Zoologisches Forschungsmuseum Alexander Koenig, zmb, Adenauerallee 160, 53113 Bonn, Germany. b.misof.zfmk@uni-bonn.de.|, Zoologisches Forschungsmuseum Alexander Koenig, zmb, Adenauerallee 160, 53113 Bonn, Germany. b.misof.zfmk@uni-bonn.de.|, Zoologisches Forschungsmuseum Alexander Koenig, zmb, Adenauerallee 160, 53113 Bonn, Germany. b.misof.zfmk@uni-bonn.de.|, Zoologisches Forschungsmuseum Alexander Koenig, zmb, Adenauerallee 160, 53113 Bonn, Germany. b.misof.zfmk@uni-bonn.de.|, Zoologisches Forschungsmuseum Alexander Koenig, zmb, Adenauerallee 160, 53113 Bonn, Germany. b.misof.zfmk@uni-bonn.de.|, Zoologisches Forschungsmuseum Alexander Koenig, zmb, Adenauerallee 160, 53113 Bonn, Germany. b.misof.zfmk@uni-bonn.de.', 'Germany|Germany|Germany|Germany|Germany|Germany', 52, 'Algorithms|Animals|Cattle|Classification|Computer Simulation|DNA Repair|Evolution, Molecular|Humans|Likelihood Functions|Mice|Phylogeny|Probability|Random Allocation|Rats|Signal Transduction|Software|Support Vector Machine|Sus scrofa', 'Comparative Study', '10.1186/1471-2105-14-348', '24299043', 'Character matrices with extensive missing data are frequently used in phylogenomics with potentially detrimental effects on the accuracy and robustness of tree inference. Therefore, many investigators select taxa and genes with high data coverage. Drawbacks of these selections are their exclusive reliance on data coverage without consideration of actual signal in the data which might, thus, not deliver optimal data matrices in terms of potential phylogenetic signal. In order to circumvent this problem, we have developed a heuristics implemented in a software called mare which (1) assesses information content of genes in supermatrices using a measure of potential signal combined with data coverage and (2) reduces supermatrices with a simple hill climbing procedure to submatrices with high total information content. We conducted simulation studies using matrices of 50 taxa × 50 genes with heterogeneous phylogenetic signal among genes and data coverage between 10-30%.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(95867, 2013, 'bmc', 'MosaicIA: an ImageJ/Fiji plugin for spatial pattern and interaction analysis', 'Shivanandan, Arun|Radenovic, Aleksandra|Sbalzarini, Ivo F', 'MOSAIC Group, Center of Systems Biology Dresden (CSBD), Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr 108, 01307 Dresden, Germany. ivos@mpi-cbg.de.|MOSAIC Group, Center of Systems Biology Dresden (CSBD), Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr 108, 01307 Dresden, Germany. ivos@mpi-cbg.de.|MOSAIC Group, Center of Systems Biology Dresden (CSBD), Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr 108, 01307 Dresden, Germany. ivos@mpi-cbg.de.', 'Germany|Germany|Germany', 43, 'Adenoviruses, Human|Algorithms|Cell Line|Endosomes|Green Fluorescent Proteins|Humans|Microscopy, Confocal|Molecular Imaging|Monte Carlo Method|Probability|Random Allocation|Software|Spatio-Temporal Analysis', 'Journal Article', '10.1186/1471-2105-14-349', '24299066', 'Analyzing spatial distributions of objects in images is a fundamental task in many biological studies. The relative arrangement of a set of objects with respect to another set of objects contains information about potential interactions between the two sets of objects. If they do not feel each others presence, their spatial distributions are expected to be independent of one another. Spatial correlations in their distributions are indicative of interactions and can be modeled by an effective interaction potential acting between the points of the two sets. This can be used to generalize co-localization analysis to spatial interaction analysis. However, no user-friendly software for this type of analysis was available so far.'),
(95868, 2013, 'bmc', 'Image-level and group-level models for Drosophila gene expression pattern annotation', 'Sun, Qian|Muckatira, Sherin|Yuan, Lei|Ji, Shuiwang|Newfeld, Stuart|Kumar, Sudhir|Ye, Jieping', 'MOSAIC Group, Center of Systems Biology Dresden (CSBD), Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr 108, 01307 Dresden, Germany. ivos@mpi-cbg.de.|MOSAIC Group, Center of Systems Biology Dresden (CSBD), Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr 108, 01307 Dresden, Germany. ivos@mpi-cbg.de.|MOSAIC Group, Center of Systems Biology Dresden (CSBD), Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr 108, 01307 Dresden, Germany. ivos@mpi-cbg.de.|MOSAIC Group, Center of Systems Biology Dresden (CSBD), Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr 108, 01307 Dresden, Germany. ivos@mpi-cbg.de.|MOSAIC Group, Center of Systems Biology Dresden (CSBD), Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr 108, 01307 Dresden, Germany. ivos@mpi-cbg.de.|MOSAIC Group, Center of Systems Biology Dresden (CSBD), Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr 108, 01307 Dresden, Germany. ivos@mpi-cbg.de.|Center for Evolutionary Medicine and Informatics, The Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA. jieping.ye@asu.edu.', 'Germany|Germany|Germany|Germany|Germany|Germany|United States', 7, 'Animals|Cell Differentiation|Cell Division|Computational Biology|Drosophila melanogaster|Gene Expression Profiling|Gene Expression Regulation, Developmental|Genome, Insect|High-Throughput Screening Assays|Models, Genetic|Molecular Sequence Annotation|Predictive Value of Tests|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-14-350', '24299119', 'Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.'),
(95869, 2013, 'bmc', 'On the amyloid datasets used for training PAFIG--how (not) to extend the experimental dataset of hexapeptides', 'Kotulska, Malgorzata|Unold, Olgierd', 'Institute of Biomedical Engineering and Instrumentation, Wroclaw University of Technology, 50-370 Wroclaw, Poland. malgorzata.kotulska@pwr.wroc.pl.|Institute of Biomedical Engineering and Instrumentation, Wroclaw University of Technology, 50-370 Wroclaw, Poland. malgorzata.kotulska@pwr.wroc.pl.', 'Poland|Poland', 4, 'Alzheimer Disease|Amyloid|Computational Biology|Databases, Protein|False Positive Reactions|Humans|Molecular Dynamics Simulation|Oligopeptides|Parkinson Disease|Peptide Fragments', 'Journal Article', '10.1186/1471-2105-14-351', '24305169', 'Amyloids are proteins capable of forming aberrant intramolecular contact sites, characteristic of beta zipper configuration. Amyloids can underlie serious health conditions, e.g. Alzheimers or Parkinsons diseases. It has been proposed that short segments of amino acids can be responsible for protein amyloidogenicity, but no more than two hundred such hexapeptides have been experimentally found. The authors of the computational tool Pafig published in BMC Bioinformatics a method for extending the amyloid hexapeptide dataset that could be used for training and testing models. They assumed that all hexapeptides belonging to an amyloid protein can be regarded as amylopositive, while those from proteins never reported as amyloid are always amylonegative. Here we show why the above described method of extending datasets is wrong and discuss the reasons why the incorrect data could lead to falsely correct classification.'),
(95870, 2013, 'bmc', 'Status quo of annotation of human disease variants', 'Venselaar, Hanka|Camilli, Franscesca|Gholizadeh, Shima|Snelleman, Marlou|Brunner, Han G|Vriend, Gert', 'CMBI, NCMLS, Radboud University Nijmegen Medical Centre, Nijmegen, PO Box 9101, Nijmegen, HB 6500, The Netherlands. vriend@cmbi.ru.nl.|CMBI, NCMLS, Radboud University Nijmegen Medical Centre, Nijmegen, PO Box 9101, Nijmegen, HB 6500, The Netherlands. vriend@cmbi.ru.nl.|CMBI, NCMLS, Radboud University Nijmegen Medical Centre, Nijmegen, PO Box 9101, Nijmegen, HB 6500, The Netherlands. vriend@cmbi.ru.nl.|CMBI, NCMLS, Radboud University Nijmegen Medical Centre, Nijmegen, PO Box 9101, Nijmegen, HB 6500, The Netherlands. vriend@cmbi.ru.nl.|CMBI, NCMLS, Radboud University Nijmegen Medical Centre, Nijmegen, PO Box 9101, Nijmegen, HB 6500, The Netherlands. vriend@cmbi.ru.nl.|CMBI, NCMLS, Radboud University Nijmegen Medical Centre, Nijmegen, PO Box 9101, Nijmegen, HB 6500, The Netherlands. vriend@cmbi.ru.nl.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 3, 'Artificial Intelligence|Cluster Analysis|Computational Biology|Conserved Sequence|Databases, Genetic|Exome|Genetic Variation|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Molecular Sequence Annotation|Mutation|Polymorphism, Single Nucleotide|Proteins|Sequence Alignment|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-14-352', '24305467', 'The ever on-going technical developments in Next Generation Sequencing have led to an increase in detected disease related mutations. Many bioinformatics approaches exist to analyse these variants, and of those the methods that use 3D structure information generally outperform those that do not use this information. 3D structure information today is available for about twenty percent of the human exome, and homology modelling can double that fraction. This percentage is rapidly increasing so that we can expect to analyse the majority of all human exome variants in the near future using protein structure information.'),
(95871, 2013, 'bmc', 'The causal effect of red blood cell folate on genome-wide methylation in cord blood: a Mendelian randomization approach', 'Binder, Alexandra M|Michels, Karin B', 'Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. abinder@hsph.harvard.edu.|Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. abinder@hsph.harvard.edu.', 'United States|United States', 20, 'Adult|Child|CpG Islands|DNA Methylation|Epigenomics|Erythrocytes|Female|Fetal Blood|Folic Acid|Genotype|Humans|Infant|Mendelian Randomization Analysis|Oligonucleotide Array Sequence Analysis|Random Allocation', 'Comparative Study', '10.1186/1471-2105-14-353', '24305512', 'Investigation of the biological mechanism by which folate acts to affect fetal development can inform appraisal of expected benefits and risk management. This research is ethically imperative given the ubiquity of folic acid fortified products in the US. Considering that folate is an essential component in the one-carbon metabolism pathway that provides methyl groups for DNA methylation, epigenetic modifications provide a putative molecular mechanism mediating the effect of folic acid supplementation on neonatal and pediatric outcomes.'),
(95872, 2013, 'bmc', 'Balony: a software package for analysis of data generated by synthetic genetic array experiments', 'Young, Barry P|Loewen, Christopher J R', 'Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, 2350 Health Sciences Mall, Vancouver, British Columbia V6T 1Z3, Canada. barry.young@ubc.ca.|Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, 2350 Health Sciences Mall, Vancouver, British Columbia V6T 1Z3, Canada. barry.young@ubc.ca.', 'Canada|Canada', 34, 'Colony Count, Microbial|Fungal Proteins|Genes, Fungal|Genome-Wide Association Study|High-Throughput Screening Assays|Image Processing, Computer-Assisted|Internet|Mutation|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-14-354', '24305553', 'Synthetic Genetic Array (SGA) analysis is a procedure which has been developed to allow the systematic examination of large numbers of double mutants in the yeast Saccharomyces cerevisiae. The aim of these experiments is to identify genetic interactions between pairs of genes. These experiments generate a number of images of ordered arrays of yeast colonies which must be analyzed in order to quantify the extent of the genetic interactions. We have designed software that is able to analyze virtually any image of regularly arrayed colonies and allows the user significant flexibility over the analysis procedure.'),
(95873, 2013, 'bmc', 'Viral quasispecies inference from 454 pyrosequencing', 'Poh, Wan-Ting|Xia, Eryu|Chin-Inmanu, Kwanrutai|Wong, Lai-Ping|Cheng, Anthony Youzhi|Malasit, Prida|Suriyaphol, Prapat|Teo, Yik-Ying|Ong, Rick Twee-Hee', 'Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, 2350 Health Sciences Mall, Vancouver, British Columbia V6T 1Z3, Canada. barry.young@ubc.ca.|Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, 2350 Health Sciences Mall, Vancouver, British Columbia V6T 1Z3, Canada. barry.young@ubc.ca.|Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, 2350 Health Sciences Mall, Vancouver, British Columbia V6T 1Z3, Canada. barry.young@ubc.ca.|Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, 2350 Health Sciences Mall, Vancouver, British Columbia V6T 1Z3, Canada. barry.young@ubc.ca.|Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, 2350 Health Sciences Mall, Vancouver, British Columbia V6T 1Z3, Canada. barry.young@ubc.ca.|Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, 2350 Health Sciences Mall, Vancouver, British Columbia V6T 1Z3, Canada. barry.young@ubc.ca.|Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, 2350 Health Sciences Mall, Vancouver, British Columbia V6T 1Z3, Canada. barry.young@ubc.ca.|Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore. statyy@nus.edu.sg.|Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore. statyy@nus.edu.sg.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Singapore|Singapore', 6, 'Base Sequence|Computational Biology|Dengue|Dengue Virus|Genetic Variation|Genome, Viral|Genomics|High-Throughput Nucleotide Sequencing|Humans|Phenotype|Recombination, Genetic|Sequence Alignment|Sequence Analysis, DNA|Species Specificity', 'Journal Article', '10.1186/1471-2105-14-355', '24308284', 'Many potentially life-threatening infectious viruses are highly mutable in nature. Characterizing the fittest variants within a quasispecies from infected patients is expected to allow unprecedented opportunities to investigate the relationship between quasispecies diversity and disease epidemiology. The advent of next-generation sequencing technologies has allowed the study of virus diversity with high-throughput sequencing, although these methods come with higher rates of errors which can artificially increase diversity.'),
(95874, 2013, 'bmc', 'Processing genome scale tabular data with wormtable', 'Kelleher, Jerome|Ness, Rob W|Halligan, Daniel L', 'University of Edinburgh, Kings Buildings, West Mains Road, Edinburgh, EH9 3JT, UK. jerome.kelleher@ed.ac.uk.|University of Edinburgh, Kings Buildings, West Mains Road, Edinburgh, EH9 3JT, UK. jerome.kelleher@ed.ac.uk.|University of Edinburgh, Kings Buildings, West Mains Road, Edinburgh, EH9 3JT, UK. jerome.kelleher@ed.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom', 4, 'Animals|Computational Biology|Computer Simulation|Databases, Factual|Drosophila Proteins|Electronic Data Processing|Genome, Human|Genome, Insect|Genomics|Humans|Libraries, Digital|Random Allocation|Search Engine|Software', 'Journal Article', '10.1186/1471-2105-14-356', '24308302', 'Modern biological science generates a vast amount of data, the analysis of which presents a major challenge to researchers. Data are commonly represented in tables stored as plain text files and require line-by-line parsing for analysis, which is time consuming and error prone. Furthermore, there is no simple means of indexing these files so that rows containing particular values can be quickly found.'),
(95875, 2013, 'bmc', 'Sample size calculation based on exact test for assessing differential expression analysis in RNA-seq data', 'Li, Chung-I|Su, Pei-Fang|Shyr, Yu', 'University of Edinburgh, Kings Buildings, West Mains Road, Edinburgh, EH9 3JT, UK. jerome.kelleher@ed.ac.uk.|University of Edinburgh, Kings Buildings, West Mains Road, Edinburgh, EH9 3JT, UK. jerome.kelleher@ed.ac.uk.|Center for Quantitative Sciences, Vanderbilt University, 571 Preston Building Nashville, TN, USA. yu.shyr@vanderbilt.edu.', 'United Kingdom|United Kingdom|United Kingdom', 21, 'Base Sequence|Computer Simulation|Gene Expression Regulation|Likelihood Functions|Models, Statistical|Poisson Distribution|RNA|Random Allocation|Research Design|Sample Size|Sequence Analysis, RNA|User-Computer Interface', 'Comparative Study', '10.1186/1471-2105-14-357', '24314022', 'Sample size calculation is an important issue in the experimental design of biomedical research. For RNA-seq experiments, the sample size calculation method based on the Poisson model has been proposed, however, when there are biological replicates, RNA-seq data could exhibit variation significantly greater than the mean (i.e. over-dispersion). The Poisson model cannot appropriately model the over-dispersion, and in such cases, the negative binomial model has been used as a natural extension of the Poisson model. Because the field currently lacks a sample size calculation method based on the negative binomial model for assessing differential expression analysis of RNA-seq data, we propose a method to calculate the sample size.'),
(95876, 2013, 'bmc', 'Fragment assignment in the cloud with eXpress-D', 'Roberts, Adam|Feng, Harvey|Pachter, Lior', 'Center for Quantitative Sciences, Vanderbilt University, 571 Preston Building Nashville, TN, USA. yu.shyr@vanderbilt.edu.|Center for Quantitative Sciences, Vanderbilt University, 571 Preston Building Nashville, TN, USA. yu.shyr@vanderbilt.edu.|Department of Computer Science, 387 Soda Hall, UC Berkeley, Berkeley, CA 94720, USA. lpachter@math.berkeley.edu.', 'United States|United States|United States', 11, 'Algorithms|Artificial Intelligence|Computational Biology|Computer Communication Networks|Feasibility Studies|High-Throughput Nucleotide Sequencing|Humans|Likelihood Functions|Oligonucleotide Array Sequence Analysis|Peptide Fragments|Probability|Programming Languages|Search Engine|Sequence Alignment|Software|Transcriptome|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-14-358', '24314033', 'Probabilistic assignment of ambiguously mapped fragments produced by high-throughput sequencing experiments has been demonstrated to greatly improve accuracy in the analysis of RNA-Seq and ChIP-Seq, and is an essential step in many other sequence census experiments. A maximum likelihood method using the expectation-maximization (EM) algorithm for optimization is commonly used to solve this problem. However, batch EM-based approaches do not scale well with the size of sequencing datasets, which have been increasing dramatically over the past few years. Thus, current approaches to fragment assignment rely on heuristics or approximations for tractability.'),
(95877, 2013, 'bmc', 'Marmal-aid--a database for Infinium HumanMethylation450', 'Lowe, Robert|Rakyan, Vardhman K', 'The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. r.lowe@qmul.ac.uk.|The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. r.lowe@qmul.ac.uk.', 'United Kingdom|United Kingdom', 0, 'Algorithms|Animals|CpG Islands|DNA Methylation|Databases, Factual|Electronic Data Processing|Genome, Human|Humans|Mice|Oligonucleotide Array Sequence Analysis|Phenotype|Search Engine|Software', 'Journal Article', '10.1186/1471-2105-14-359', '24330312', 'DNA methylation is indispensible for normal human genome function. Currently there is an increasingly large number of DNA methylomic data being released in the public domain allowing for an opportunity to investigate the relationships between the DNA methylome, genome function, and human phenotypes. The Illumina450K is one of the most popular platforms for assessing DNA methylation with over 10,000 samples available in the public domain. However, accessing all this data requires downloading each individual experiment and due to inconsistent annotation, accessing the right data can be a challenge.'),
(95878, 2013, 'bmc', 'Gene set bagging for estimating the probability a statistically significant result will replicate', 'Jaffe, Andrew E|Storey, John D|Ji, Hongkai|Leek, Jeffrey T', 'The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. r.lowe@qmul.ac.uk.|The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. r.lowe@qmul.ac.uk.|The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. r.lowe@qmul.ac.uk.|Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore MD 21205, USA. jleek@jhsph.edu.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Binding Sites|Brain Chemistry|Computer Simulation|DNA Methylation|DNA Replication|Databases, Factual|Gene Expression Profiling|Genome, Human|Genomics|Humans|Oligonucleotide Array Sequence Analysis|Predictive Value of Tests|Probability|Sample Size|Smoking|Transcription Factors', 'Journal Article', '10.1186/1471-2105-14-360', '24330332', 'Significance analysis plays a major role in identifying and ranking genes, transcription factor binding sites, DNA methylation regions, and other high-throughput features associated with illness. We propose a new approach, called gene set bagging, for measuring the probability that a gene set replicates in future studies. Gene set bagging involves resampling the original high-throughput data, performing gene-set analysis on the resampled data, and confirming that biological categories replicate in the bagged samples.'),
(95879, 2013, 'bmc', 'Detection of attractors of large Boolean networks via exhaustive enumeration of appropriate subspaces of the state space', 'Berntenis, Nikolaos|Ebeling, Martin', 'Non-Clinical-Safety, F, Hoffmann - La Roche AG, Grenzacherstrasse 124, 4070, Basel, Switzerland. nikolaos.berntenis@roche.com.|Non-Clinical-Safety, F, Hoffmann - La Roche AG, Grenzacherstrasse 124, 4070, Basel, Switzerland. nikolaos.berntenis@roche.com.', 'Switzerland|Switzerland', 0, 'Algorithms|Computer Storage Devices|Data Collection|Gene Regulatory Networks|Gene Targeting|Models, Genetic|Proteins|RNA Stability|Signal Transduction|Software|Transcription Factors', 'Comparative Study', '10.1186/1471-2105-14-361', '24330355', 'Boolean models are increasingly used to study biological signaling networks. In a Boolean network, nodes represent biological entities such as genes, proteins or protein complexes, and edges indicate activating or inhibiting influences of one node towards another. Depending on the input of activators or inhibitors, Boolean networks categorize nodes as either active or inactive. The formalism is appealing because for many biological relationships, we lack quantitative information about binding constants or kinetic parameters and can only rely on a qualitative description of the type A activates (or inhibits) B. A central aim of Boolean network analysis is the determination of attractors (steady states and/or cycles). This problem is known to be computationally complex, its most important parameter being the number of network nodes. Various algorithms tackle it with considerable success. In this paper we present an algorithm, which extends the size of analyzable networks thanks to simple and intuitive arguments.'),
(95880, 2013, 'bmc', 'iMir: an integrated pipeline for high-throughput analysis of small non-coding RNA data obtained by smallRNA-Seq', 'Giurato, Giorgio|De Filippo, Maria Rosaria|Rinaldi, Antonio|Hashim, Adnan|Nassa, Giovanni|Ravo, Maria|Rizzo, Francesca|Tarallo, Roberta|Weisz, Alessandro', 'Non-Clinical-Safety, F, Hoffmann - La Roche AG, Grenzacherstrasse 124, 4070, Basel, Switzerland. nikolaos.berntenis@roche.com.|Non-Clinical-Safety, F, Hoffmann - La Roche AG, Grenzacherstrasse 124, 4070, Basel, Switzerland. nikolaos.berntenis@roche.com.|Non-Clinical-Safety, F, Hoffmann - La Roche AG, Grenzacherstrasse 124, 4070, Basel, Switzerland. nikolaos.berntenis@roche.com.|Non-Clinical-Safety, F, Hoffmann - La Roche AG, Grenzacherstrasse 124, 4070, Basel, Switzerland. nikolaos.berntenis@roche.com.|Non-Clinical-Safety, F, Hoffmann - La Roche AG, Grenzacherstrasse 124, 4070, Basel, Switzerland. nikolaos.berntenis@roche.com.|Non-Clinical-Safety, F, Hoffmann - La Roche AG, Grenzacherstrasse 124, 4070, Basel, Switzerland. nikolaos.berntenis@roche.com.|Non-Clinical-Safety, F, Hoffmann - La Roche AG, Grenzacherstrasse 124, 4070, Basel, Switzerland. nikolaos.berntenis@roche.com.|Non-Clinical-Safety, F, Hoffmann - La Roche AG, Grenzacherstrasse 124, 4070, Basel, Switzerland. nikolaos.berntenis@roche.com.|Laboratory of Molecular Medicine and Genomics, Department of Medicine and Surgery, University of Salerno, via Allende, 1, Salerno, Baronissi, Italy. aweisz@unisa.it.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Ital', 44, 'Base Sequence|Binding Sites|Gene Targeting|Genetic Code|Genome-Wide Association Study|Genomics|High-Throughput Nucleotide Sequencing|Humans|MCF-7 Cells|MicroRNAs|Predictive Value of Tests|RNA, Small Untranslated|Sequence Analysis, RNA|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-14-362', '24330401', 'Qualitative and quantitative analysis of small non-coding RNAs by next generation sequencing (smallRNA-Seq) represents a novel technology increasingly used to investigate with high sensitivity and specificity RNA population comprising microRNAs and other regulatory small transcripts. Analysis of smallRNA-Seq data to gather biologically relevant information, i.e. detection and differential expression analysis of known and novel non-coding RNAs, target prediction, etc., requires implementation of multiple statistical and bioinformatics tools from different sources, each focusing on a specific step of the analysis pipeline. As a consequence, the analytical workflow is slowed down by the need for continuous interventions by the operator, a critical factor when large numbers of datasets need to be analyzed at once.'),
(95881, 2013, 'bmc', 'Using passenger mutations to estimate the timing of driver mutations and identify mutator alterations', 'Youn, Ahrim|Simon, Richard', 'Laboratory of Molecular Medicine and Genomics, Department of Medicine and Surgery, University of Salerno, via Allende, 1, Salerno, Baronissi, Italy. aweisz@unisa.it.|Biometric Research Branch, National Cancer Institute, Bethesda, Maryland, USA. rsimon@mail.nih.gov.', 'Italy|United States', 9, 'Cell Transformation, Neoplastic|Computational Biology|Humans|Models, Genetic|Mutation|Neoplasms|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-14-363', '24330428', 'Recent developments in high-throughput genomic technologies make it possible to have a comprehensive view of genomic alterations in tumors on a whole genome scale. Only a small number of somatic alterations detected in tumor genomes are driver alterations which drive tumorigenesis. Most of the somatic alterations are passengers that are neutral to tumor cell selection. Although most research efforts are focused on analyzing driver alterations, the passenger alterations also provide valuable information about the history of tumor development.'),
(95882, 2013, 'bmc', 'A flexible statistical model for alignment of label-free proteomics data--incorporating ion mobility and product ion information', 'Benjamin, Ashlee M|Thompson, J Will|Soderblom, Erik J|Geromanos, Scott J|Henao, Ricardo|Kraus, Virginia B|Moseley, M Arthur|Lucas, Joseph E', 'Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, USA. amb103@duke.edu.|Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, USA. amb103@duke.edu.|Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, USA. amb103@duke.edu.|Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, USA. amb103@duke.edu.|Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, USA. amb103@duke.edu.|Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, USA. amb103@duke.edu.|Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, USA. amb103@duke.edu.|Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, USA. amb103@duke.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States', 4, 'DNA-Binding Proteins|Escherichia coli Proteins|Hepatitis C|Humans|Ions|Models, Genetic|Osteoarthritis|Peptide Fragments|Proteomics|Sequence Alignment|Spectrometry, Mass, Electrospray Ionization|Tandem Mass Spectrometry', 'Comparative Study', '10.1186/1471-2105-14-364', '24341404', 'The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing--the matching of peptide measurements across samples.'),
(95883, 2013, 'bmc', 'Network-based differential gene expression analysis suggests cell cycle related genes regulated by E2F1 underlie the molecular difference between smoker and non-smoker lung adenocarcinoma', 'Wu, Chao|Zhu, Jun|Zhang, Xuegong', 'Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, USA. amb103@duke.edu.|Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Mount Sinai School of Medicine, New York, NY, USA. jun.zhu@mssm.edu.|Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Mount Sinai School of Medicine, New York, NY, USA. jun.zhu@mssm.edu.', 'United States|United States|United States', 0, 'Adenocarcinoma|Adenocarcinoma of Lung|E2F1 Transcription Factor|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Genes, cdc|Humans|Lung Neoplasms|Oligonucleotide Array Sequence Analysis|Phenotype|Smoking', 'Comparative Study', '10.1186/1471-2105-14-365', '24341432', 'Differential gene expression (DGE) analysis is commonly used to reveal the deregulated molecular mechanisms of complex diseases. However, traditional DGE analysis (e.g., the t test or the rank sum test) tests each gene independently without considering interactions between them. Top-ranked differentially regulated genes prioritized by the analysis may not directly relate to the coherent molecular changes underlying complex diseases. Joint analyses of co-expression and DGE have been applied to reveal the deregulated molecular modules underlying complex diseases. Most of these methods consist of separate steps: first to identify gene-gene relationships under the studied phenotype then to integrate them with gene expression changes for prioritizing signature genes, or vice versa. It is warrant a method that can simultaneously consider gene-gene co-expression strength and corresponding expression level changes so that both types of information can be leveraged optimally.'),
(95884, 2013, 'bmc', 'Proceedings of the Third Annual RECOMB Satellite Workshop on Massively Parallel Sequencing (RECOMB-seq 2013), April 11-12, 2013, Beijing, China', '-', '-', '-', 15, 'Animals|Computational Biology|Humans', 'Congress', '10.1186/1471-2105-14-365', '24350336', '-'),
(95885, 2013, 'bmc', 'Variational attenuation correction in two-view confocal microscopy', 'Schmidt, Thorsten|Dürr, Jasmin|Keuper, Margret|Blein, Thomas|Palme, Klaus|Ronneberger, Olaf', 'Department of Computer Science, Albert-Ludwigs-Universität, Georges-Köhler-Allee Geb, 52, 79110 Freiburg, Germany. tschmidt@cs.uni-freiburg.de.|Department of Computer Science, Albert-Ludwigs-Universität, Georges-Köhler-Allee Geb, 52, 79110 Freiburg, Germany. tschmidt@cs.uni-freiburg.de.|Department of Computer Science, Albert-Ludwigs-Universität, Georges-Köhler-Allee Geb, 52, 79110 Freiburg, Germany. tschmidt@cs.uni-freiburg.de.|Department of Computer Science, Albert-Ludwigs-Universität, Georges-Köhler-Allee Geb, 52, 79110 Freiburg, Germany. tschmidt@cs.uni-freiburg.de.|Department of Computer Science, Albert-Ludwigs-Universität, Georges-Köhler-Allee Geb, 52, 79110 Freiburg, Germany. tschmidt@cs.uni-freiburg.de.|Department of Computer Science, Albert-Ludwigs-Universität, Georges-Köhler-Allee Geb, 52, 79110 Freiburg, Germany. tschmidt@cs.uni-freiburg.de.', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Animals|Arabidopsis|Computational Biology|Energy Metabolism|Fluorescent Dyes|Genetic Variation|Image Interpretation, Computer-Assisted|Microscopy, Confocal|Programming Languages|Software|Zebrafish', 'Journal Article', '10.1186/1471-2105-14-366', '24350574', 'Absorption and refraction induced signal attenuation can seriously hinder the extraction of quantitative information from confocal microscopic data. This signal attenuation can be estimated and corrected by algorithms that use physical image formation models. Especially in thick heterogeneous samples, current single view based models are unable to solve the underdetermined problem of estimating the attenuation-free intensities.'),
(95886, 2013, 'bmc', 'Sequencing error correction without a reference genome', 'Sleep, Julie A|Schreiber, Andreas W|Baumann, Ute', 'Australian Centre for Plant Functional Genomics, The University of Adelaide, Urrbrae, SA 5064, Australia. julie.sleep@unisa.edu.au.|Australian Centre for Plant Functional Genomics, The University of Adelaide, Urrbrae, SA 5064, Australia. julie.sleep@unisa.edu.au.|Australian Centre for Plant Functional Genomics, The University of Adelaide, Urrbrae, SA 5064, Australia. julie.sleep@unisa.edu.au.', 'Australia|Australia|Australia', 15, 'Animals|Base Sequence|Chromosome Mapping|Computer Simulation|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Models, Genetic|Sequence Analysis, DNA|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-14-367', '24350580', 'Next (second) generation sequencing is an increasingly important tool for many areas of molecular biology, however, care must be taken when interpreting its output. Even a low error rate can cause a large number of errors due to the high number of nucleotides being sequenced. Identifying sequencing errors from true biological variants is a challenging task. For organisms without a reference genome this difficulty is even more challenging.'),
(95887, 2013, 'bmc', 'Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline', 'Chang, Lun-Ching|Lin, Hui-Min|Sibille, Etienne|Tseng, George C', 'Australian Centre for Plant Functional Genomics, The University of Adelaide, Urrbrae, SA 5064, Australia. julie.sleep@unisa.edu.au.|Australian Centre for Plant Functional Genomics, The University of Adelaide, Urrbrae, SA 5064, Australia. julie.sleep@unisa.edu.au.|Australian Centre for Plant Functional Genomics, The University of Adelaide, Urrbrae, SA 5064, Australia. julie.sleep@unisa.edu.au.|Department of Biostatistics, Graduate school of Public Health, University of Pittsburgh, Pittsburgh, PA, USA. ctseng@pitt.edu.', 'Australia|Australia|Australia|United States', 0, 'Breast Neoplasms|Female|Gene Expression Profiling|Genetic Markers|Genome|Genomics|Humans|Meta-Analysis as Topic|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-14-368', '24359104', 'As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application, the decision essentially requires both statistical and biological considerations.'),
(95888, 2013, 'bmc', 'A comparison study of succinct data structures for use in GWAS', 'Putnam, Patrick P|Zhang, Ge|Wilsey, Philip A', 'Experimental Computing Lab, School of Electronic and Computing Systems, PO Box 210030, Cincinnati, OH 45221-0030, USA. putnampp@gmail.com.|Experimental Computing Lab, School of Electronic and Computing Systems, PO Box 210030, Cincinnati, OH 45221-0030, USA. putnampp@gmail.com.|Experimental Computing Lab, School of Electronic and Computing Systems, PO Box 210030, Cincinnati, OH 45221-0030, USA. putnampp@gmail.com.', 'United States|United States|United States', 0, 'Algorithms|Data Compression|Genome, Human|Genome-Wide Association Study|Genotype|Humans', 'Comparative Study', '10.1186/1471-2105-14-369', '24359123', 'In recent years genetic data analysis has seen a rapid increase in the scale of data to be analyzed. Schadt et al (NRG 11:647-657, 2010) offered that with data sets approaching the petabyte scale, data related challenges such as formatting, management, and transfer are increasingly important topics which need to be addressed. The use of succinct data structures is one method of reducing physical size of a data set without the use of expensive compression techniques. In this work, we consider the use of 2- and 3-bit encoding schemes for genotype data. We compare the computational performance of allele or genotype counting algorithms utilizing genotype data encoded in both schemes.'),
(95889, 2013, 'bmc', 'Blind spots of quantitative RNA-seq: the limits for assessing abundance, differential expression, and isoform switching', 'Rehrauer, Hubert|Opitz, Lennart|Tan, Ge|Sieverling, Lina|Schlapbach, Ralph', 'Functional Genomics Center Zurich, University of Zurich/ETH, Zurich, Switzerland. Hubert.Rehrauer@fgcz.uzh.ch.|Functional Genomics Center Zurich, University of Zurich/ETH, Zurich, Switzerland. Hubert.Rehrauer@fgcz.uzh.ch.|Functional Genomics Center Zurich, University of Zurich/ETH, Zurich, Switzerland. Hubert.Rehrauer@fgcz.uzh.ch.|Functional Genomics Center Zurich, University of Zurich/ETH, Zurich, Switzerland. Hubert.Rehrauer@fgcz.uzh.ch.|Functional Genomics Center Zurich, University of Zurich/ETH, Zurich, Switzerland. Hubert.Rehrauer@fgcz.uzh.ch.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 19, 'Base Sequence|Gene Expression Profiling|Gene Library|Genome, Human|Humans|Models, Statistical|Optic Disk|Protein Isoforms|RNA|Sequence Alignment|Sequence Analysis, RNA|Transcriptome', 'Journal Article', '10.1186/1471-2105-14-370', '24365034', 'RNA-seq is now widely used to quantitatively assess gene expression, expression differences and isoform switching, and promises to deliver results for the entire transcriptome. However, whether the transcriptional state of a gene can be captured accurately depends critically on library preparation, read alignment, expression estimation and the tests for differential expression and isoform switching. There are comparisons available for the individual steps but there is not yet a systematic investigation which specific genes are impacted by biases throughout the entire analysis workflow. It is especially unclear whether for a given gene, with current methods and protocols, expression changes and isoform switches can be detected.'),
(95890, 2013, 'bmc', 'Identification of reproducible gene expression signatures in lung adenocarcinoma', 'Lu, Tzu-Pin|Chuang, Eric Y|Chen, James J', 'Functional Genomics Center Zurich, University of Zurich/ETH, Zurich, Switzerland. Hubert.Rehrauer@fgcz.uzh.ch.|Functional Genomics Center Zurich, University of Zurich/ETH, Zurich, Switzerland. Hubert.Rehrauer@fgcz.uzh.ch.|Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration Jefferson, Little Rock, Arkansas, USA. jamesj.chen@fda.hhs.gov.', 'Switzerland|Switzerland|United States', 12, 'Adenocarcinoma|Adenocarcinoma of Lung|Aged|Female|Gene Expression Regulation, Neoplastic|Gene Library|Humans|Lung Neoplasms|Male|Middle Aged|Proportional Hazards Models|Reproducibility of Results|Survival Rate|Transcriptome', 'Journal Article', '10.1186/1471-2105-14-371', '24369726', 'Lung cancer is the leading cause of cancer-related death worldwide. Tremendous research efforts have been devoted to improving treatment procedures, but the average five-year overall survival rates are still less than 20%. Many biomarkers have been identified for predicting survival, challenges arise, however, in translating the findings into clinical practice due to their inconsistency and irreproducibility. In this study, we proposed an approach by identifying predictive genes through pathways.'),
(95891, 2013, 'bmc', 'A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis', 'Zhang, Wenlu|Feng, Daming|Li, Rongjian|Chernikov, Andrey|Chrisochoides, Nikos|Osgood, Christopher|Konikoff, Charlotte|Newfeld, Stuart|Kumar, Sudhir|Ji, Shuiwang', 'Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration Jefferson, Little Rock, Arkansas, USA. jamesj.chen@fda.hhs.gov.|Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration Jefferson, Little Rock, Arkansas, USA. jamesj.chen@fda.hhs.gov.|Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration Jefferson, Little Rock, Arkansas, USA. jamesj.chen@fda.hhs.gov.|Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration Jefferson, Little Rock, Arkansas, USA. jamesj.chen@fda.hhs.gov.|Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration Jefferson, Little Rock, Arkansas, USA. jamesj.chen@fda.hhs.gov.|Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration Jefferson, Little Rock, Arkansas, USA. jamesj.chen@fda.hhs.gov.|Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration Jefferson, Little Rock, Arkansas, USA. jamesj.chen@fda.hhs.gov.|Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration Jefferson, Little Rock, Arkansas, USA. jamesj.chen@fda.hhs.gov.|Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration Jefferson, Little Rock, Arkansas, USA. jamesj.chen@fda.hhs.gov.|Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA. sji@cs.odu.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Artificial Intelligence|Cluster Analysis|Computational Biology|Drosophila|Gene Expression Profiling|Gene Expression Regulation, Developmental|Image Processing, Computer-Assisted|Software|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-14-372', '24373308', 'Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions.'),
(95892, 2014, 'bmc', 'New mini- zincin structures provide a minimal scaffold for members of this metallopeptidase superfamily', 'Trame, Christine B|Chang, Yuanyuan|Axelrod, Herbert L|Eberhardt, Ruth Y|Coggill, Penelope|Punta, Marco|Rawlings, Neil D', 'Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA. sji@cs.odu.edu.|Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA. sji@cs.odu.edu.|Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA. sji@cs.odu.edu.|Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA. sji@cs.odu.edu.|Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA. sji@cs.odu.edu.|Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA. sji@cs.odu.edu.|Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK. ndr@ebi.ac.uk.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Actinomycetales|Amino Acid Motifs|Amino Acid Sequence|Bacterial Proteins|Dimerization|Metalloproteases|Models, Molecular|Molecular Sequence Data|Phylogeny|Protein Subunits|Sequence Alignment|Zinc', 'Journal Article', '10.1186/1471-2105-15-1', '24383880', 'The Acel_2062 protein from Acidothermus cellulolyticus is a protein of unknown function. Initial sequence analysis predicted that it was a metallopeptidase from the presence of a motif conserved amongst the Asp-zincins, which are peptidases that contain a single, catalytic zinc ion ligated by the histidines and aspartic acid within the motif (HEXXHXXGXXD). The Acel_2062 protein was chosen by the Joint Center for Structural Genomics for crystal structure determination to explore novel protein sequence space and structure-based function annotation.'),
(95893, 2014, 'bmc', 'Diminishing return for increased Mappability with longer sequencing reads: implications of the k-mer distributions in the human genome', 'Li, Wentian|Freudenberg, Jan|Miramontes, Pedro', 'The Robert S, Boas Center for Genomics and Human Genetic, The Feinstein Institute for Medical Research, North Shore LIJ Health System, 350 Community Drive, Manhasset, USA. wtli2012@gmail.com.|The Robert S, Boas Center for Genomics and Human Genetic, The Feinstein Institute for Medical Research, North Shore LIJ Health System, 350 Community Drive, Manhasset, USA. wtli2012@gmail.com.|The Robert S, Boas Center for Genomics and Human Genetic, The Feinstein Institute for Medical Research, North Shore LIJ Health System, 350 Community Drive, Manhasset, USA. wtli2012@gmail.com.', 'United States|United States|United States', 25, 'Chromosome Mapping|Genome, Human|Genomics|Humans|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-15-2', '24386976', 'The amount of non-unique sequence (non-singletons) in a genome directly affects the difficulty of read alignment to a reference assembly for high throughput-sequencing data. Although a longer read is more likely to be uniquely mapped to the reference genome, a quantitative analysis of the influence of read lengths on mappability has been lacking. To address this question, we evaluate the k-mer distribution of the human reference genome. The k-mer frequency is determined for k ranging from 20 bp to 1000 bp.'),
(95894, 2014, 'bmc', 'Critical assessment of coalescent simulators in modeling recombination hotspots in genomic sequences', 'Yang, Tao|Deng, Hong-Wen|Niu, Tianhua', 'The Robert S, Boas Center for Genomics and Human Genetic, The Feinstein Institute for Medical Research, North Shore LIJ Health System, 350 Community Drive, Manhasset, USA. wtli2012@gmail.com.|The Robert S, Boas Center for Genomics and Human Genetic, The Feinstein Institute for Medical Research, North Shore LIJ Health System, 350 Community Drive, Manhasset, USA. wtli2012@gmail.com.|Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Suite 2001, New Orleans, LA 70112, USA. tniu@tulane.edu.', 'United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|Computer Simulation|Databases, Genetic|Evolution, Molecular|Genetics, Population|Genome|Genomics|Humans|Linkage Disequilibrium|Models, Genetic|Polymorphism, Single Nucleotide|Recombination, Genetic|Reproducibility of Results|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-15-3', '24387001', 'Coalescent simulation is pivotal for understanding population evolutionary models and demographic histories, as well as for developing novel analytical methods for genetic association studies for DNA sequence data. A plethora of coalescent simulators are developed, but selecting the most appropriate program remains challenging.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(95895, 2014, 'bmc', 'Identification of RNA silencing components in soybean and sorghum', 'Liu, Xiang|Lu, Tao|Dou, Yongchao|Yu, Bin|Zhang, Chi', 'Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Suite 2001, New Orleans, LA 70112, USA. tniu@tulane.edu.|Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Suite 2001, New Orleans, LA 70112, USA. tniu@tulane.edu.|Center for Bioinformatics and Genomics, Department of Biostatistics and Bioinformatics, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Suite 2001, New Orleans, LA 70112, USA. tniu@tulane.edu.|School of Biological Sciences & Center for Plant Science and Innovation, University of Nebraska, Lincoln, NE 68588, USA. byu3@unl.edu.|School of Biological Sciences & Center for Plant Science and Innovation, University of Nebraska, Lincoln, NE 68588, USA. byu3@unl.edu.', 'United States|United States|United States|United States|United States', 20, 'Arabidopsis|Genes, Plant|MicroRNAs|Phylogeny|RNA Interference|RNA, Small Interfering|Sorghum|Soybeans', 'Journal Article', '10.1186/1471-2105-15-4', '24387046', 'RNA silencing is a process triggered by 21-24 small RNAs to repress gene expression. Many organisms including plants use RNA silencing to regulate development and physiology, and to maintain genome stability. Plants possess two classes of small RNAs: microRNAs (miRNAs) and small interfering RNAs (siRNAs). The frameworks of miRNA and siRNA pathways have been established in the model plant, Arabidopsis thaliana (Arabidopsis).'),
(95896, 2014, 'bmc', 'Quantitative prediction of the effect of genetic variation using hidden Markov models', 'Liu, Mingming|Watson, Layne T|Zhang, Liqing', 'School of Biological Sciences & Center for Plant Science and Innovation, University of Nebraska, Lincoln, NE 68588, USA. byu3@unl.edu.|School of Biological Sciences & Center for Plant Science and Innovation, University of Nebraska, Lincoln, NE 68588, USA. byu3@unl.edu.|Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA. lqzhang@cs.vt.edu.', 'United States|United States|United States', 12, 'Computational Biology|Genetic Variation|Genome, Human|Humans|INDEL Mutation|Markov Chains|Models, Genetic|Models, Statistical|Proteins|ROC Curve', 'Journal Article', '10.1186/1471-2105-15-5', '24405700', 'With the development of sequencing technologies, more and more sequence variants are available for investigation. Different classes of variants in the human genome have been identified, including single nucleotide substitutions, insertion and deletion, and large structural variations such as duplications and deletions. Insertion and deletion (indel) variants comprise a major proportion of human genetic variation. However, little is known about their effects on humans. The absence of understanding is largely due to the lack of both biological data and computational resources.'),
(95897, 2014, 'bmc', 'Toward an accurate prediction of inter-residue distances in proteins using 2D recursive neural networks', 'Kukic, Predrag|Mirabello, Claudio|Tradigo, Giuseppe|Walsh, Ian|Veltri, Pierangelo|Pollastri, Gianluca', 'School of Computer Science and Informatics, Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland. pk397@cam.ac.uk.|School of Computer Science and Informatics, Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland. pk397@cam.ac.uk.|School of Computer Science and Informatics, Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland. pk397@cam.ac.uk.|School of Computer Science and Informatics, Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland. pk397@cam.ac.uk.|School of Computer Science and Informatics, Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland. pk397@cam.ac.uk.|School of Computer Science and Informatics, Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland. pk397@cam.ac.uk.', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland', 14, 'Algorithms|Computational Biology|Databases, Protein|Models, Molecular|Neural Networks (Computer)|Protein Conformation|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-15-6', '24410833', 'Protein inter-residue contact maps provide a translation and rotation invariant topological representation of a protein. They can be used as an intermediary step in protein structure predictions. However, the prediction of contact maps represents an unbalanced problem as far fewer examples of contacts than non-contacts exist in a protein structure.In this study we explore the possibility of completely eliminating the unbalanced nature of the contact map prediction problem by predicting real-value distances between residues. Predicting full inter-residue distance maps and applying them in protein structure predictions has been relatively unexplored in the past.'),
(95898, 2014, 'bmc', 'Skylign: a tool for creating informative, interactive logos representing sequence alignments and profile hidden Markov models', 'Wheeler, Travis J|Clements, Jody|Finn, Robert D', 'HHMI Janelia Farm Research Campus, Ashburn, VA 20147, USA. wheelert@janelia.hhmi.org.|HHMI Janelia Farm Research Campus, Ashburn, VA 20147, USA. wheelert@janelia.hhmi.org.|HHMI Janelia Farm Research Campus, Ashburn, VA 20147, USA. wheelert@janelia.hhmi.org.', 'United States|United States|United States', 125, 'Amino Acid Sequence|Base Sequence|Computational Biology|Computer Graphics|DNA|Internet|Molecular Sequence Data|Sequence Alignment|Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-15-7', '24410852', 'Logos are commonly used in molecular biology to provide a compact graphical representation of the conservation pattern of a set of sequences. They render the information contained in sequence alignments or profile hidden Markov models by drawing a stack of letters for each position, where the height of the stack corresponds to the conservation at that position, and the height of each letter within a stack depends on the frequency of that letter at that position.'),
(95899, 2014, 'bmc', 'Robustness of Random Forest-based gene selection methods', 'Kursa, Miron Bartosz', 'Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, Pawinskiego 5A, 02-106 Warsaw, Poland. M.Kursa@icm.edu.pl.', 'Poland', 80, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computational Biology|Databases, Genetic|Decision Trees|Genetic Markers|Humans|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-15-8', '24410865', 'Gene selection is an important part of microarray data analysis because it provides information that can lead to a better mechanistic understanding of an investigated phenomenon. At the same time, gene selection is very difficult because of the noisy nature of microarray data. As a consequence, gene selection is often performed with machine learning methods. The Random Forest method is particularly well suited for this purpose. In this work, four state-of-the-art Random Forest-based feature selection methods were compared in a gene selection context. The analysis focused on the stability of selection because, although it is necessary for determining the significance of results, it is often ignored in similar studies.'),
(95900, 2014, 'bmc', 'Efficient haplotype block recognition of very long and dense genetic sequences', 'Taliun, Daniel|Gamper, Johann|Pattaro, Cristian', 'Center for Biomedicine, European Academy of Bolzano/Bozen (EURAC), Bozen-Bolzano, Italy. daniel.taliun@eurac.edu.|Center for Biomedicine, European Academy of Bolzano/Bozen (EURAC), Bozen-Bolzano, Italy. daniel.taliun@eurac.edu.|Center for Biomedicine, European Academy of Bolzano/Bozen (EURAC), Bozen-Bolzano, Italy. daniel.taliun@eurac.edu.', 'Italy|Italy|Italy', 15, 'Algorithms|Arthritis, Rheumatoid|Computational Biology|Gene Frequency|Genome|Haplotypes|Humans|Linkage Disequilibrium|Models, Genetic|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-15-10', '24423111', 'The new sequencing technologies enable to scan very long and dense genetic sequences, obtaining datasets of genetic markers that are an order of magnitude larger than previously available. Such genetic sequences are characterized by common alleles interspersed with multiple rarer alleles. This situation has renewed the interest for the identification of haplotypes carrying the rare risk alleles. However, large scale explorations of the linkage-disequilibrium (LD) pattern to identify haplotype blocks are not easy to perform, because traditional algorithms have at least xcex98(n2) time and memory complexity.'),
(95901, 2014, 'bmc', 'kruX: matrix-based non-parametric eQTL discovery', 'Qi, Jianlong|Asl, Hassan Foroughi|Björkegren, Johan|Michoel, Tom', 'Center for Biomedicine, European Academy of Bolzano/Bozen (EURAC), Bozen-Bolzano, Italy. daniel.taliun@eurac.edu.|Center for Biomedicine, European Academy of Bolzano/Bozen (EURAC), Bozen-Bolzano, Italy. daniel.taliun@eurac.edu.|Center for Biomedicine, European Academy of Bolzano/Bozen (EURAC), Bozen-Bolzano, Italy. daniel.taliun@eurac.edu.|School of Life Sciences - LifeNet, Freiburg Institute for Advanced Studies (FRIAS), University of Freiburg, Freiburg, Germany. tom.michoel@roslin.ed.ac.uk.', 'Italy|Italy|Italy|Germany', 14, 'Algorithms|Computational Biology|Genome|Genotype|Humans|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Reproducibility of Results|Software|Statistics, Nonparametric', 'Journal Article', '10.1186/1471-2105-15-11', '24423115', 'The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive.'),
(95902, 2014, 'bmc', 'GIANT: pattern analysis of molecular interactions in 3D structures of protein-small ligand complexes', 'Kasahara, Kota|Kinoshita, Kengo', 'School of Life Sciences - LifeNet, Freiburg Institute for Advanced Studies (FRIAS), University of Freiburg, Freiburg, Germany. tom.michoel@roslin.ed.ac.uk.|Graduate School of Information Sciences, Tohoku University, 6-3-09 Aoba, Aramaki, Aoba-ku, Sendai, Miyagi 980-8597, Japan. kengo@ecei.tohoku.ac.jp.', 'Germany|Japan', 9, 'Computational Biology|Databases, Protein|Hydrogen Bonding|Internet|Ligands|Pattern Recognition, Automated|Protein Conformation|Proteins|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-15-12', '24423161', 'Interpretation of binding modes of protein-small ligand complexes from 3D structure data is essential for understanding selective ligand recognition by proteins. It is often performed by visual inspection and sometimes largely depends on a priori knowledge about typical interactions such as hydrogen bonds and xcfx80-xcfx80 stacking. Because it can introduce some biases due to scientists subjective perspectives, more objective viewpoints considering a wide range of interactions are required.'),
(95903, 2014, 'bmc', 'gsGator: an integrated web platform for cross-species gene set analysis', 'Kang, Hyunjung|Choi, Ikjung|Cho, Sooyoung|Ryu, Daeun|Lee, Sanghyuk|Kim, Wankyu', 'Graduate School of Information Sciences, Tohoku University, 6-3-09 Aoba, Aramaki, Aoba-ku, Sendai, Miyagi 980-8597, Japan. kengo@ecei.tohoku.ac.jp.|Graduate School of Information Sciences, Tohoku University, 6-3-09 Aoba, Aramaki, Aoba-ku, Sendai, Miyagi 980-8597, Japan. kengo@ecei.tohoku.ac.jp.|Graduate School of Information Sciences, Tohoku University, 6-3-09 Aoba, Aramaki, Aoba-ku, Sendai, Miyagi 980-8597, Japan. kengo@ecei.tohoku.ac.jp.|Graduate School of Information Sciences, Tohoku University, 6-3-09 Aoba, Aramaki, Aoba-ku, Sendai, Miyagi 980-8597, Japan. kengo@ecei.tohoku.ac.jp.|Graduate School of Information Sciences, Tohoku University, 6-3-09 Aoba, Aramaki, Aoba-ku, Sendai, Miyagi 980-8597, Japan. kengo@ecei.tohoku.ac.jp.|Ewha Global Top5 Research Program, Ewha Womans University, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 120-750, Korea. wkim@ewha.ac.kr.', 'Japan|Japan|Japan|Japan|Japan|-', 5, 'Animals|Databases, Genetic|Genome|Genomics|Humans|Internet|Mice|Molecular Sequence Annotation|Protein Interaction Maps|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-15-13', '24423189', 'Gene set analysis (GSA) is useful in deducing biological significance of gene lists using a priori defined gene sets such as gene ontology (GO) or pathways. Phenotypic annotation is sparse for human genes, but is far more abundant for other model organisms such as mouse, fly, and worm. Often, GSA needs to be done highly interactively by combining or modifying gene lists or inspecting gene-gene interactions in a molecular network.'),
(95904, 2014, 'bmc', 'Fold change rank ordering statistics: a new method for detecting differentially expressed genes', 'Dembélé, Doulaye|Kastner, Philippe', 'Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U964, CNRS UMR 7104, Université de Strasbourg, 67404 Illkirch, France. doulaye@igbmc.fr.|Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U964, CNRS UMR 7104, Université de Strasbourg, 67404 Illkirch, France. doulaye@igbmc.fr.', 'France|France', 59, 'Algorithms|Computational Biology|Computer Simulation|Databases, Genetic|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-15-14', '24423217', 'Different methods have been proposed for analyzing differentially expressed (DE) genes in microarray data. Methods based on statistical tests that incorporate expression level variability are used more commonly than those based on fold change (FC). However, FC based results are more reproducible and biologically relevant.'),
(95905, 2014, 'bmc', 'A generic classification-based method for segmentation of nuclei in 3D images of early embryos', 'Gul-Mohammed, Jaza|Arganda-Carreras, Ignacio|Andrey, Philippe|Galy, Vincent|Boudier, Thomas', 'Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U964, CNRS UMR 7104, Université de Strasbourg, 67404 Illkirch, France. doulaye@igbmc.fr.|Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U964, CNRS UMR 7104, Université de Strasbourg, 67404 Illkirch, France. doulaye@igbmc.fr.|Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U964, CNRS UMR 7104, Université de Strasbourg, 67404 Illkirch, France. doulaye@igbmc.fr.|Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U964, CNRS UMR 7104, Université de Strasbourg, 67404 Illkirch, France. doulaye@igbmc.fr.|Sorbonne Universités, UPMC Univ Paris 06, 4 place Jussieu, 75005 Paris, France. thomas.boudier@snv.jussieu.fr.', 'France|France|France|France|France', 18, 'Algorithms|Animals|Caenorhabditis elegans|Cell Nucleus|Computational Biology|Databases, Factual|Drosophila|Embryo, Nonmammalian|Imaging, Three-Dimensional|Models, Genetic', 'Journal Article', '10.1186/1471-2105-15-9', '24423252', 'Studying how individual cells spatially and temporally organize within the embryo is a fundamental issue in modern developmental biology to better understand the first stages of embryogenesis. In order to perform high-throughput analyses in three-dimensional microscopic images, it is essential to be able to automatically segment, classify and track cell nuclei. Many 3D/4D segmentation and tracking algorithms have been reported in the literature. Most of them are specific to particular models or acquisition systems and often require the fine tuning of parameters.'),
(95906, 2014, 'bmc', 'OncomiRdbB: a comprehensive database of microRNAs and their targets in breast cancer', 'Khurana, Rimpi|Verma, Vinod Kumar|Rawoof, Abdul|Tiwari, Shrish|Nair, Rekha A|Mahidhara, Ganesh|Idris, Mohammed M|Clarke, Alan R|Kumar, Lekha Dinesh', 'Sorbonne Universités, UPMC Univ Paris 06, 4 place Jussieu, 75005 Paris, France. thomas.boudier@snv.jussieu.fr.|Sorbonne Universités, UPMC Univ Paris 06, 4 place Jussieu, 75005 Paris, France. thomas.boudier@snv.jussieu.fr.|Sorbonne Universités, UPMC Univ Paris 06, 4 place Jussieu, 75005 Paris, France. thomas.boudier@snv.jussieu.fr.|Sorbonne Universités, UPMC Univ Paris 06, 4 place Jussieu, 75005 Paris, France. thomas.boudier@snv.jussieu.fr.|Sorbonne Universités, UPMC Univ Paris 06, 4 place Jussieu, 75005 Paris, France. thomas.boudier@snv.jussieu.fr.|Sorbonne Universités, UPMC Univ Paris 06, 4 place Jussieu, 75005 Paris, France. thomas.boudier@snv.jussieu.fr.|Sorbonne Universités, UPMC Univ Paris 06, 4 place Jussieu, 75005 Paris, France. thomas.boudier@snv.jussieu.fr.|Sorbonne Universités, UPMC Univ Paris 06, 4 place Jussieu, 75005 Paris, France. thomas.boudier@snv.jussieu.fr.|Cancer Biology, Centre for Cellular & Molecular Biology, Council of scientific and Industrial Research, Hyderabad, A,P, India. lekha@ccmb.res.in', 'France|France|France|France|France|France|France|France|India', 8, '3 Untranslated Regions|Algorithms|Animals|Breast Neoplasms|Computational Biology|Databases, Nucleic Acid|Female|Humans|Mice|MicroRNAs', 'Journal Article', '10.1186/1471-2105-15-15', '24428888', 'Given the estimate that 30% of our genes are controlled by microRNAs, it is essential that we understand the precise relationship between microRNAs and their targets. OncomiRs are microRNAs (miRNAs) that have been frequently shown to be deregulated in cancer. However, although several oncomiRs have been identified and characterized, there is as yet no comprehensive compilation of this data which has rendered it underutilized by cancer biologists. There is therefore an unmet need in generating bioinformatic platforms to speed the identification of novel therapeutic targets.'),
(95907, 2014, 'bmc', 'Joint probabilistic-logical refinement of multiple protein feature predictors', 'Teso, Stefano|Passerini, Andrea', 'Department of Information Engineering and Computer Science, Università degli Studi di Trento, Trento, Italy. teso@disi.unitn.it.|Department of Information Engineering and Computer Science, Università degli Studi di Trento, Trento, Italy. teso@disi.unitn.it.', 'Italy|Italy', 1, 'Algorithms|Computational Biology|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-15-16', '24428894', 'Computational methods for the prediction of protein features from sequence are a long-standing focus of bioinformatics. A key observation is that several protein features are closely inter-related, that is, they are conditioned on each other. Researchers invested a lot of effort into designing predictors that exploit this fact. Most existing methods leverage inter-feature constraints by including known (or predicted) correlated features as inputs to the predictor, thus conditioning the result.'),
(95908, 2014, 'bmc', 'Large-scale combining signals from both biomedical literature and the FDA Adverse Event Reporting System (FAERS) to improve post-marketing drug safety signal detection', 'Xu, Rong|Wang, QuanQiu', 'Medical Informatics Division, Case Western Reserve, Cleveland, Ohio, USA. rxx@case.edu.|Medical Informatics Division, Case Western Reserve, Cleveland, Ohio, USA. rxx@case.edu.', 'United States|United States', 37, 'Adverse Drug Reaction Reporting Systems|Algorithms|Biomarkers, Pharmacological|Data Mining|Drug-Related Side Effects and Adverse Reactions|Humans|MEDLINE|Patient Safety|Product Surveillance, Postmarketing|United States|United States Food and Drug Administration', 'Journal Article', '10.1186/1471-2105-15-17', '24428898', 'Independent data sources can be used to augment post-marketing drug safety signal detection. The vast amount of publicly available biomedical literature contains rich side effect information for drugs at all clinical stages. In this study, we present a large-scale signal boosting approach that combines over 4 million records in the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and over 21 million biomedical articles.'),
(95909, 2014, 'bmc', 'ISAAC - InterSpecies Analysing Application using Containers', 'Baier, Herbert|Schultz, Jörg', 'Medical Informatics Division, Case Western Reserve, Cleveland, Ohio, USA. rxx@case.edu.|Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, Würzburg 97074, Germany. joerg.schultz@biozentrum.uni-wuerzburg.de.', 'United States|Germany', 4, 'Animals|Computational Biology|Databases, Genetic|Genes|Humans|Internet|Mice|Proteins|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-15-18', '24428905', 'Information about genes, transcripts and proteins is spread over a wide variety of databases. Different tools have been developed using these databases to identify biological signals in gene lists from large scale analysis. Mostly, they search for enrichments of specific features. But, these tools do not allow an explorative walk through different views and to change the gene lists according to newly upcoming stories.'),
(95910, 2014, 'bmc', 'Automated alignment-based curation of gene models in filamentous fungi', 'van der Burgt, Ate|Severing, Edouard|Collemare, Jérôme|de Wit, Pierre J G M', 'Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, Würzburg 97074, Germany. joerg.schultz@biozentrum.uni-wuerzburg.de.|Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, Würzburg 97074, Germany. joerg.schultz@biozentrum.uni-wuerzburg.de.|Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, Würzburg 97074, Germany. joerg.schultz@biozentrum.uni-wuerzburg.de.|Laboratory of Phytopathology, Wageningen University & Research Centre, P,O, Box 16, 6700 AA Wageningen, The Netherlands. pierre.dewit@wur.nl.', 'Germany|Germany|Germany|Netherlands', 8, 'Amino Acid Sequence|Cladosporium|Computational Biology|Databases, Genetic|Genes, Fungal|Models, Genetic|Molecular Sequence Data|Reproducibility of Results|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-15-19', '24433567', 'Automated gene-calling is still an error-prone process, particularly for the highly plastic genomes of fungal species. Improvement through quality control and manual curation of gene models is a time-consuming process that requires skilled biologists and is only marginally performed. The wealth of available fungal genomes has not yet been exploited by an automated method that applies quality control of gene models in order to obtain more accurate genome annotations.'),
(95911, 2014, 'bmc', 'Tracing retinal vessel trees by transductive inference', 'De, Jaydeep|Li, Huiqi|Cheng, Li', 'Laboratory of Phytopathology, Wageningen University & Research Centre, P,O, Box 16, 6700 AA Wageningen, The Netherlands. pierre.dewit@wur.nl.|Laboratory of Phytopathology, Wageningen University & Research Centre, P,O, Box 16, 6700 AA Wageningen, The Netherlands. pierre.dewit@wur.nl.|Bioinformatics Institute, A*STAR, Singapore, Singapore. chengli@bii.a-star.edu.sg.', 'Netherlands|Netherlands|Singapore', 13, 'Algorithms|Artificial Intelligence|Computational Biology|Computer Simulation|Databases, Factual|Fundus Oculi|Humans|Image Processing, Computer-Assisted|Retinal Vessels', 'Journal Article', '10.1186/1471-2105-15-20', '24438151', 'Structural study of retinal blood vessels provides an early indication of diseases such as diabetic retinopathy, glaucoma, and hypertensive retinopathy. These studies require accurate tracing of retinal vessel tree structure from fundus images in an automated manner. However, the existing work encounters great difficulties when dealing with the crossover issue commonly-seen in vessel networks.'),
(95912, 2014, 'bmc', 'Differential expression of microRNAs as predictors of glioblastoma phenotypes', 'Bradley, Barrie S|Loftus, Joseph C|Mielke, Clinton J|Dinu, Valentin', 'Department of Biomedical Informatics, Arizona State University, 13212 East Shea Boulevard, Scottsdale, AZ 85259, USA. barrie.bradley@asu.edu.|Department of Biomedical Informatics, Arizona State University, 13212 East Shea Boulevard, Scottsdale, AZ 85259, USA. barrie.bradley@asu.edu.|Department of Biomedical Informatics, Arizona State University, 13212 East Shea Boulevard, Scottsdale, AZ 85259, USA. barrie.bradley@asu.edu.|Department of Biomedical Informatics, Arizona State University, 13212 East Shea Boulevard, Scottsdale, AZ 85259, USA. barrie.bradley@asu.edu.', 'United States|United States|United States|United States', 8, 'Apoptosis|Cell Line, Tumor|Cell Movement|Computational Biology|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Glioblastoma|Humans|MicroRNAs|Neoplasm Invasiveness|Phenotype', 'Journal Article', '10.1186/1471-2105-15-21', '24438171', 'Glioblastoma is the most aggressive primary central nervous tumor and carries a very poor prognosis. Invasion precludes effective treatment and virtually assures tumor recurrence. In the current study, we applied analytical and bioinformatics approaches to identify a set of microRNAs (miRs) from several different human glioblastoma cell lines that exhibit significant differential expression between migratory (edge) and migration-restricted (core) cell populations. The hypothesis of the study is that differential expression of miRs provides an epigenetic mechanism to drive cell migration and invasion.'),
(95913, 2014, 'bmc', 'BioShell-Threading: versatile Monte Carlo package for protein 3D threading', 'Gniewek, Pawel|Kolinski, Andrzej|Kloczkowski, Andrzej|Gront, Dominik', 'Department of Biomedical Informatics, Arizona State University, 13212 East Shea Boulevard, Scottsdale, AZ 85259, USA. barrie.bradley@asu.edu.|Department of Biomedical Informatics, Arizona State University, 13212 East Shea Boulevard, Scottsdale, AZ 85259, USA. barrie.bradley@asu.edu.|Department of Biomedical Informatics, Arizona State University, 13212 East Shea Boulevard, Scottsdale, AZ 85259, USA. barrie.bradley@asu.edu.|Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland. dgront@chem.uw.edu.pl.', 'United States|United States|United States|Poland', 12, 'Algorithms|Amino Acid Sequence|Computational Biology|Computer Simulation|Models, Molecular|Monte Carlo Method|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-15-22', '24444459', 'The comparative modeling approach to protein structure prediction inherently relies on a template structure. Before building a model such a template protein has to be found and aligned with the query sequence. Any error made on this stage may dramatically affects the quality of result. There is a need, therefore, to develop accurate and sensitive alignment protocols.'),
(95914, 2014, 'bmc', 'Gene expression and nucleotide composition are associated with genic methylation level in Oryza sativa', 'Elhaik, Eran|Pellegrini, Matteo|Tatarinova, Tatiana V', 'Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland. dgront@chem.uw.edu.pl.|Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland. dgront@chem.uw.edu.pl.|Childrens Hospital Los Angeles, Keck School of Medicine, University of Southern California, 4650 Sunset Blvd, Los Angeles, CA 90027, USA. Tatiana.tatarinova@usc.edu.', 'Poland|Poland|United States', 8, 'Base Composition|Codon|Computational Biology|Cytosine|DNA Methylation|Gene Expression Regulation, Plant|Humans|Oryza|Reproducibility of Results|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-15-23', '24447369', 'The methylation of cytosines at CpG dinucleotides, which plays an important role in gene expression regulation, is one of the most studied epigenetic modifications. Thus far, the detection of DNA methylation has been determined mostly by experimental methods, which are not only prone to bench effects and artifacts but are also time-consuming, expensive, and cannot be easily scaled up to many samples. It is therefore useful to develop computational prediction methods for DNA methylation. Our previous studies highlighted the existence of correlations between the GC content of the third codon position (GCxe2x82x83), methylation, and gene expression. We thus designed a model to predict methylation in Oryza sativa based on genomic sequence features and gene expression data.'),
(95915, 2014, 'bmc', 'A method to incorporate prior information into score test for genetic association studies', 'Zakharov, Sergii|Teoh, Garrett H K|Salim, Agus|Thalamuthu, Anbupalam', 'Human Genetics, Genome Institute of Singapore, 60 Biopolis Street, #02-01 Genome, Singapore 138672, Singapore. zakharovs99@gis.a-star.edu.sg.|Human Genetics, Genome Institute of Singapore, 60 Biopolis Street, #02-01 Genome, Singapore 138672, Singapore. zakharovs99@gis.a-star.edu.sg.|Human Genetics, Genome Institute of Singapore, 60 Biopolis Street, #02-01 Genome, Singapore 138672, Singapore. zakharovs99@gis.a-star.edu.sg.|Human Genetics, Genome Institute of Singapore, 60 Biopolis Street, #02-01 Genome, Singapore 138672, Singapore. zakharovs99@gis.a-star.edu.sg.', 'Singapore|Singapore|Singapore|Singapore', 0, 'Computational Biology|Genetic Association Studies|Genetic Variation|Genetics, Population|Models, Genetic|Phenotype', 'Journal Article', '10.1186/1471-2105-15-24', '24450486', 'The interest of the scientific community in investigating the impact of rare variants on complex traits has stimulated the development of novel statistical methodologies for association studies. The fact that many of the recently proposed methods for association studies suffer from low power to identify a genetic association motivates the incorporation of prior knowledge into statistical tests.'),
(95916, 2014, 'bmc', 'A modular computational framework for automated peak extraction from ion mobility spectra', 'DAddario, Marianna|Kopczynski, Dominik|Baumbach, Jörg Ingo|Rahmann, Sven', 'Human Genetics, Genome Institute of Singapore, 60 Biopolis Street, #02-01 Genome, Singapore 138672, Singapore. zakharovs99@gis.a-star.edu.sg.|Human Genetics, Genome Institute of Singapore, 60 Biopolis Street, #02-01 Genome, Singapore 138672, Singapore. zakharovs99@gis.a-star.edu.sg.|Human Genetics, Genome Institute of Singapore, 60 Biopolis Street, #02-01 Genome, Singapore 138672, Singapore. zakharovs99@gis.a-star.edu.sg.|Collaborative Research Center SFB 876, TU Dortmund University, Dortmund, Germany. Sven.Rahmann@uni-due.de.', 'Singapore|Singapore|Singapore|Germany', 0, 'Biomarkers|Breath Tests|Case-Control Studies|Computational Biology|Humans|Ions|Signal Processing, Computer-Assisted|Software|Spectrum Analysis|Volatile Organic Compounds', 'Journal Article', '10.1186/1471-2105-15-25', '24450533', 'An ion mobility (IM) spectrometer coupled with a multi-capillary column (MCC) measures volatile organic compounds (VOCs) in the air or in exhaled breath. This technique is utilized in several biotechnological and medical applications. Each peak in an MCC/IM measurement represents a certain compound, which may be known or unknown. For clustering and classification of measurements, the raw data matrix must be reduced to a set of peaks. Each peak is described by its coordinates (retention time in the MCC and reduced inverse ion mobility) and shape (signal intensity, further shape parameters). This fundamental step is referred to as peak extraction. It is the basis for identifying discriminating peaks, and hence putative biomarkers, between two classes of measurements, such as a healthy control group and a group of patients with a confirmed disease. Current state-of-the-art peak extraction methods require human interaction, such as hand-picking approximate peak locations, assisted by a visualization of the data matrix. In a high-throughput context, however, it is preferable to have robust methods for fully automated peak extraction.'),
(95917, 2014, 'bmc', 'Incorporating the type and direction information in predicting novel regulatory interactions between HIV-1 and human proteins using a biclustering approach', 'Mukhopadhyay, Anirban|Ray, Sumanta|Maulik, Ujjwal', 'Collaborative Research Center SFB 876, TU Dortmund University, Dortmund, Germany. Sven.Rahmann@uni-due.de.|Department of Computer Science and Engineering, Aliah University, Kolkata-700091, West Bengal, India. sumantababai86@gmail.com.|Department of Computer Science and Engineering, Aliah University, Kolkata-700091, West Bengal, India. sumantababai86@gmail.com.', 'Germany|India|India', 25, 'Cluster Analysis|Computational Biology|Databases, Factual|HIV Infections|HIV-1|Host-Pathogen Interactions|Humans|Protein Interaction Mapping|Proteins', 'Journal Article', '10.1186/1471-2105-15-26', '24460683', 'Discovering novel interactions between HIV-1 and human proteins would greatly contribute to different areas of HIV research. Identification of such interactions leads to a greater insight into drug target prediction. Some recent studies have been conducted for computational prediction of new interactions based on the experimentally validated information stored in a HIV-1-human protein-protein interaction database. However, these techniques do not predict any regulatory mechanism between HIV-1 and human proteins by considering interaction types and direction of regulation of interactions.'),
(95918, 2014, 'bmc', 'Using single cell sequencing data to model the evolutionary history of a tumor', 'Kim, Kyung In|Simon, Richard', 'Department of Computer Science and Engineering, Aliah University, Kolkata-700091, West Bengal, India. sumantababai86@gmail.com.|Biometric Research Branch, National Cancer Institute, 9609 Medical Center Dr,, MSC 9735 Bethesda, MD 20892, USA. rsimon@mail.nih.gov.', 'India|United States', 34, 'Computational Biology|Evolution, Molecular|Genome|High-Throughput Nucleotide Sequencing|Humans|Mutation|Neoplasms|Single-Cell Analysis|Tumor Cells, Cultured', 'Journal Article', '10.1186/1471-2105-15-27', '24460695', 'The introduction of next-generation sequencing (NGS) technology has made it possible to detect genomic alterations within tumor cells on a large scale. However, most applications of NGS show the genetic content of mixtures of cells. Recently developed single cell sequencing technology can identify variation within a single cell. Characterization of multiple samples from a tumor using single cell sequencing can potentially provide information on the evolutionary history of that tumor. This may facilitate understanding how key mutations accumulate and evolve in lineages to form a heterogeneous tumor.'),
(95919, 2014, 'bmc', 'Non-synonymous variations in cancer and their effects on the human proteome: workflow for NGS data biocuration and proteome-wide analysis of TCGA data', 'Cole, Charles|Krampis, Konstantinos|Karagiannis, Konstantinos|Almeida, Jonas S|Faison, William J|Motwani, Mona|Wan, Quan|Golikov, Anton|Pan, Yang|Simonyan, Vahan|Mazumder, Raja', 'Biometric Research Branch, National Cancer Institute, 9609 Medical Center Dr,, MSC 9735 Bethesda, MD 20892, USA. rsimon@mail.nih.gov.|Biometric Research Branch, National Cancer Institute, 9609 Medical Center Dr,, MSC 9735 Bethesda, MD 20892, USA. rsimon@mail.nih.gov.|Biometric Research Branch, National Cancer Institute, 9609 Medical Center Dr,, MSC 9735 Bethesda, MD 20892, USA. rsimon@mail.nih.gov.|Biometric Research Branch, National Cancer Institute, 9609 Medical Center Dr,, MSC 9735 Bethesda, MD 20892, USA. rsimon@mail.nih.gov.|Biometric Research Branch, National Cancer Institute, 9609 Medical Center Dr,, MSC 9735 Bethesda, MD 20892, USA. rsimon@mail.nih.gov.|Biometric Research Branch, National Cancer Institute, 9609 Medical Center Dr,, MSC 9735 Bethesda, MD 20892, USA. rsimon@mail.nih.gov.|Biometric Research Branch, National Cancer Institute, 9609 Medical Center Dr,, MSC 9735 Bethesda, MD 20892, USA. rsimon@mail.nih.gov.|Biometric Research Branch, National Cancer Institute, 9609 Medical Center Dr,, MSC 9735 Bethesda, MD 20892, USA. rsimon@mail.nih.gov.|Biometric Research Branch, National Cancer Institute, 9609 Medical Center Dr,, MSC 9735 Bethesda, MD 20892, USA. rsimon@mail.nih.gov.|Biometric Research Branch, National Cancer Institute, 9609 Medical Center Dr,, MSC 9735 Bethesda, MD 20892, USA. rsimon@mail.nih.gov.|Department of Biochemistry and Molecular Medicine, George Washington University Medical Center, Washington, DC 20037, USA. mazumder@gwu.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 10, 'Algorithms|Biomedical Research|Database Management Systems|Databases, Genetic|High-Throughput Nucleotide Sequencing|Humans|Neoplasms|Phylogeny|Polymorphism, Single Nucleotide|Proteome|Proteomics|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-15-28', '24467687', 'Next-generation sequencing (NGS) technologies have resulted in petabytes of scattered data, decentralized in archives, databases and sometimes in isolated hard-disks which are inaccessible for browsing and analysis. It is expected that curated secondary databases will help organize some of this Big Data thereby allowing users better navigate, search and compute on it.'),
(95920, 2014, 'bmc', 'A tool for design of primers for microRNA-specific quantitative RT-qPCR', 'Busk, Peter K', 'Department of Biotechnology, Chemistry and Environmental Engineering, Aalborg University Copenhagen, A,C, Meyers Vænge 15, Copenhagen, SV 2450, Denmark. pkb@bio.aau.dk.', 'Denmark', 102, 'Algorithms|Computational Biology|DNA Primers|MicroRNAs|RNA Probes|Real-Time Polymerase Chain Reaction|Software', 'Journal Article', '10.1186/1471-2105-15-29', '24472427', 'MicroRNAs are small but biologically important RNA molecules. Although different methods can be used for quantification of microRNAs, quantitative PCR is regarded as the reference that is used to validate other methods. Several commercial qPCR assays are available but they often come at a high price and the sequences of the primers are not disclosed. An alternative to commercial assays is to manually design primers but this work is tedious and, hence, not practical for the design of primers for a larger number of targets.'),
(95921, 2014, 'bmc', 'Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline', 'Reid, Jeffrey G|Carroll, Andrew|Veeraraghavan, Narayanan|Dahdouli, Mahmoud|Sundquist, Andreas|English, Adam|Bainbridge, Matthew|White, Simon|Salerno, William|Buhay, Christian|Yu, Fuli|Muzny, Donna|Daly, Richard|Duyk, Geoff|Gibbs, Richard A|Boerwinkle, Eric', 'Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.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|United States|United States', 0, 'Genome|Genomics|High-Throughput Nucleotide Sequencing|Humans|Internet|Software', 'Journal Article', '10.1186/1471-2105-15-30', '24475911', 'Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results.'),
(95922, 2014, 'bmc', 'geneCommittee: a web-based tool for extensively testing the discriminatory power of biologically relevant gene sets in microarray data classification', 'Reboiro-Jato, Miguel|Arrais, Joel P|Oliveira, José Luis|Fdez-Riverola, Florentino', 'Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. jgreid@bcm.edu.|Escuela Superior de Ingeniería Informática, Universidade de Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain. riverola@uvigo.es.', 'United States|United States|United States|Spain', 5, 'Computational Biology|Databases, Genetic|Disease|Gene Expression Profiling|Humans|Internet|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-15-31', '24475928', 'The diagnosis and prognosis of several diseases can be shortened through the use of different large-scale genome experiments. In this context, microarrays can generate expression data for a huge set of genes. However, to obtain solid statistical evidence from the resulting data, it is necessary to train and to validate many classification techniques in order to find the best discriminative method. This is a time-consuming process that normally depends on intricate statistical tools.'),
(95923, 2014, 'bmc', 'Maximizing Kolmogorov Complexity for accurate and robust bright field cell segmentation', 'Mohamadlou, Hamid|Shope, Joseph C|Flann, Nicholas S', 'Escuela Superior de Ingeniería Informática, Universidade de Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain. riverola@uvigo.es.|Escuela Superior de Ingeniería Informática, Universidade de Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain. riverola@uvigo.es.|Department of Computer Science, Utah State University, Logan, UT 84322, USA. Nick.Flann@usu.edu.', 'Spain|Spain|United States', 0, 'Algorithms|Cytological Techniques|HEK293 Cells|Humans|Image Processing, Computer-Assisted|Microscopy|Statistics, Nonparametric', 'Journal Article', '10.1186/1471-2105-15-32', '24475950', 'Analysis of cellular processes with microscopic bright field defocused imaging has the advantage of low phototoxicity and minimal sample preparation. However bright field images lack the contrast and nuclei reporting available with florescent approaches and therefore present a challenge to methods that segment and track the live cells. Moreover, such methods must be robust to systemic and random noise, variability in experimental configuration, and the multiple unknowns in the biological system under study.'),
(95924, 2014, 'bmc', 'QTrim: a novel tool for the quality trimming of sequence reads generated using the Roche/454 sequencing platform', 'Shrestha, Ram Krishna|Lubinsky, Baruch|Bansode, Vijay B|Moinz, Mónica B J|McCormack, Grace P|Travers, Simon A', 'Department of Computer Science, Utah State University, Logan, UT 84322, USA. Nick.Flann@usu.edu.|Department of Computer Science, Utah State University, Logan, UT 84322, USA. Nick.Flann@usu.edu.|Department of Computer Science, Utah State University, Logan, UT 84322, USA. Nick.Flann@usu.edu.|Department of Computer Science, Utah State University, Logan, UT 84322, USA. Nick.Flann@usu.edu.|Department of Computer Science, Utah State University, Logan, UT 84322, USA. Nick.Flann@usu.edu.|South African National Bioinformatics Institute, SA MRC Bioinformatics Unit, University of the Western Cape, Private Bag X17, Bellville 7535, South Africa. simon@sanbi.ac.za.', 'United States|United States|United States|United States|United States|South Africa', 11, 'Algorithms|Computational Biology|High-Throughput Nucleotide Sequencing|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-15-33', '24479419', 'Many high throughput sequencing (HTS) approaches, such as the Roche/454 platform, produce sequences in which the quality of the sequence (as measured by a Phred-like quality scores) decreases linearly across a sequence read. Undertaking quality trimming of this data is essential to enable confidence in the results of subsequent downstream analysis. Here, we have developed a novel, highly sensitive and accurate approach (QTrim) for the quality trimming of sequence reads generated using the Roche/454 sequencing platform (or any platform with long reads that outputs Phred-like quality scores).'),
(95925, 2014, 'bmc', 'Efficient sequential and parallel algorithms for planted motif search', 'Nicolae, Marius|Rajasekaran, Sanguthevar', 'Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA. marius.nicolae@engr.uconn.edu.|Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA. marius.nicolae@engr.uconn.edu.', 'United States|United States', 28, 'Algorithms|Computational Biology|DNA|Proteins|Sequence Analysis, DNA|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-15-34', '24479443', 'Motif searching is an important step in the detection of rare events occurring in a set of DNA or protein sequences. One formulation of the problem is known as (l,d)-motif search or Planted Motif Search (PMS). In PMS we are given two integers l and d and n biological sequences. We want to find all sequences of length l that appear in each of the input sequences with at most d mismatches. The PMS problem is NP-complete. PMS algorithms are typically evaluated on certain instances considered challenging. Despite ample research in the area, a considerable performance gap exists because many state of the art algorithms have large runtimes even for moderately challenging instances.'),
(95926, 2014, 'bmc', 'Inferring clonal evolution of tumors from single nucleotide somatic mutations', 'Jiao, Wei|Vembu, Shankar|Deshwar, Amit G|Stein, Lincoln|Morris, Quaid', 'Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA. marius.nicolae@engr.uconn.edu.|Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA. marius.nicolae@engr.uconn.edu.|Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA. marius.nicolae@engr.uconn.edu.|Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA. marius.nicolae@engr.uconn.edu.|Department of Molecular Genetics, University of Toronto, Toronto, Canada. quaid.morris@utoronto.ca.', 'United States|United States|United States|United States|Canada', 0, 'Algorithms|Bayes Theorem|Clonal Evolution|Computational Biology|Cytological Techniques|Evolution, Molecular|Genotype|Humans|Mutation|Neoplasms|Phylogeny|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1186/1471-2105-15-35', '24484323', 'High-throughput sequencing allows the detection and quantification of frequencies of somatic single nucleotide variants (SNV) in heterogeneous tumor cell populations. In some cases, the evolutionary history and population frequency of the subclonal lineages of tumor cells present in the sample can be reconstructed from these SNV frequency measurements. But automated methods to do this reconstruction are not available and the conditions under which reconstruction is possible have not been described.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(95927, 2014, 'bmc', 'uPEPperoni: an online tool for upstream open reading frame location and analysis of transcript conservation', 'Skarshewski, Adam|Stanton-Cook, Mitchell|Huber, Thomas|Al Mansoori, Sumaya|Smith, Ross|Beatson, Scott A|Rothnagel, Joseph A', 'Department of Molecular Genetics, University of Toronto, Toronto, Canada. quaid.morris@utoronto.ca.|Department of Molecular Genetics, University of Toronto, Toronto, Canada. quaid.morris@utoronto.ca.|Department of Molecular Genetics, University of Toronto, Toronto, Canada. quaid.morris@utoronto.ca.|Department of Molecular Genetics, University of Toronto, Toronto, Canada. quaid.morris@utoronto.ca.|Department of Molecular Genetics, University of Toronto, Toronto, Canada. quaid.morris@utoronto.ca.|Department of Molecular Genetics, University of Toronto, Toronto, Canada. quaid.morris@utoronto.ca.|School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia. j.rothnagel@uq.edu.au.', 'Canada|Canada|Canada|Canada|Canada|Canada|Australia', 13, '5 Untranslated Regions|Amino Acid Sequence|Animals|Cluster Analysis|Codon, Initiator|Computational Biology|Conserved Sequence|Humans|Internet|Mice|Molecular Sequence Data|Open Reading Frames|RNA, Messenger|Rats|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-15-36', '24484385', 'Several small open reading frames located within the 5 untranslated regions of mRNAs have recently been shown to be translated. In humans, about 50% of mRNAs contain at least one upstream open reading frame representing a large resource of coding potential. We propose that some upstream open reading frames encode peptides that are functional and contribute to proteome complexity in humans and other organisms. We use the term uPEPs to describe peptides encoded by upstream open reading frames.'),
(95928, 2014, 'bmc', 'A network-assisted co-clustering algorithm to discover cancer subtypes based on gene expression', 'Liu, Yiyi|Gu, Quanquan|Hou, Jack P|Han, Jiawei|Ma, Jian', 'School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia. j.rothnagel@uq.edu.au.|School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia. j.rothnagel@uq.edu.au.|School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia. j.rothnagel@uq.edu.au.|School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia. j.rothnagel@uq.edu.au.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA. jianma@illinois.edu.', 'Australia|Australia|Australia|Australia|United States', 53, 'Algorithms|Cluster Analysis|Computational Biology|Female|Gene Expression Profiling|Gene Regulatory Networks|Humans|Neoplasms', 'Journal Article', '10.1186/1471-2105-15-37', '24491042', 'Cancer subtype information is critically important for understanding tumor heterogeneity. Existing methods to identify cancer subtypes have primarily focused on utilizing generic clustering algorithms (such as hierarchical clustering) to identify subtypes based on gene expression data. The network-level interaction among genes, which is key to understanding the molecular perturbations in cancer, has been rarely considered during the clustering process. The motivation of our work is to develop a method that effectively incorporates molecular interaction networks into the clustering process to improve cancer subtype identification.'),
(95929, 2014, 'bmc', 'Statistical analysis of differential gene expression relative to a fold change threshold on NanoString data of mouse odorant receptor genes', 'Vaes, Evelien|Khan, Mona|Mombaerts, Peter', 'Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA. jianma@illinois.edu.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA. jianma@illinois.edu.|Max Planck Research Unit for Neurogenetics, Max-von-Laue-Strasse 3, 60438 Frankfurt, Germany. peter.mombaerts@biophys.mpg.de.', 'United States|United States|Germany', 18, 'Animals|Computational Biology|Gene Expression Profiling|Mice|Models, Statistical|Oligonucleotide Array Sequence Analysis|Receptors, Odorant', 'Journal Article', '10.1186/1471-2105-15-39', '24495268', 'A challenge in gene expression studies is the reliable identification of differentially expressed genes. In many high-throughput studies, genes are accepted as differentially expressed only if they satisfy simultaneously a p value criterion and a fold change criterion. A statistical method, TREAT, has been developed for microarray data to assess formally if fold changes are significantly higher than a predefined threshold. We have recently applied the NanoString digital platform to study expression of mouse odorant receptor genes, which form with 1,200 members the largest gene family in the mouse genome. Our objectives are, on these data, to decrease false discoveries when formally assessing the genes relative to a fold change threshold, and to provide a guided selection in the choice of this threshold.'),
(95930, 2014, 'bmc', 'SInC: an accurate and fast error-model based simulator for SNPs, Indels and CNVs coupled with a read generator for short-read sequence data', 'Pattnaik, Swetansu|Gupta, Saurabh|Rao, Arjun A|Panda, Binay', 'Max Planck Research Unit for Neurogenetics, Max-von-Laue-Strasse 3, 60438 Frankfurt, Germany. peter.mombaerts@biophys.mpg.de.|Max Planck Research Unit for Neurogenetics, Max-von-Laue-Strasse 3, 60438 Frankfurt, Germany. peter.mombaerts@biophys.mpg.de.|Max Planck Research Unit for Neurogenetics, Max-von-Laue-Strasse 3, 60438 Frankfurt, Germany. peter.mombaerts@biophys.mpg.de.|Ganit Labs, Bio-IT Centre, Institute of Bioinformatics and Applied Biotechnology, Biotech Park, Electronic City Phase I, Bangalore 560100, India. binay@ganitlabs.in.', 'Germany|Germany|Germany|India', 0, 'Computer Simulation|Databases, Genetic|Genome|Genomics|High-Throughput Nucleotide Sequencing|INDEL Mutation|Polymorphism, Genetic|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-15-40', '24495296', 'The rapid advancements in the field of genome sequencing are aiding our understanding on many biological systems. In the last five years, computational biologists and bioinformatics specialists have come up with newer, better and more efficient tools towards the discovery, analysis and interpretation of different genomic variants from high-throughput sequencing data. Availability of reliable simulated dataset is essential and is the first step towards testing any newly developed analytical tools for variant discovery. Although there are tools currently available that can simulate variants, none present the possibility of simulating all the three major types of variations (Single Nucleotide Polymorphisms, Insertions and Deletions and Copy Number Variations) and can generate reads taking a realistic error-model into consideration. Therefore, an efficient simulator and read generator is needed that can simulate variants taking the error rates of true biological samples into consideration.'),
(95931, 2014, 'bmc', 'DRUMS: Disk Repository with Update Management and Select option for high throughput sequencing data', 'Nettling, Martin|Thieme, Nils|Both, Andreas|Grosse, Ivo', 'Ganit Labs, Bio-IT Centre, Institute of Bioinformatics and Applied Biotechnology, Biotech Park, Electronic City Phase I, Bangalore 560100, India. binay@ganitlabs.in.|Ganit Labs, Bio-IT Centre, Institute of Bioinformatics and Applied Biotechnology, Biotech Park, Electronic City Phase I, Bangalore 560100, India. binay@ganitlabs.in.|R&D, Unister GmbH, Leipzig, Germany. andreas.both@unister.de.|R&D, Unister GmbH, Leipzig, Germany. andreas.both@unister.de.', 'India|India|Germany|Germany', 0, 'Database Management Systems|Databases, Genetic|Endogenous Retroviruses|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Information Storage and Retrieval|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1186/1471-2105-15-38', '24495746', 'New technologies for analyzing biological samples, like next generation sequencing, are producing a growing amount of data together with quality scores. Moreover, software tools (e.g., for mapping sequence reads), calculating transcription factor binding probabilities, estimating epigenetic modification enriched regions or determining single nucleotide polymorphism increase this amount of position-specific DNA-related data even further. Hence, requesting data becomes challenging and expensive and is often implemented using specialised hardware. In addition, picking specific data as fast as possible becomes increasingly important in many fields of science. The general problem of handling big data sets was addressed by developing specialized databases like HBase, HyperTable or Cassandra. However, these database solutions require also specialized or distributed hardware leading to expensive investments. To the best of our knowledge, there is no database capable of (i) storing billions of position-specific DNA-related records, (ii) performing fast and resource saving requests, and (iii) running on a single standard computer hardware.'),
(95932, 2014, 'bmc', 'VAMPS: a website for visualization and analysis of microbial population structures', 'Huse, Susan M|Mark Welch, David B|Voorhis, Andy|Shipunova, Anna|Morrison, Hilary G|Eren, A Murat|Sogin, Mitchell L', 'Department of Pathology and Laboratory Medicine, Brown University, 70 Ship Street, Campus Box G-E5, Providence, RI 02912, USA. susan_huse@brown.edu.|Department of Pathology and Laboratory Medicine, Brown University, 70 Ship Street, Campus Box G-E5, Providence, RI 02912, USA. susan_huse@brown.edu.|Department of Pathology and Laboratory Medicine, Brown University, 70 Ship Street, Campus Box G-E5, Providence, RI 02912, USA. susan_huse@brown.edu.|Department of Pathology and Laboratory Medicine, Brown University, 70 Ship Street, Campus Box G-E5, Providence, RI 02912, USA. susan_huse@brown.edu.|Department of Pathology and Laboratory Medicine, Brown University, 70 Ship Street, Campus Box G-E5, Providence, RI 02912, USA. susan_huse@brown.edu.|Department of Pathology and Laboratory Medicine, Brown University, 70 Ship Street, Campus Box G-E5, Providence, RI 02912, USA. susan_huse@brown.edu.|Department of Pathology and Laboratory Medicine, Brown University, 70 Ship Street, Campus Box G-E5, Providence, RI 02912, USA. susan_huse@brown.edu.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Bacteria|Computational Biology|Computer Graphics|High-Throughput Nucleotide Sequencing|Internet|Microbiota|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-15-41', '24499292', 'The advent of next-generation DNA sequencing platforms has revolutionized molecular microbial ecology by making the detailed analysis of complex communities over time and space a tractable research pursuit for small research groups. However, the ability to generate 10xe2x81xb5-10xe2x81xb8 reads with relative ease brings with it many downstream complications. Beyond the computational resources and skills needed to process and analyze data, it is difficult to compare datasets in an intuitive and interactive manner that leads to hypothesis generation and testing.'),
(95933, 2014, 'bmc', 'Improving read mapping using additional prefix grams', 'Kim, Jongik|Li, Chen|Xie, Xiaohui', 'Department of Pathology and Laboratory Medicine, Brown University, 70 Ship Street, Campus Box G-E5, Providence, RI 02912, USA. susan_huse@brown.edu.|Department of Pathology and Laboratory Medicine, Brown University, 70 Ship Street, Campus Box G-E5, Providence, RI 02912, USA. susan_huse@brown.edu.|Department of Computer Science, University of California, Irvine, USA. xhx@ics.uci.edu.', 'United States|United States|United States', 14, 'Algorithms|Computational Biology|Genome|High-Throughput Nucleotide Sequencing|Internet|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-15-42', '24499321', 'Next-generation sequencing (NGS) enables rapid production of billions of bases at a relatively low cost. Mapping reads from next-generation sequencers to a given reference genome is an important first step in many sequencing applications. Popular read mappers, such as Bowtie and BWA, are optimized to return top one or a few candidate locations of each read. However, identifying all mapping locations of each read, instead of just one or a few, is also important in some sequencing applications such as ChIP-seq for discovering binding sites in repeat regions, and RNA-seq for transcript abundance estimation.'),
(95934, 2014, 'bmc', 'Mining locus tags in PubMed Central to improve microbial gene annotation', 'Stubben, Chris J|Challacombe, Jean F', 'Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA. stubben@lanl.gov.|Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA. stubben@lanl.gov.', 'United States|United States', 0, 'Algorithms|Data Mining|Genes, Bacterial|Molecular Sequence Annotation|PubMed', 'Journal Article', '10.1186/1471-2105-15-43', '24499370', 'The scientific literature contains millions of microbial gene identifiers within the full text and tables, but these annotations rarely get incorporated into public sequence databases. We propose to utilize the Open Access (OA) subset of PubMed Central (PMC) as a gene annotation database and have developed an R package called pmcXML to automatically mine and extract locus tags from full text, tables and supplements.'),
(95935, 2014, 'bmc', 'The HTS barcode checker pipeline, a tool for automated detection of illegally traded species from high-throughput sequencing data', 'Lammers, Youri|Peelen, Tamara|Vos, Rutger A|Gravendeel, Barbara', 'Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA. stubben@lanl.gov.|Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA. stubben@lanl.gov.|Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA. stubben@lanl.gov.|Naturalis Biodiversity Center, Darwinweg 4, 2333 CR Leiden, The Netherlands. Barbara.Gravendeel@naturalis.nl.', 'United States|United States|United States|Netherlands', 0, 'Classification|DNA Barcoding, Taxonomic|Databases, Nucleic Acid|Drugs, Chinese Herbal|Endangered Species|Internationality|Medicine, Chinese Traditional|Software', 'Journal Article', '10.1186/1471-2105-15-44', '24502833', 'Mixtures of internationally traded organic substances can contain parts of species protected by the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). These mixtures often raise the suspicion of border control and customs offices, which can lead to confiscation, for example in the case of Traditional Chinese medicines (TCMs). High-throughput sequencing of DNA barcoding markers obtained from such samples provides insight into species constituents of mixtures, but manual cross-referencing of results against the CITES appendices is labor intensive. Matching DNA barcodes against NCBI GenBank using BLAST may yield misleading results both as false positives, due to incorrectly annotated sequences, and false negatives, due to spurious taxonomic re-assignment. Incongruence between the taxonomies of CITES and NCBI GenBank can result in erroneous estimates of illegal trade.'),
(95936, 2014, 'bmc', 'DFLAT: functional annotation for human development', 'Wick, Heather C|Drabkin, Harold|Ngu, Huy|Sackman, Michael|Fournier, Craig|Haggett, Jessica|Blake, Judith A|Bianchi, Diana W|Slonim, Donna K', 'Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.|Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.|Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.|Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.|Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.|Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.|Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.|Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.|Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Amniotic Fluid|Databases, Genetic|Fetal Development|Fetal Diseases|Genes|Genomics|Human Development|Humans|Infant, Newborn|Molecular Sequence Annotation|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-15-45', '24507166', 'Recent increases in genomic studies of the developing human fetus and neonate have led to a need for widespread characterization of the functional roles of genes at different developmental stages. The Gene Ontology (GO), a valuable and widely-used resource for characterizing gene function, offers perhaps the most suitable functional annotation system for this purpose. However, due in part to the difficulty of studying molecular genetic effects in humans, even the current collection of comprehensive GO annotations for human genes and gene products often lacks adequate developmental context for scientists wishing to study gene function in the human fetus.'),
(95937, 2014, 'bmc', 'Peak picking NMR spectral data using non-negative matrix factorization', 'Tikole, Suhas|Jaravine, Victor|Rogov, Vladimir|Dötsch, Volker|Güntert, Peter', 'Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.|Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.|Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.|Department of Computer Science, Tufts University, 155 College Ave, Medford, MA 02155, USA. hwick@cs.tufts.edu.|Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance, and Frankfurt Institute of Advanced Studies, Goethe University Frankfurt am Main, Max-von-Laue-Str, 9, 60438 Frankfurt am Main, Germany. guentert@em.uni-frankfurt.de.', 'United States|United States|United States|United States|Germany', 0, 'Algorithms|Fourier Analysis|Models, Chemical|Models, Statistical|Nuclear Magnetic Resonance, Biomolecular|Proteins', 'Journal Article', '10.1186/1471-2105-15-46', '24511909', 'Simple peak-picking algorithms, such as those based on lineshape fitting, perform well when peaks are completely resolved in multidimensional NMR spectra, but often produce wrong intensities and frequencies for overlapping peak clusters. For example, NOESY-type spectra have considerable overlaps leading to significant peak-picking intensity errors, which can result in erroneous structural restraints. Precise frequencies are critical for unambiguous resonance assignments.'),
(95938, 2014, 'bmc', 'PSEUDOMARKER 20: efficient computation of likelihoods using NOMAD', 'Gertz, Edward Michael|Hiekkalinna, Tero|Digabel, Sébastien Le|Audet, Charles|Terwilliger, Joseph D|Schäffer, Alejandro A', 'National Center for Biotechnology Information, NIH, DHHS, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov.|National Center for Biotechnology Information, NIH, DHHS, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov.|National Center for Biotechnology Information, NIH, DHHS, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov.|National Center for Biotechnology Information, NIH, DHHS, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov.|National Center for Biotechnology Information, NIH, DHHS, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov.|National Center for Biotechnology Information, NIH, DHHS, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov.', 'United States|United States|United States|United States|United States|United States', 15, 'Computational Biology|Disease|Gene Frequency|Genetic Linkage|Humans|Likelihood Functions|Linkage Disequilibrium|Pedigree|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-15-47', '24533837', 'PSEUDOMARKER is a software package that performs joint linkage and linkage disequilibrium analysis between a marker and a putative disease locus. A key feature of PSEUDOMARKER is that it can combine case-controls and pedigrees of varying structure into a single unified analysis. Thus it maximizes the full likelihood of the data over marker allele frequencies or conditional allele frequencies on disease and recombination fraction.'),
(95939, 2014, 'bmc', 'LDsplit: screening for cis-regulatory motifs stimulating meiotic recombination hotspots by analysis of DNA sequence polymorphisms', 'Yang, Peng|Wu, Min|Guo, Jing|Kwoh, Chee Keong|Przytycka, Teresa M|Zheng, Jie', 'National Center for Biotechnology Information, NIH, DHHS, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov.|National Center for Biotechnology Information, NIH, DHHS, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov.|National Center for Biotechnology Information, NIH, DHHS, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov.|National Center for Biotechnology Information, NIH, DHHS, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov.|National Center for Biotechnology Information, NIH, DHHS, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov.|Bioinformatics Research Centre (BIRC), School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore. zhengjie@ntu.edu.sg.', 'United States|United States|United States|United States|United States|Singapore', 0, 'Alleles|Animals|DNA|Genomic Instability|Genomics|Humans|Linkage Disequilibrium|Meiosis|Mice|Nucleotide Motifs|Polymorphism, Single Nucleotide|Recombination, Genetic|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-15-48', '24533858', 'As a fundamental genomic element, meiotic recombination hotspot plays important roles in life sciences. Thus uncovering its regulatory mechanisms has broad impact on biomedical research. Despite the recent identification of the zinc finger protein PRDM9 and its 13-mer binding motif as major regulators for meiotic recombination hotspots, other regulators remain to be discovered. Existing methods for finding DNA sequence motifs of recombination hotspots often rely on the enrichment of co-localizations between hotspots and short DNA patterns, which ignore the cross-individual variation of recombination rates and sequence polymorphisms in the population. Our objective in this paper is to capture signals encoded in genetic variations for the discovery of recombination-associated DNA motifs.'),
(95940, 2014, 'bmc', 'Gene selection for cancer identification: a decision tree model empowered by particle swarm optimization algorithm', 'Chen, Kun-Huang|Wang, Kung-Jeng|Tsai, Min-Lung|Wang, Kung-Min|Adrian, Angelia Melani|Cheng, Wei-Chung|Yang, Tzu-Sen|Teng, Nai-Chia|Tan, Kuo-Pin|Chang, Ku-Shang', 'Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.', '-|-|-|-|-|-|-|-|-|-', 0, 'Algorithms|Artificial Intelligence|Bayes Theorem|Computational Biology|Databases, Factual|Decision Trees|Female|Gene Expression Profiling|Humans|Male|Neoplasms|Reproducibility of Results|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-15-49', '24555567', 'In the application of microarray data, how to select a small number of informative genes from thousands of genes that may contribute to the occurrence of cancers is an important issue. Many researchers use various computational intelligence methods to analyzed gene expression data.'),
(95941, 2014, 'bmc', 'Evaluation of copy number variation detection for a SNP array platform', 'Zhang, Xin|Du, Renqian|Li, Shilin|Zhang, Feng|Jin, Li|Wang, Hongyan', 'Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan, R,O,C. khchen@mail.ntust.edu.tw.|State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, 220 Handan Road, Shanghai 200433, China. wanghy@fudan.edu.cn.', '-|-|-|-|-|China', 21, 'Algorithms|Comparative Genomic Hybridization|Computational Biology|DNA Copy Number Variations|Genome, Human|Humans|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Reproducibility of Results|Sensitivity and Specificity|Software', 'Journal Article', '10.1186/1471-2105-15-50', '24555668', 'Copy Number Variations (CNVs) are usually inferred from Single Nucleotide Polymorphism (SNP) arrays by use of some software packages based on given algorithms. However, there is no clear understanding of the performance of these software packages, it is therefore difficult to select one or several software packages for CNV detection based on the SNP array platform.We selected four publicly available software packages designed for CNV calling from an Affymetrix SNP array, including Birdsuite, dChip, Genotyping Console (GTC) and PennCNV. The publicly available dataset generated by Array-based Comparative Genomic Hybridization (CGH), with a resolution of 24 million probes per sample, was considered to be the gold standard. Compared with the CGH-based dataset, the success rate, average stability rate, sensitivity, consistence and reproducibility of these four software packages were assessed compared with the gold standard. Specially, we also compared the efficiency of detecting CNVs simultaneously by two, three and all of the software packages with that by a single software package.'),
(95942, 2014, 'bmc', 'Statistical hypothesis testing of factor loading in principal component analysis and its application to metabolite set enrichment analysis', 'Yamamoto, Hiroyuki|Fujimori, Tamaki|Sato, Hajime|Ishikawa, Gen|Kami, Kenjiro|Ohashi, Yoshiaki', 'Human Metabolome Technologies, Inc, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan. h.yama2396@gmail.com.|Human Metabolome Technologies, Inc, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan. h.yama2396@gmail.com.|Human Metabolome Technologies, Inc, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan. h.yama2396@gmail.com.|Human Metabolome Technologies, Inc, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan. h.yama2396@gmail.com.|Human Metabolome Technologies, Inc, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan. h.yama2396@gmail.com.|Human Metabolome Technologies, Inc, 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan. h.yama2396@gmail.com.', 'Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Animals|Liver|Metabolic Networks and Pathways|Metabolome|Metabolomics|Mice|Mice, Transgenic|Principal Component Analysis', 'Journal Article', '10.1186/1471-2105-15-51', '24555693', 'Principal component analysis (PCA) has been widely used to visualize high-dimensional metabolomic data in a two- or three-dimensional subspace. In metabolomics, some metabolites (e.g., the top 10 metabolites) have been subjectively selected when using factor loading in PCA, and biological inferences are made for these metabolites. However, this approach may lead to biased biological inferences because these metabolites are not objectively selected with statistical criteria.'),
(95943, 2014, 'bmc', 'Comparison of genotype clustering tools with rare variants', 'Perreault, Louis-Philippe Lemieux|Legault, Marc-André|Barhdadi, Amina|Provost, Sylvie|Normand, Valérie|Tardif, Jean-Claude|Dubé, Marie-Pierre', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 4, 'Cluster Analysis|Gene Frequency|Genome|Genomics|Genotype|Humans|Reproducibility of Results|Sequence Analysis, DNA', 'Comparative Study', '10.1186/1471-2105-15-52', '24559245', 'Along with the improvement of high throughput sequencing technologies, the genetics community is showing marked interest for the rare variants/common diseases hypothesis. While sequencing can still be prohibitive for large studies, commercially available genotyping arrays targeting rare variants prove to be a reasonable alternative. A technical challenge of array based methods is the task of deriving genotype classes (homozygous or heterozygous) by clustering intensity data points. The performance of clustering tools for common polymorphisms is well established, while their performance when conducted with a large proportion of rare variants (where data points are sparse for genotypes containing the rare allele) is less known. We have compared the performance of four clustering tools (GenCall, GenoSNP, optiCall and zCall) for the genotyping of over 10,000 samples using the Illuminas HumanExome BeadChip, which includes 247,870 variants, 90% of which have a minor allele frequency below 5% in a population of European ancestry. Different reference parameters for GenCall and different initial parameters for GenoSNP were tested. Genotyping accuracy was assessed using data from the 1000 Genomes Project as a gold standard, and agreement between tools was measured.'),
(95944, 2013, 'bmc', 'Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives', 'Zhao, Min|Wang, Qingguo|Wang, Quan|Jia, Peilin|Zhao, Zhongming', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada', 230, 'DNA Copy Number Variations|Exons|Genome|Genomics|Genotype|High-Throughput Nucleotide Sequencing|Humans', 'Journal Article', '10.1186/1471-2105-14-S11-S1', '24564169', 'Copy number variation (CNV) is a prevalent form of critical genetic variation that leads to an abnormal number of copies of large genomic regions in a cell. Microarray-based comparative genome hybridization (arrayCGH) or genotyping arrays have been standard technologies to detect large regions subject to copy number changes in genomes until most recently high-resolution sequence data can be analyzed by next-generation sequencing (NGS). During the last several years, NGS-based analysis has been widely applied to identify CNVs in both healthy and diseased individuals. Correspondingly, the strong demand for NGS-based CNV analyses has fuelled development of numerous computational methods and tools for CNV detection. In this article, we review the recent advances in computational methods pertaining to CNV detection using whole genome and whole exome sequencing data. Additionally, we discuss their strengths and weaknesses and suggest directions for future development. '),
(95945, 2013, 'bmc', 'A gene signature based method for identifying subtypes and subtype-specific drivers in cancer with an application to medulloblastoma', 'Chen, Peikai|Fan, Yubo|Man, Tsz-kwong|Hung, Y S|Lau, Ching C|Wong, Stephen T C', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Brain Neoplasms|Child|Cluster Analysis|Gene Dosage|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Medulloblastoma|Survival Rate', 'Journal Article', '10.1186/1471-2105-14-S18-S1', '24564171', 'Subtypes are widely found in cancer. They are characterized with different behaviors in clinical and molecular profiles, such as survival rates, gene signature and copy number aberrations (CNAs). While cancer is generally believed to have been caused by genetic aberrations, the number of such events is tremendous in the cancer tissue and only a small subset of them may be tumorigenic. On the other hand, gene expression signature of a subtype represents residuals of the subtype-specific cancer mechanisms. Using high-throughput data to link these factors to define subtype boundaries and identify subtype-specific drivers, is a promising yet largely unexplored topic.'),
(95946, 2013, 'bmc', 'On the inversion-indel distance', 'Willing, Eyla|Zaccaria, Simone|Braga, Marília D V|Stoye, Jens', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada', 4, 'Algorithms|Chromosome Inversion|Genome|INDEL Mutation|Models, Genetic', 'Journal Article', '10.1186/1471-2105-14-S15-S3', '24564182', 'The inversion distance, that is the distance between two unichromosomal genomes with the same content allowing only inversions of DNA segments, can be computed thanks to a pioneering approach of Hannenhalli and Pevzner in 1995. In 2000, El-Mabrouk extended the inversion model to allow the comparison of unichromosomal genomes with unequal contents, thus insertions and deletions of DNA segments besides inversions. However, an exact algorithm was presented only for the case in which we have insertions alone and no deletion (or vice versa), while a heuristic was provided for the symmetric case, that allows both insertions and deletions and is called the inversion-indel distance. In 2005, Yancopoulos, Attie and Friedberg started a new branch of research by introducing the generic double cut and join (DCJ) operation, that can represent several genome rearrangements (including inversions). Among others, the DCJ model gave rise to two important results. First, it has been shown that the inversion distance can be computed in a simpler way with the help of the DCJ operation. Second, the DCJ operation originated the DCJ-indel distance, that allows the comparison of genomes with unequal contents, considering DCJ, insertions and deletions, and can be computed in linear time.'),
(95947, 2014, 'bmc', 'Guidelines for managing data and processes in bone and cartilage tissue engineering', 'Viti, Federica|Scaglione, Silvia|Orro, Alessandro|Milanesi, Luciano', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada', 0, 'Animals|Biocompatible Materials|Bone and Bones|Cartilage|Cell Differentiation|Guidelines as Topic|Humans|Tissue Engineering', 'Journal Article', '10.1186/1471-2105-15-S1-S14', '24564199', 'In the last decades, a wide number of researchers/clinicians involved in tissue engineering field published several works about the possibility to induce a tissue regeneration guided by the use of biomaterials. To this aim, different scaffolds have been proposed, and their effectiveness tested through in vitro and/or in vivo experiments. In this context, integration and meta-analysis approaches are gaining importance for analyses and reuse of data as, for example, those concerning the bone and cartilage biomarkers, the biomolecular factors intervening in cell differentiation and growth, the morphology and the biomechanical performance of a neo-formed tissue, and, in general, the scaffolds ability to promote tissue regeneration. Therefore standards and ontologies are becoming crucial, to provide a unifying knowledge framework for annotating data and supporting the semantic integration and the unambiguous interpretation of novel experimental results.'),
(95948, 2013, 'bmc', 'Fast discovery and visualization of conserved regions in DNA sequences using quasi-alignment', 'Nagar, Anurag|Hahsler, Michael', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada', 2, 'Algorithms|Base Sequence|Cluster Analysis|Conserved Sequence|DNA|Genome|High-Throughput Nucleotide Sequencing|RNA, Ribosomal, 16S|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-14-S11-S2', '24564200', 'Next Generation Sequencing techniques are producing enormous amounts of biological sequence data and analysis becomes a major computational problem. Currently, most analysis, especially the identification of conserved regions, relies heavily on Multiple Sequence Alignment and its various heuristics such as progressive alignment, whose run time grows with the square of the number and the length of the aligned sequences and requires significant computational resources. In this work, we present a method to efficiently discover regions of high similarity across multiple sequences without performing expensive sequence alignment. The method is based on approximating edit distance between segments of sequences using p-mer frequency counts. Then, efficient high-throughput data stream clustering is used to group highly similar segments into so called quasi-alignments. Quasi-alignments have numerous applications such as identifying species and their taxonomic class from sequences, comparing sequences for similarities, and, as in this paper, discovering conserved regions across related sequences.'),
(95949, 2013, 'bmc', 'Rigidity analysis of protein biological assemblies and periodic crystal structures', 'Jagodzinski, Filip|Clark, Pamela|Grant, Jessica|Liu, Tiffany|Monastra, Samantha|Streinu, Ileana', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Crystallography, X-Ray|Databases, Protein|HIV-1|Models, Molecular|Protein Structure, Quaternary|Protein Structure, Tertiary|Proteins|Software', 'Journal Article', '10.1186/1471-2105-14-S18-S2', '24564201', 'We initiate in silico rigidity-theoretical studies of biological assemblies and small crystals for protein structures. The goal is to determine if, and how, the interactions among neighboring cells and subchains affect the flexibility of a molecule in its crystallized state. We use experimental X-ray crystallography data from the Protein Data Bank (PDB). The analysis relies on an effcient graph-based algorithm. Computational experiments were performed using new protein rigidity analysis tools available in the new release of our KINARI-Web server http://kinari.cs.umass.edu.'),
(95950, 2013, 'bmc', 'Lateral gene transfer, rearrangement, reconciliation', 'Patterson, Murray|Szxc3xb6llxc5x91si, Gergely|Daubin, Vincent|Tannier, Eric', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Cyanobacteria|Evolution, Molecular|Gene Duplication|Gene Transfer, Horizontal|Genome|Software', 'Journal Article', '10.1186/1471-2105-14-S15-S4', '24564205', 'Models of ancestral gene order reconstruction have progressively integrated different evolutionary patterns and processes such as unequal gene content, gene duplications, and implicitly sequence evolution via reconciled gene trees. These models have so far ignored lateral gene transfer, even though in unicellular organisms it can have an important confounding effect, and can be a rich source of information on the function of genes through the detection of transfers of clusters of genes.'),
(95951, 2013, 'bmc', 'Towards accurate modeling of noncovalent interactions for protein rigidity analysis', 'Fox, Naomi|Streinu, Ileana', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada', 5, 'Algorithms|Cluster Analysis|Crystallography, X-Ray|HIV-1|Hydrogen Bonding|Hydrophobic and Hydrophilic Interactions|Models, Molecular|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Software', 'Journal Article', '10.1186/1471-2105-14-S18-S3', '24564209', 'Protein rigidity analysis is an efficient computational method for extracting flexibility information from static, X-ray crystallography protein data. Atoms and bonds are modeled as a mechanical structure and analyzed with a fast graph-based algorithm, producing a decomposition of the flexible molecule into interconnected rigid clusters. The result depends critically on noncovalent atomic interactions, primarily on how hydrogen bonds and hydrophobic interactions are computed and modeled. Ongoing research points to the stringent need for benchmarking rigidity analysis software systems, towards the goal of increasing their accuracy and validating their results, either against each other and against biologically relevant (functional) parameters. We propose two new methods for modeling hydrogen bonds and hydrophobic interactions that more accurately reflect a mechanical model, without being computationally more intensive. We evaluate them using a novel scoring method, based on the B-cubed score from the information retrieval literature, which measures how well two cluster decompositions match.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(95952, 2014, 'bmc', 'Development and tuning of an original search engine for patent libraries in medicinal chemistry', 'Pasche, Emilie|Gobeill, Julien|Kreim, Olivier|Oezdemir-Zaech, Fatma|Vachon, Therese|Lovis, Christian|Ruch, Patrick', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 5, 'Algorithms|Chemistry, Pharmaceutical|Information Storage and Retrieval|Internet|Patents as Topic|Search Engine|Small Molecule Libraries', 'Journal Article', '10.1186/1471-2105-15-S1-S15', '24564220', 'The large increase in the size of patent collections has led to the need of efficient search strategies. But the development of advanced text-mining applications dedicated to patents of the biomedical field remains rare, in particular to address the needs of the pharmaceutical & biotech industry, which intensively uses patent libraries for competitive intelligence and drug development.'),
(95953, 2013, 'bmc', 'Gene tree correction guided by orthology', 'Lafond, Manuel|Semeria, Magali|Swenson, Krister M|Tannier, Eric|El-Mabrouk, Nadia', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Animals|Evolution, Molecular|Humans|Phylogeny|Sequence Alignment|Software|Synteny', 'Journal Article', '10.1186/1471-2105-14-S15-S5', '24564227', 'Reconciled gene trees yield orthology and paralogy relationships between genes. This information may however contradict other information on orthology and paralogy provided by other footprints of evolution, such as conserved synteny.'),
(95954, 2013, 'bmc', 'Efficient digest of high-throughput sequencing data in a reproducible report', 'Zhang, Zhe|Leipzig, Jeremy|Sasson, Ariella|Yu, Angela M|Perin, Juan C|Xie, Hongbo M|Sarmady, Mahdi|Warren, Patrick V|White, Peter S', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Base Sequence|Chromosomes|Exons|Genome|High-Throughput Nucleotide Sequencing|Reproducibility of Results|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-14-S11-S3', '24564231', 'High-throughput sequencing (HTS) technologies are spearheading the accelerated development of biomedical research. Processing and summarizing the large amount of data generated by HTS presents a non-trivial challenge to bioinformatics. A commonly adopted standard is to store sequencing reads aligned to a reference genome in SAM (Sequence Alignment/Map) or BAM (Binary Alignment/Map) files. Quality control of SAM/BAM files is a critical checkpoint before downstream analysis. The goal of the current project is to facilitate and standardize this process.'),
(95955, 2013, 'bmc', 'Signal extraction from movies of honeybee brain activity: the ImageBee plugin for KNIME', 'Strauch, Martin|Rein, Julia|Lutz, Christian|Galizia, C Giovanni', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada', 7, 'Algorithms|Animals|Bees|Brain|Calcium|Cluster Analysis|Software', 'Journal Article', '10.1186/1471-2105-14-S18-S4', '24564238', 'In the antennal lobe, a dedicated olfactory center of the honeybee brain, odours are encoded as activity patterns of coding units, the so-called glomeruli. Optical imaging with calcium-sensitive dyes allows us to record these activity patterns and to gain insight into olfactory information processing in the brain.'),
(95956, 2014, 'bmc', 'Integrated Bio-Search: challenges and trends for the integration, search and comprehensive processing of biological information', 'Masseroli, Marco|Mons, Barend|Bongcam-Rudloff, Erik|Ceri, Stefano|Kel, Alexander|Rechenmann, François|Lisacek, Frederique|Romano, Paolo', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 10, 'Algorithms|Animals|Computational Biology|Cooperative Behavior|Genome|Genomics|Humans|Software', 'Journal Article', '10.1186/1471-2105-15-S1-S2', '24564249', 'Many efforts exist to design and implement approaches and tools for data capture, integration and analysis in the life sciences. Challenges are not only the heterogeneity, size and distribution of information sources, but also the danger of producing too many solutions for the same problem. Methodological, technological, infrastructural and social aspects appear to be essential for the development of a new generation of best practices and tools. In this paper, we analyse and discuss these aspects from different perspectives, by extending some of the ideas that arose during the NETTAB 2012 Workshop, making reference especially to the European context. First, relevance of using data and software models for the management and analysis of biological data is stressed. Second, some of the most relevant community achievements of the recent years, which should be taken as a starting point for future efforts in this research domain, are presented. Third, some of the main outstanding issues, challenges and trends are analysed. The challenges related to the tendency to fund and create large scale international research infrastructures and public-private partnerships in order to address the complex challenges of data intensive science are especially discussed. The needs and opportunities of Genomic Computing (the integration, search and display of genomic information at a very specific level, e.g. at the level of a single DNA region) are then considered. In the current data and network-driven era, social aspects can become crucial bottlenecks. How these may best be tackled to unleash the technical abilities for effective data integration and validation efforts is then discussed. Especially the apparent lack of incentives for already overwhelmed researchers appears to be a limitation for sharing information and knowledge with other scientists. We point out as well how the bioinformatics market is growing at an unprecedented speed due to the impact that new powerful in silico analysis promises to have on better diagnosis, prognosis, drug discovery and treatment, towards personalized medicine. An open business model for bioinformatics, which appears to be able to reduce undue duplication of efforts and support the increased reuse of valuable data sets, tools and platforms, is finally discussed.'),
(95957, 2013, 'bmc', 'libgapmis: extending short-read alignments', 'Alachiotis, Nikolaos|Berger, Simon|Flouri, Tomáš|Pissis, Solon P|Stamatakis, Alexandros', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada', 7, 'Algorithms|Base Sequence|Exons|Genome|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-14-S11-S4', '24564250', 'A wide variety of short-read alignment programmes have been published recently to tackle the problem of mapping millions of short reads to a reference genome, focusing on different aspects of the procedure such as time and memory efficiency, sensitivity, and accuracy. These tools allow for a small number of mismatches in the alignment, however, their ability to allow for gaps varies greatly, with many performing poorly or not allowing them at all. The seed-and-extend strategy is applied in most short-read alignment programmes. After aligning a substring of the reference sequence against the high-quality prefix of a short read--the seed--an important problem is to find the best possible alignment between a substring of the reference sequence succeeding and the remaining suffix of low quality of the read--extend. The fact that the reads are rather short and that the gap occurrence frequency observed in various studies is rather low suggest that aligning (parts of) those reads with a single gap is in fact desirable.'),
(95958, 2013, 'bmc', 'Fast algorithms and heuristics for phylogenomics under ILS and hybridization', 'Yu, Yun|Ristic, Nikola|Nakhleh, Luay', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada', 0, 'Algorithms|Biological Evolution|Feasibility Studies|Genome|Genomics|Hybridization, Genetic|Phylogeny|Probability', 'Journal Article', '10.1186/1471-2105-14-S15-S6', '24564257', 'Phylogenomic analyses involving whole-genome or multi-locus data often entail dealing with incongruent gene trees. In this paper, we consider two causes of such incongruence, namely, incomplete lineage sorting (ILS) and hybridization, and consider both parsimony and probabilistic criteria for dealing with them.'),
(95959, 2013, 'bmc', 'Gene regulatory networks inference using a multi-GPU exhaustive search algorithm', 'Borelli, Fabrizio F|de Camargo, Raphael Y|Martins, David C|Rozante, Luiz C S', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada', 20, 'Algorithms|Computational Biology|Gene Regulatory Networks', 'Journal Article', '10.1186/1471-2105-14-S18-S5', '24564268', 'Gene regulatory networks (GRN) inference is an important bioinformatics problem in which the gene interactions need to be deduced from gene expression data, such as microarray data. Feature selection methods can be applied to this problem. A feature selection technique is composed by two parts: a search algorithm and a criterion function. Among the search algorithms already proposed, there is the exhaustive search where the best feature subset is returned, although its computational complexity is unfeasible in almost all situations. The objective of this work is the development of a low cost parallel solution based on GPU architectures for exhaustive search with a viable cost-benefit. We use CUDA™, a general purpose parallel programming platform that allows the usage of NVIDIA® GPUs to solve complex problems in an efficient way.'),
(95960, 2013, 'bmc', 'Phase change for the accuracy of the median value in estimating divergence time', 'Jamshidpey, Arash|Sankoff, David', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada', 0, 'Evolution, Molecular|Gene Order|Genome|Models, Genetic|Phylogeny|Time Factors', 'Journal Article', '10.1186/1471-2105-14-S15-S7', '24564272', 'We prove that for general models of random gene-order evolution of k xe2x89xa5 3 genomes, as the number of genes n goes to xe2x88x9e, the median value approximates k times the divergence time if the number of rearrangements is less than cn/4 for any c <1. For some c* xe2x89xa5 1, if the number of rearrangements is greater than c*n/4, this approximation does not hold. '),
(95961, 2013, 'bmc', 'A base composition analysis of natural patterns for the preprocessing of metagenome sequences', 'Bonham-Carter, Oliver|Ali, Hesham|Bastola, Dhundy', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada', 0, 'Algorithms|Base Composition|Base Sequence|Cluster Analysis|DNA, Bacterial|Genome, Bacterial|Metagenome|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-14-S11-S5', '24564274', 'On the pretext that sequence reads and contigs often exhibit the same kinds of base usage that is also observed in the sequences from which they are derived, we offer a base composition analysis tool. Our tool uses these natural patterns to determine relatedness across sequence data. We introduce spectrum sets (sets of motifs) which are permutations of bacterial restriction sites and the base composition analysis framework to measure their proportional content in sequence data. We suggest that this framework will increase the efficiency during the pre-processing stages of metagenome sequencing and assembly projects.'),
(95962, 2014, 'bmc', 'Explorative search of distributed bio-data to answer complex biomedical questions', 'Masseroli, Marco|Picozzi, Matteo|Ghisalberti, Giorgio|Ceri, Stefano', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Biomedical Technology|Computational Biology|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-15-S1-S3', '24564278', 'The huge amount of biomedical-molecular data increasingly produced is providing scientists with potentially valuable information. Yet, such data quantity makes difficult to find and extract those data that are most reliable and most related to the biomedical questions to be answered, which are increasingly complex and often involve many different biomedical-molecular aspects. Such questions can be addressed only by comprehensively searching and exploring different types of data, which frequently are ordered and provided by different data sources. Search Computing has been proposed for the management and integration of ranked results from heterogeneous search services. Here, we present its novel application to the explorative search of distributed biomedical-molecular data and the integration of the search results to answer complex biomedical questions.'),
(95963, 2013, 'bmc', 'MaTSE: the gene expression time-series explorer', 'Craig, Paul|Cannon, Alan|Kukla, Robert|Kennedy, Jessie', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada', 5, 'Computational Biology|Computer Graphics|Gene Expression|Humans|Information Dissemination|Pattern Recognition, Automated|Software|Time Factors', 'Journal Article', '10.1186/1471-2105-14-S19-S1', '24564291', 'High throughput gene expression time-course experiments provide a perspective on biological functioning recognized as having huge value for the diagnosis, treatment, and prevention of diseases. There are however significant challenges to properly exploiting this data due to its massive scale and complexity. In particular, existing techniques are found to be ill suited to finding patterns of changing activity over a limited interval of an experiments time frame. The Time-Series Explorer (TSE) was developed to overcome this limitation by allowing users to explore their data by controlling an animated scatter-plot view. MaTSE improves and extends TSE by allowing users to visualize data with missing values, cross reference multiple conditions, highlight gene groupings, and collaborate by sharing their findings.'),
(95964, 2013, 'bmc', 'Provenance in bioinformatics workflows', 'de Paula, Renato|Holanda, Maristela|Gomes, Luciana S A|Lifschitz, Sergio|Walter, Maria Emilia M T', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada', 0, 'Bacillus cereus|Computational Biology|Genome|Software|Workflow', 'Journal Article', '10.1186/1471-2105-14-S11-S6', '24564294', 'In this work, we used the PROV-DM model to manage data provenance in workflows of genome projects. This provenance model allows the storage of details of one workflow execution, e.g., raw and produced data and computational tools, their versions and parameters. Using this model, biologists can access details of one particular execution of a workflow, compare results produced by different executions, and plan new experiments more efficiently. In addition to this, a provenance simulator was created, which facilitates the inclusion of provenance data of one genome project workflow execution. Finally, we discuss one case study, which aims to identify genes involved in specific metabolic pathways of Bacillus cereus, as well as to compare this isolate with other phylogenetic related bacteria from the Bacillus group. B. cereus is an extremophilic bacteria, collected in warm water in the Midwestern Region of Brazil, its DNA samples having been sequenced with an NGS machine. '),
(95965, 2014, 'bmc', 'Integrating microRNA target predictions for the discovery of gene regulatory networks: a semi-supervised ensemble learning approach', 'Pio, Gianvito|Malerba, Donato|DElia, Domenica|Ceci, Michelangelo', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada', 39, 'Algorithms|Gene Expression Regulation|Gene Regulatory Networks|Humans|MicroRNAs|Multigene Family|RNA, Messenger|Reproducibility of Results', 'Journal Article', '10.1186/1471-2105-15-S1-S4', '24564296', 'MicroRNAs (miRNAs) are small non-coding RNAs which play a key role in the post-transcriptional regulation of many genes. Elucidating miRNA-regulated gene networks is crucial for the understanding of mechanisms and functions of miRNAs in many biological processes, such as cell proliferation, development, differentiation and cell homeostasis, as well as in many types of human tumors. To this aim, we have recently presented the biclustering method HOCCLUS2, for the discovery of miRNA regulatory networks. Experiments on predicted interactions revealed that the statistical and biological consistency of the obtained networks is negatively affected by the poor reliability of the output of miRNA target prediction algorithms. Recently, some learning approaches have been proposed to learn to combine the outputs of distinct prediction algorithms and improve their accuracy. However, the application of classical supervised learning algorithms presents two challenges: i) the presence of only positive examples in datasets of experimentally verified interactions and ii) unbalanced number of labeled and unlabeled examples.'),
(95966, 2013, 'bmc', 'Practical aliquoting of flowering plant genomes', 'Zheng, Chunfang|Sankoff, David', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada', 7, 'Algorithms|Cluster Analysis|Genome, Plant|Lycopersicon esculentum|Polyploidy|Vitis', 'Journal Article', '10.1186/1471-2105-14-S15-S8', '24564303', 'We pose the problem of dissecting an ancient polyploid genome into its constituent subgenomes despite fragmentation and noise caused by genome rearrangements and fractionation of multi-copy genes. We formulate this in terms of decomposition into defective k-partite graphs, distinguished by location within the genome. We devise and implement a clustering heuristic for solving realistic instances of the problem. An unusual focus of our method is the focus on prioritizing gene density or lack of gaps in the assembly of fragments into larger regions, rather than maximizing the number of genes. We validate the method against the grape genome in which the ancient core eudicot triplication is readily detectible and is already well known. We then analyze the tomato genome, whose proposed status as a descendant of a more recent Solanum hexaploid is controversial, and confirm this proposal. The solution reveals unexpected information about the evolution of the tomato. '),
(95967, 2013, 'bmc', 'An efficient and scalable graph modeling approach for capturing information at different levels in next generation sequencing reads', 'Warnke, Julia D|Ali, Hesham H', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada', 0, 'Algorithms|Cluster Analysis|Genome, Bacterial|High-Throughput Nucleotide Sequencing|Metagenomics|Models, Theoretical|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-14-S11-S7', '24564333', 'Next generation sequencing technologies have greatly advanced many research areas of the biomedical sciences through their capability to generate massive amounts of genetic information at unprecedented rates. The advent of next generation sequencing has led to the development of numerous computational tools to analyze and assemble the millions to billions of short sequencing reads produced by these technologies. While these tools filled an important gap, current approaches for storing, processing, and analyzing short read datasets generally have remained simple and lack the complexity needed to efficiently model the produced reads and assemble them correctly.'),
(95968, 2013, 'bmc', 'iVUN: interactive Visualization of Uncertain biochemical reaction Networks', 'Vehlow, Corinna|Hasenauer, Jan|Kramer, Andrei|Raue, Andreas|Hug, Sabine|Timmer, Jens|Radde, Nicole|Theis, Fabian J|Weiskopf, Daniel', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Computational Biology|Computer Graphics|Metabolic Networks and Pathways|Models, Biological|Models, Chemical|Signal Transduction|Uncertainty', 'Journal Article', '10.1186/1471-2105-14-S19-S2', '24564335', 'Mathematical models are nowadays widely used to describe biochemical reaction networks. One of the main reasons for this is that models facilitate the integration of a multitude of different data and data types using parameter estimation. Thereby, models allow for a holistic understanding of biological processes. However, due to measurement noise and the limited amount of data, uncertainties in the model parameters should be considered when conclusions are drawn from estimated model attributes, such as reaction fluxes or transient dynamics of biological species.'),
(95969, 2014, 'bmc', 'ProphNet: a generic prioritization method through propagation of information', 'Martínez, Víctor|Cano, Carlos|Blanco, Armando', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada', 0, 'Algorithms|Breast Neoplasms|Computational Biology|Diabetes Mellitus|Genes|Genetic Predisposition to Disease|Humans|Software Design', 'Journal Article', '10.1186/1471-2105-15-S1-S5', '24564336', 'Prioritization methods have become an useful tool for mining large amounts of data to suggest promising hypotheses in early research stages. Particularly, network-based prioritization tools use a network representation for the interactions between different biological entities to identify novel indirect relationships. However, current network-based prioritization tools are strongly tailored to specific domains of interest (e.g. gene-disease prioritization) and they do not allow to consider networks with more than two types of entities (e.g. genes and diseases). Therefore, the direct application of these methods to accomplish new prioritization tasks is limited.'),
(95970, 2013, 'bmc', 'Sorting genomes with rearrangements and segmental duplications through trajectory graphs', 'Shao, Mingfu|Lin, Yu|Moret, Bernard', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada', 0, 'Algorithms|Evolution, Molecular|Genome|Models, Genetic|Segmental Duplications, Genomic', 'Journal Article', '10.1186/1471-2105-14-S15-S9', '24564345', 'We study the problem of sorting genomes under an evolutionary model that includes genomic rearrangements and segmental duplications. We propose an iterative algorithm to improve any initial evolutionary trajectory between two genomes in terms of parsimony. Our algorithm is based on a new graphical model, the trajectory graph, which models not only the final states of two genomes but also an existing evolutionary trajectory between them. We show that redundant rearrangements in the trajectory correspond to certain cycles in the trajectory graph, and prove that our algorithm converges to an optimal trajectory for any initial trajectory involving only rearrangements. '),
(95971, 2013, 'bmc', 'Assessing the impact of human genome annotation choice on RNA-seq expression estimates', 'Wu, Po-Yen|Phan, John H|Wang, May D', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada', 26, 'Exons|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Protein Isoforms|RNA|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-14-S11-S8', '24564364', 'Genome annotation is a crucial component of RNA-seq data analysis. Much effort has been devoted to producing an accurate and rational annotation of the human genome. An annotated genome provides a comprehensive catalogue of genomic functional elements. Currently, at least six human genome annotations are publicly available, including AceView Genes, Ensembl Genes, H-InvDB Genes, RefSeq Genes, UCSC Known Genes, and Vega Genes. Characteristics of these annotations differ because of variations in annotation strategies and information sources. When performing RNA-seq data analysis, researchers need to choose a genome annotation. However, the effect of genome annotation choice on downstream RNA-seq expression estimates is still unclear. This study (1) investigates the effect of different genome annotations on RNA-seq quantification and (2) provides guidelines for choosing a genome annotation based on research focus.'),
(95972, 2014, 'bmc', 'CorrelaGenes: a new tool for the interpretation of the human transcriptome', 'Cremaschi, Paolo|Rovida, Sergio|Sacchi, Lucia|Lisa, Antonella|Calvi, Francesca|Montecucco, Alessandra|Biamonti, Giuseppe|Bione, Silvia|Sacchi, Gianni', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Data Mining|Down-Regulation|Gene Expression Profiling|Humans|Internet|Transcriptome|Up-Regulation', 'Journal Article', '10.1186/1471-2105-15-S1-S6', '24564370', 'The amount of gene expression data available in public repositories has grown exponentially in the last years, now requiring new data mining tools to transform them in information easily accessible to biologists.'),
(95973, 2013, 'bmc', 'enRoute: dynamic path extraction from biological pathway maps for exploring heterogeneous experimental datasets', 'Partl, Christian|Lex, Alexander|Streit, Marc|Kalkofen, Denis|Kashofer, Karl|Schmalstieg, Dieter', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada|Canada', 16, 'Computational Biology|Computer Graphics|Databases, Genetic|Genomics|Humans|Metabolic Networks and Pathways|Neoplasms', 'Journal Article', '10.1186/1471-2105-14-S19-S3', '24564375', 'Jointly analyzing biological pathway maps and experimental data is critical for understanding how biological processes work in different conditions and why different samples exhibit certain characteristics. This joint analysis, however, poses a significant challenge for visualization. Current techniques are either well suited to visualize large amounts of pathway node attributes, or to represent the topology of the pathway well, but do not accomplish both at the same time. To address this we introduce enRoute, a technique that enables analysts to specify a path of interest in a pathway, extract this path into a separate, linked view, and show detailed experimental data associated with the nodes of this extracted path right next to it. This juxtaposition of the extracted path and the experimental data allows analysts to simultaneously investigate large amounts of potentially heterogeneous data, thereby solving the problem of joint analysis of topology and node attributes. As this approach does not modify the layout of pathway maps, it is compatible with arbitrary graph layouts, including those of hand-crafted, image-based pathway maps. We demonstrate the technique in context of pathways from the KEGG and the Wikipathways databases. We apply experimental data from two public databases, the Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Atlas (TCGA) that both contain a wide variety of genomic datasets for a large number of samples. In addition, we make use of a smaller dataset of hepatocellular carcinoma and common xenograft models. To verify the utility of enRoute, domain experts conducted two case studies where they explore data from the CCLE and the hepatocellular carcinoma datasets in the context of relevant pathways. '),
(95974, 2013, 'bmc', 'ViralPhos: incorporating a recursively statistical method to predict phosphorylation sites on virus proteins', 'Huang, Kai-Yao|Lu, Cheng-Tsung|Bretaña, Neil|Lee, Tzong-Yi|Chang, Tzu-Hao', 'Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.|Beaulieu-Saucier Université de Montréal Pharmacogenomics Center, Montreal Heart Institute Research Center, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca.', 'Canada|Canada|Canada|Canada|Canada', 11, 'Computational Biology|Databases, Protein|Internet|Models, Statistical|Phosphorylation|Phosphotransferases|Protein Structure, Tertiary|Reproducibility of Results|Support Vector Machine|Viral Proteins', 'Journal Article', '10.1186/1471-2105-14-S16-S10', '24564381', 'The phosphorylation of virus proteins by host kinases is linked to viral replication. This leads to an inhibition of normal host-cell functions. Further elucidation of phosphorylation in virus proteins is required in order to aid in drug design and treatment. However, only a few studies have investigated substrate motifs in identifying virus phosphorylation sites. Additionally, existing bioinformatics tool do not consider potential host kinases that may initiate the phosphorylation of a virus protein.');
