INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78198, 2014, 'bio', 'ngsTools: methods for population genetics analyses from next-generation sequencing data', 'Fumagalli, Matteo|Vieira, Filipe G|Linderoth, Tyler|Nielsen, Rasmus', 'Department of Integrative Biology, Department of Statistics, University of California, Berkeley, CA 94720, USA and Department of Biology, University of Copenhagen, Copenhagen 2200, Denmark.|Department of Integrative Biology, Department of Statistics, University of California, Berkeley, CA 94720, USA and Department of Biology, University of Copenhagen, Copenhagen 2200, Denmark.|Department of Integrative Biology, Department of Statistics, University of California, Berkeley, CA 94720, USA and Department of Biology, University of Copenhagen, Copenhagen 2200, Denmark.|Department of Integrative Biology, Department of Statistics, University of California, Berkeley, CA 94720, USA and Department of Biology, University of Copenhagen, Copenhagen 2200, Denmark.', 'Denmark|Denmark|Denmark|Denmark', 0, 'Algorithms|Genetics, Population|Genome|Genotype|High-Throughput Nucleotide Sequencing|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btu041', '24458950', 'Next-generation sequencing technologies produce short reads that are either de novo assembled or mapped to a reference genome. Genotypes and/or single-nucleotide polymorphisms are then determined from the read composition at each site, which become the basis for many downstream analyses. However, for low sequencing depths, e.g. , there is considerable statistical uncertainty in the assignment of genotypes because of random sampling of homologous base pairs in heterozygotes and sequencing or alignment errors. Recently, several probabilistic methods have been proposed to account for this uncertainty and make accurate inferences from low quality and/or coverage sequencing data. We present ngsTools, a collection of programs to perform population genetics analyses from next-generation sequencing data. The methods implemented in these programs do not rely on single-nucleotide polymorphism or genotype calling and are particularly suitable for low sequencing depth data.'),
(78199, 2014, 'bio', 'The most informative spacing test effectively discovers biologically relevant outliers or multiple modes in expression', 'Pawlikowska, Iwona|Wu, Gang|Edmonson, Michael|Liu, Zhifa|Gruber, Tanja|Zhang, Jinghui|Pounds, Stan', 'Departments of Biostatistics, St. Jude Childrens Research Hospital, Memphis, TN, USA, Institue of Mathematics, University of Silesia, Katowice, Poland, Department of Computational Biology and Department of Oncology, St. Jude Childrens Research Hospital, Memphis, TN, USA.|Departments of Biostatistics, St. Jude Childrens Research Hospital, Memphis, TN, USA, Institue of Mathematics, University of Silesia, Katowice, Poland, Department of Computational Biology and Department of Oncology, St. Jude Childrens Research Hospital, Memphis, TN, USA.|Departments of Biostatistics, St. Jude Childrens Research Hospital, Memphis, TN, USA, Institue of Mathematics, University of Silesia, Katowice, Poland, Department of Computational Biology and Department of Oncology, St. Jude Childrens Research Hospital, Memphis, TN, USA.|Departments of Biostatistics, St. Jude Childrens Research Hospital, Memphis, TN, USA, Institue of Mathematics, University of Silesia, Katowice, Poland, Department of Computational Biology and Department of Oncology, St. Jude Childrens Research Hospital, Memphis, TN, USA.|Departments of Biostatistics, St. Jude Childrens Research Hospital, Memphis, TN, USA, Institue of Mathematics, University of Silesia, Katowice, Poland, Department of Computational Biology and Department of Oncology, St. Jude Childrens Research Hospital, Memphis, TN, USA.|Departments of Biostatistics, St. Jude Childrens Research Hospital, Memphis, TN, USA, Institue of Mathematics, University of Silesia, Katowice, Poland, Department of Computational Biology and Department of Oncology, St. Jude Childrens Research Hospital, Memphis, TN, USA.|Departments of Biostatistics, St. Jude Childrens Research Hospital, Memphis, TN, USA, Institue of Mathematics, University of Silesia, Katowice, Poland, Department of Computational Biology and Department of Oncology, St. Jude Childrens Research Hospital, Memphis, TN, USA.', 'Poland|Poland|Poland|Poland|Poland|Poland|Poland', 6, 'Adult|Biometry|Child|Exons|Female|Gene Expression|Humans|Leukemia, Myeloid, Acute|Male|Models, Genetic|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btu039', '24458951', 'Several outlier and subgroup identification statistics (OASIS) have been proposed to discover transcriptomic features with outliers or multiple modes in expression that are indicative of distinct biological processes or subgroups. Here, we borrow ideas from the OASIS methods in the bioinformatics and statistics literature to develop the most informative spacing test (MIST) for unsupervised detection of such transcriptomic features. In an example application involving 14 cases of pediatric acute megakaryoblastic leukemia, MIST more robustly identified features that perfectly discriminate subjects according to gender or the presence of a prognostically relevant fusion-gene than did seven other OASIS methods in the analysis of RNA-seq exon expression, RNA-seq exon junction expression and micorarray exon expression data. MIST was also effective at identifying features related to gender or molecular subtype in an example application involving 157 adult cases of acute myeloid leukemia.'),
(78200, 2014, 'bio', 'Algorithms and tools for protein-protein interaction networks clustering, with a special focus on population-based stochastic methods', 'Pizzuti, Clara|Rombo, Simona E', 'Institute for High Performance Computing and Networking (ICAR), National Research Council of Italy (CNR), Via P. Bucci 41C, 87036 Rende (CS) and Department of Mathematics and Computer Science, University of Palermo, Via Archirafi 34, 90123 Palermo (PA), Italy.|Institute for High Performance Computing and Networking (ICAR), National Research Council of Italy (CNR), Via P. Bucci 41C, 87036 Rende (CS) and Department of Mathematics and Computer Science, University of Palermo, Via Archirafi 34, 90123 Palermo (PA), Italy.', 'Italy|Italy', 0, 'Algorithms|Animals|Cluster Analysis|Humans|Protein Interaction Mapping|Proteins', 'Journal Article', '10.1093/bioinformatics/btu034', '24458952', 'Protein-protein interaction (PPI) networks are powerful models to represent the pairwise protein interactions of the organisms. Clustering PPI networks can be useful for isolating groups of interacting proteins that participate in the same biological processes or that perform together specific biological functions. Evolutionary orthologies can be inferred this way, as well as functions and properties of yet uncharacterized proteins.'),
(78201, 2014, 'bio', 'Combinatorial therapy discovery using mixed integer linear programming', 'Pang, Kaifang|Wan, Ying-Wooi|Choi, William T|Donehower, Lawrence A|Sun, Jingchun|Pant, Dhruv|Liu, Zhandong', 'Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Jan and Dan Duncan Neurological Research Institute, Texas Childrens Hospital, Department of Pediatrics-Neurology, Department of Obstetrics and Gynaecology, Department of Molecular Virology and Microbiology, Baylor College of Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA, and Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.|Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Jan and Dan Duncan Neurological Research Institute, Texas Childrens Hospital, Department of Pediatrics-Neurology, Department of Obstetrics and Gynaecology, Department of Molecular Virology and Microbiology, Baylor College of Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA, and Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.|Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Jan and Dan Duncan Neurological Research Institute, Texas Childrens Hospital, Department of Pediatrics-Neurology, Department of Obstetrics and Gynaecology, Department of Molecular Virology and Microbiology, Baylor College of Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA, and Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.|Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Jan and Dan Duncan Neurological Research Institute, Texas Childrens Hospital, Department of Pediatrics-Neurology, Department of Obstetrics and Gynaecology, Department of Molecular Virology and Microbiology, Baylor College of Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA, and Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.|Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Jan and Dan Duncan Neurological Research Institute, Texas Childrens Hospital, Department of Pediatrics-Neurology, Department of Obstetrics and Gynaecology, Department of Molecular Virology and Microbiology, Baylor College of Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA, and Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.|Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Jan and Dan Duncan Neurological Research Institute, Texas Childrens Hospital, Department of Pediatrics-Neurology, Department of Obstetrics and Gynaecology, Department of Molecular Virology and Microbiology, Baylor College of Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA, and Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.|Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Jan and Dan Duncan Neurological Research Institute, Texas Childrens Hospital, Department of Pediatrics-Neurology, Department of Obstetrics and Gynaecology, Department of Molecular Virology and Microbiology, Baylor College of Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA, and Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.', 'United States|United States|United States|United States|United States|United States|United States', 16, 'Algorithms|Databases, Factual|Diabetes Mellitus, Type 2|Drug Combinations|Gene Regulatory Networks|Humans|Myocardial Infarction|Programming, Linear|Software Design', 'Journal Article', '10.1093/bioinformatics/btu046', '24463180', 'Combinatorial therapies play increasingly important roles in combating complex diseases. Owing to the huge cost associated with experimental methods in identifying optimal drug combinations, computational approaches can provide a guide to limit the search space and reduce cost. However, few computational approaches have been developed for this purpose, and thus there is a great need of new algorithms for drug combination prediction.'),
(78202, 2014, 'bio', 'Cas-OFFinder: a fast and versatile algorithm that searches for potential off-target sites of Cas9 RNA-guided endonucleases', 'Bae, Sangsu|Park, Jeongbin|Kim, Jin-Soo', 'National Creative Research Initiatives Center for Genome Engineering, Department of Chemistry and Department of Physics and Astronomy, Seoul National University, 599 Gwanak-ro, Seoul 151-742, South Korea.|National Creative Research Initiatives Center for Genome Engineering, Department of Chemistry and Department of Physics and Astronomy, Seoul National University, 599 Gwanak-ro, Seoul 151-742, South Korea.|National Creative Research Initiatives Center for Genome Engineering, Department of Chemistry and Department of Physics and Astronomy, Seoul National University, 599 Gwanak-ro, Seoul 151-742, South Korea.', '-|-|-', 0, 'Algorithms|Animals|Bacterial Proteins|Base Sequence|CRISPR-Associated Protein 9|DNA|Endonucleases|Genome, Human|Genome, Plant|Humans|Mice|RNA, Guide|Sequence Analysis, DNA|Software|Time Factors', 'Evaluation Studies', '10.1093/bioinformatics/btu048', '24463181', 'The Type II clustered regularly interspaced short palindromic repeats (CRISPR)/Cas system is an adaptive immune response in prokaryotes, protecting host cells against invading phages or plasmids by cleaving these foreign DNA species in a targeted manner. CRISPR/Cas-derived RNA-guided engineered nucleases (RGENs) enable genome editing in cultured cells, animals and plants, but are limited by off-target mutations. Here, we present a novel algorithm termed Cas-OFFinder that searches for potential off-target sites in a given genome or user-defined sequences. Unlike other algorithms currently available for identification of RGEN off-target sites, Cas-OFFinder is not limited by the number of mismatches and allows variations in protospacer-adjacent motif sequences recognized by Cas9, the essential protein component in RGENs. Cas-OFFinder is available as a command-line program or accessible via our website.'),
(78203, 2014, 'bio', 'ECplot: an online tool for making standardized plots from large datasets for bioinformatics publications', 'Fok, Alex Chun-Hong|Mok, Sunny Siu-Nam|Lee, Sau Dan|Yip, Kevin Y', 'Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.|Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.|Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.|Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong', 0, 'Computational Biology|Databases, Factual|Internet|Programming Languages|Publications|Software', 'Journal Article', '10.1093/bioinformatics/btu038', '24463182', 'We have implemented ECplot, an online tool for plotting charts from large datasets. This tool supports a variety of chart types commonly used in bioinformatics publications. In our benchmarking, it was able to create a Box-and-Whisker plot with about 67 000 data points and 8 MB total file size within several seconds. The design of the tool makes common formatting operations easy to perform. It also allows more complex operations to be achieved by advanced XML (Extensible Markup Language) and programming options. Data and formatting styles are stored in separate files, such that style templates can be made and applied to new datasets. The text-based file formats based on XML facilitate efficient manipulation of formatting styles for a large number of data series. These file formats also provide a means to reproduce published figures from raw data, which complement parallel efforts in making the data and software involved in published analysis results accessible. We demonstrate this idea by using ECplot to replicate some complex figures from a previous publication.'),
(78204, 2014, 'bio', 'G-BLASTN: accelerating nucleotide alignment by graphics processors', 'Zhao, Kaiyong|Chu, Xiaowen', 'Department of Computer Science, Hong Kong Baptist University, Hong Kong, China and Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Hong Kong, China.|Department of Computer Science, Hong Kong Baptist University, Hong Kong, China and Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Hong Kong, China.', 'China|China', 0, 'Algorithms|Base Sequence|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btu047', '24463183', 'Since 1990, the basic local alignment search tool (BLAST) has become one of the most popular and fundamental bioinformatics tools for sequence similarity searching, receiving extensive attention from the research community. The two pioneering papers on BLAST have received over 96 000 citations. Given the huge population of BLAST users and the increasing size of sequence databases, an urgent topic of study is how to improve the speed. Recently, graphics processing units (GPUs) have been widely used as low-cost, high-performance computing platforms. The existing GPU-BLAST is a promising software tool that uses a GPU to accelerate protein sequence alignment. Unfortunately, there is still no GPU-accelerated software tool for BLAST-based nucleotide sequence alignment.'),
(78205, 2014, 'bio', 'Modeling tissue contamination to improve molecular identification of the primary tumor site of metastases', 'Vincent, Martin|Perell, Katharina|Nielsen, Finn Cilius|Daugaard, Gedske|Hansen, Niels Richard', 'Department of Mathematical Sciences, University of Copenhagen, Department of Oncology, and Center for Genomic Medicine, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen xc3x98, Denmark.|Department of Mathematical Sciences, University of Copenhagen, Department of Oncology, and Center for Genomic Medicine, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen xc3x98, Denmark.|Department of Mathematical Sciences, University of Copenhagen, Department of Oncology, and Center for Genomic Medicine, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen xc3x98, Denmark.|Department of Mathematical Sciences, University of Copenhagen, Department of Oncology, and Center for Genomic Medicine, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen xc3x98, Denmark.|Department of Mathematical Sciences, University of Copenhagen, Department of Oncology, and Center for Genomic Medicine, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen xc3x98, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark', 4, 'Biopsy|Gene Expression Regulation, Neoplastic|Humans|Liver Neoplasms|MicroRNAs|Models, Genetic', 'Journal Article', '10.1093/bioinformatics/btu044', '24463184', 'Contamination of a cancer tissue by the surrounding benign (non-cancerous) tissue is a concern for molecular cancer diagnostics. This is because an observed molecular signature will be distorted by the surrounding benign tissue, possibly leading to an incorrect diagnosis. One example is molecular identification of the primary tumor site of metastases because biopsies of metastases typically contain a significant amount of benign tissue.'),
(78206, 2014, 'bio', 'Comparison of approaches for parameter identifiability analysis of biological systems', 'Raue, Andreas|Karlsson, Johan|Saccomani, Maria Pia|Jirstrand, Mats|Timmer, Jens', 'University of Freiburg, Institute for Physics, 79104 Freiburg, Germany, Merrimack Pharmaceuticals Inc., 02139 Cambridge, MA, USA, Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Göteborg, Sweden, Department of Information Engineering, University of Padova, 35131 Padova, Italy, BIOSS Centre for Biological Signalling Studies and Zentrum für Biosystemanalyse (ZBSA), University of Freiburg, 79104 Freiburg, Germany.|University of Freiburg, Institute for Physics, 79104 Freiburg, Germany, Merrimack Pharmaceuticals Inc., 02139 Cambridge, MA, USA, Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Göteborg, Sweden, Department of Information Engineering, University of Padova, 35131 Padova, Italy, BIOSS Centre for Biological Signalling Studies and Zentrum für Biosystemanalyse (ZBSA), University of Freiburg, 79104 Freiburg, Germany.|University of Freiburg, Institute for Physics, 79104 Freiburg, Germany, Merrimack Pharmaceuticals Inc., 02139 Cambridge, MA, USA, Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Göteborg, Sweden, Department of Information Engineering, University of Padova, 35131 Padova, Italy, BIOSS Centre for Biological Signalling Studies and Zentrum für Biosystemanalyse (ZBSA), University of Freiburg, 79104 Freiburg, Germany.|University of Freiburg, Institute for Physics, 79104 Freiburg, Germany, Merrimack Pharmaceuticals Inc., 02139 Cambridge, MA, USA, Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Göteborg, Sweden, Department of Information Engineering, University of Padova, 35131 Padova, Italy, BIOSS Centre for Biological Signalling Studies and Zentrum für Biosystemanalyse (ZBSA), University of Freiburg, 79104 Freiburg, Germany.|University of Freiburg, Institute for Physics, 79104 Freiburg, Germany, Merrimack Pharmaceuticals Inc., 02139 Cambridge, MA, USA, Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Göteborg, Sweden, Department of Information Engineering, University of Padova, 35131 Padova, Italy, BIOSS Centre for Biological Signalling Studies and Zentrum für Biosystemanalyse (ZBSA), University of Freiburg, 79104 Freiburg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Cell Line, Tumor|Gene Expression Regulation, Neoplastic|Humans|Interleukin-13|Lymphoma|Models, Biological|RNA, Messenger|Research Design|Systems Biology', 'Comparative Study', '10.1093/bioinformatics/btu006', '24463185', 'Modeling of dynamical systems using ordinary differential equations is a popular approach in the field of Systems Biology. The amount of experimental data that are used to build and calibrate these models is often limited. In this setting, the model parameters may not be uniquely determinable. Structural or a priori identifiability is a property of the system equations that indicates whether, in principle, the unknown model parameters can be determined from the available data.'),
(78207, 2014, 'bio', 'Parseq: reconstruction of microbial transcription landscape from RNA-Seq read counts using state-space models', 'Mirauta, Bogdan|Nicolas, Pierre|Richard, Hugues', 'Biologie Computationnelle et Quantitative, UPMC and CNRS UMR7238, Paris, France and Mathématique Informatique et Génome, INRA UR1077, Jouy-en-Josas, France.|Biologie Computationnelle et Quantitative, UPMC and CNRS UMR7238, Paris, France and Mathématique Informatique et Génome, INRA UR1077, Jouy-en-Josas, France.|Biologie Computationnelle et Quantitative, UPMC and CNRS UMR7238, Paris, France and Mathématique Informatique et Génome, INRA UR1077, Jouy-en-Josas, France.', 'France|France|France', 6, 'Algorithms|Escherichia coli|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Markov Chains|Models, Genetic|Monte Carlo Method|RNA|Saccharomyces cerevisiae|Sequence Analysis, RNA|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btu042', '24470570', 'The most common RNA-Seq strategy consists of random shearing, amplification and high-throughput sequencing of the RNA fraction. Methods to analyze transcription level variations along the genome from the read count profiles generated by the RNA-Seq protocol are needed.'),
(78208, 2014, 'bio', 'Bio Simulators: a web UI for biological simulation', 'Pedersen, Michael|Oury, Nicolas|Gravill, Colin|Phillips, Andrew', 'Department of Plant Sciences, Cambridge University, Cambridge CB2 3EA, UK, School of Informatics, Edinburgh University, Edinburgh EH8 9AB, Scotland and Microsoft Research, Cambridge CB1 2FB, UK.|Department of Plant Sciences, Cambridge University, Cambridge CB2 3EA, UK, School of Informatics, Edinburgh University, Edinburgh EH8 9AB, Scotland and Microsoft Research, Cambridge CB1 2FB, UK.|Department of Plant Sciences, Cambridge University, Cambridge CB2 3EA, UK, School of Informatics, Edinburgh University, Edinburgh EH8 9AB, Scotland and Microsoft Research, Cambridge CB1 2FB, UK.|Department of Plant Sciences, Cambridge University, Cambridge CB2 3EA, UK, School of Informatics, Edinburgh University, Edinburgh EH8 9AB, Scotland and Microsoft Research, Cambridge CB1 2FB, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Internet|Software|Software Design', 'Journal Article', '10.1093/bioinformatics/btu050', '24470571', 'A host of formal, textual languages for modeling cellular processes have recently emerged, but their simulation tools often require an installation process which can pose a barrier for use. Bio Simulators is a framework for easy online deployment of simulators, providing a uniform web-based user interface to a diverse pool of tools. The framework is demonstrated through two plugins based on the KaSim Kappa simulator, one running directly in the browser and another running in the cloud.'),
(78209, 2014, 'bio', 'ChEpiMod: a knowledgebase for chemical modulators of epigenome reader domains', 'Meslamani, Jamel|Smith, Steven G|Sanchez, Roberto|Zhou, Ming-Ming', 'Department of Structural and Chemical Biology, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA.|Department of Structural and Chemical Biology, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA.|Department of Structural and Chemical Biology, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA.|Department of Structural and Chemical Biology, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, USA.', 'United States|United States|United States|United States', 11, 'Amino Acid Sequence|Databases, Genetic|Epigenesis, Genetic|Genomics|Humans|Ligands|Molecular Sequence Data|Small Molecule Libraries|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btu052', '24470572', 'Epigenome reader domains are rapidly emerging as a new class of drug targets for a wide array of human diseases. To facilitate study of structure-activity relationship and small-molecule ligand design for these domains, we have created ChEpiMod. ChEpiMod is a free knowledgebase of chemical modulators with documented modulatory activity for epigenome reader domains.'),
(78210, 2014, 'bio', 'Network orientation via shortest paths', 'Silverbush, Dana|Sharan, Roded', 'The Balavatnik School of Computer Science, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|The Balavatnik School of Computer Science, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel.', 'Israel|Israel', 0, 'Algorithms|Linear Models|Protein Binding|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu043', '24470573', 'The graph orientation problem calls for orienting the edges of a graph so as to maximize the number of pre-specified source-target vertex pairs that admit a directed path from the source to the target. Most algorithmic approaches to this problem share a common preprocessing step, in which the input graph is reduced to a tree by repeatedly contracting its cycles. Although this reduction is valid from an algorithmic perspective, the assignment of directions to the edges of the contracted cycles becomes arbitrary, and the connecting source-target paths may be arbitrarily long. In the context of biological networks, the connection of vertex pairs via shortest paths is highly motivated, leading to the following problem variant: given a graph and a collection of source-target vertex pairs, assign directions to the edges so as to maximize the number of pairs that are connected by a shortest (in the original graph) directed path. This problem is NP-complete and hard to approximate to within sub-polynomial factors. Here we provide a first polynomial-size integer linear program formulation for this problem, which allows its exact solution in seconds on current networks. We apply our algorithm to orient protein-protein interaction networks in yeast and compare it with two state-of-the-art algorithms. We find that our algorithm outperforms previous approaches and can orient considerable parts of the network, thus revealing its structure and function.'),
(78211, 2014, 'bio', 'PGP: parallel prokaryotic proteogenomics pipeline for MPI clusters, high-throughput batch clusters and multicore workstations', 'Tovchigrechko, Andrey|Venepally, Pratap|Payne, Samuel H', 'J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850 and Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99354, USA.|J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850 and Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99354, USA.|J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850 and Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99354, USA.', 'United States|United States|United States', 12, 'Cluster Analysis|Genomics|High-Throughput Nucleotide Sequencing|Mass Spectrometry|Prokaryotic Cells|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btu051', '24470574', 'We present the first public release of our proteogenomic annotation pipeline. We have previously used our original unreleased implementation to improve the annotation of 46 diverse prokaryotic genomes by discovering novel genes, post-translational modifications and correcting the erroneous annotations by analyzing proteomic mass-spectrometry data. This public version has been redesigned to run in a wide range of parallel Linux computing environments and provided with the automated configuration, build and testing facilities for easy deployment and portability.'),
(78212, 2014, 'bio', 'Composition of seed sequence is a major determinant of microRNA targeting patterns', 'Wang, Xiaowei', 'Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO 63108, USA.', 'United States', 0, 'Base Composition|Cell Line|Gene Expression Regulation|High-Throughput Nucleotide Sequencing|Humans|MicroRNAs|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btu045', '24470575', 'MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in gene expression regulation. One major roadblock in functional miRNA studies is the reliable prediction of genes targeted by miRNAs, as rules defining miRNA target recognition have not been well-established to date. Availability of high-throughput experimental data from a recent CLASH (cross linking, ligation and sequencing of hybrids) study has presented an unprecedented opportunity to characterize miRNA target recognition patterns, which may provide guidance for improved miRNA target prediction.'),
(78213, 2014, 'bio', 'NGSANE: a lightweight production informatics framework for high-throughput data analysis', 'Buske, Fabian A|French, Hugh J|Smith, Martin A|Clark, Susan J|Bauer, Denis C', 'Cancer Epigenetics Program, Cancer Research Division, Kinghorn Cancer Centre, Garvan Institute of Medical Research, RNA Biology and Plasticity Laboratory, Garvan Institute of Medical Research, St Vincents Clinical School, University of NSW, Sydney 2010, Australia and Division of Computational Informatics, CSIRO, Sydney 2113, Australia.|Cancer Epigenetics Program, Cancer Research Division, Kinghorn Cancer Centre, Garvan Institute of Medical Research, RNA Biology and Plasticity Laboratory, Garvan Institute of Medical Research, St Vincents Clinical School, University of NSW, Sydney 2010, Australia and Division of Computational Informatics, CSIRO, Sydney 2113, Australia.|Cancer Epigenetics Program, Cancer Research Division, Kinghorn Cancer Centre, Garvan Institute of Medical Research, RNA Biology and Plasticity Laboratory, Garvan Institute of Medical Research, St Vincents Clinical School, University of NSW, Sydney 2010, Australia and Division of Computational Informatics, CSIRO, Sydney 2113, Australia.|Cancer Epigenetics Program, Cancer Research Division, Kinghorn Cancer Centre, Garvan Institute of Medical Research, RNA Biology and Plasticity Laboratory, Garvan Institute of Medical Research, St Vincents Clinical School, University of NSW, Sydney 2010, Australia and Division of Computational Informatics, CSIRO, Sydney 2113, Australia.|Cancer Epigenetics Program, Cancer Research Division, Kinghorn Cancer Centre, Garvan Institute of Medical Research, RNA Biology and Plasticity Laboratory, Garvan Institute of Medical Research, St Vincents Clinical School, University of NSW, Sydney 2010, Australia and Division of Computational Informatics, CSIRO, Sydney 2113, Australia.', 'Australia|Australia|Australia|Australia|Australia', 0, 'Automation, Laboratory|High-Throughput Nucleotide Sequencing|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btu036', '24470576', 'The initial steps in the analysis of next-generation sequencing data can be automated by way of software pipelines. However, individual components depreciate rapidly because of the evolving technology and analysis methods, often rendering entire versions of production informatics pipelines obsolete. Constructing pipelines from Linux bash commands enables the use of hot swappable modular components as opposed to the more rigid program call wrapping by higher level languages, as implemented in comparable published pipelining systems. Here we present Next Generation Sequencing ANalysis for Enterprises (NGSANE), a Linux-based, high-performance-computing-enabled framework that minimizes overhead for set up and processing of new projects, yet maintains full flexibility of custom scripting when processing raw sequence data.'),
(78214, 2014, 'bio', 'PUmPER: phylogenies updated perpetually', 'Izquierdo-Carrasco, Fernando|Cazes, John|Smith, Stephen A|Stamatakis, Alexandros', 'Scientific Computing Group, Heidelberg Institute for Theoretical Studies (HITS gGmbH), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg, Baden-Württemberg, Germany, Texas Advanced Computing Center, University of Texas, Austin, TX, 78758, USA, University of Michigan, Ann Arbor Department of Ecology and Evolutionary Biology, 48109, MI, USA and Karlsruhe Institute of Technology, Institute for Theoretical Informatics, Postfach 6980, 76128 Karlsruhe, Baden-Württemberg, Germany.|Scientific Computing Group, Heidelberg Institute for Theoretical Studies (HITS gGmbH), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg, Baden-Württemberg, Germany, Texas Advanced Computing Center, University of Texas, Austin, TX, 78758, USA, University of Michigan, Ann Arbor Department of Ecology and Evolutionary Biology, 48109, MI, USA and Karlsruhe Institute of Technology, Institute for Theoretical Informatics, Postfach 6980, 76128 Karlsruhe, Baden-Württemberg, Germany.|Scientific Computing Group, Heidelberg Institute for Theoretical Studies (HITS gGmbH), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg, Baden-Württemberg, Germany, Texas Advanced Computing Center, University of Texas, Austin, TX, 78758, USA, University of Michigan, Ann Arbor Department of Ecology and Evolutionary Biology, 48109, MI, USA and Karlsruhe Institute of Technology, Institute for Theoretical Informatics, Postfach 6980, 76128 Karlsruhe, Baden-Württemberg, Germany.|Scientific Computing Group, Heidelberg Institute for Theoretical Studies (HITS gGmbH), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg, Baden-Württemberg, Germany, Texas Advanced Computing Center, University of Texas, Austin, TX, 78758, USA, University of Michigan, Ann Arbor Department of Ecology and Evolutionary Biology, 48109, MI, USA and Karlsruhe Institute of Technology, Institute for Theoretical Informatics, Postfach 6980, 76128 Karlsruhe, Baden-Württemberg, Germany.', 'Germany|Germany|Germany|Germany', 11, 'Databases, Genetic|Embryophyta|Phylogeny|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btu053', '24478338', 'New sequence data useful for phylogenetic and evolutionary analyses continues to be added to public databases. The construction of multiple sequence alignments and inference of huge phylogenies comprising large taxonomic groups are expensive tasks, both in terms of man hours and computational resources. Therefore, maintaining comprehensive phylogenies, based on representative and up-to-date molecular sequences, is challenging. PUmPER is a framework that can perpetually construct multi-gene alignments (with PHLAWD) and phylogenetic trees (with ExaML or RAxML-Light) for a given NCBI taxonomic group. When sufficient numbers of new gene sequences for the selected taxonomic group have accumulated in GenBank, PUmPER automatically extends the alignment and infers extended phylogenetic trees by using previously inferred smaller trees as starting topologies. Using our framework, large phylogenetic trees can be perpetually updated without human intervention. Importantly, resulting phylogenies are not statistically significantly worse than trees inferred from scratch.'),
(78215, 2014, 'bio', 'Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays', 'Aryee, Martin J|Jaffe, Andrew E|Corrada-Bravo, Hector|Ladd-Acosta, Christine|Feinberg, Andrew P|Hansen, Kasper D|Irizarry, Rafael A', 'Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA, Department of Biostatistics, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Lieber Institute of Brain Development, Johns Hopkins Medical Campus, 855 N Wolfe Street, Baltimore, MD 21205, USA, Department of Computer Science, University of Maryland, College Park, MD 20742, USA, Department of Epidemiology, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Center for Epigenetics and Department of Medicine, Johns Hopkins University School of Medicine, 570 Rangos, 725 N Wolfe Street, Baltimore, MD 21205, USA and Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.|Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA, Department of Biostatistics, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Lieber Institute of Brain Development, Johns Hopkins Medical Campus, 855 N Wolfe Street, Baltimore, MD 21205, USA, Department of Computer Science, University of Maryland, College Park, MD 20742, USA, Department of Epidemiology, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Center for Epigenetics and Department of Medicine, Johns Hopkins University School of Medicine, 570 Rangos, 725 N Wolfe Street, Baltimore, MD 21205, USA and Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.|Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA, Department of Biostatistics, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Lieber Institute of Brain Development, Johns Hopkins Medical Campus, 855 N Wolfe Street, Baltimore, MD 21205, USA, Department of Computer Science, University of Maryland, College Park, MD 20742, USA, Department of Epidemiology, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Center for Epigenetics and Department of Medicine, Johns Hopkins University School of Medicine, 570 Rangos, 725 N Wolfe Street, Baltimore, MD 21205, USA and Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.|Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA, Department of Biostatistics, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Lieber Institute of Brain Development, Johns Hopkins Medical Campus, 855 N Wolfe Street, Baltimore, MD 21205, USA, Department of Computer Science, University of Maryland, College Park, MD 20742, USA, Department of Epidemiology, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Center for Epigenetics and Department of Medicine, Johns Hopkins University School of Medicine, 570 Rangos, 725 N Wolfe Street, Baltimore, MD 21205, USA and Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.|Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA, Department of Biostatistics, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Lieber Institute of Brain Development, Johns Hopkins Medical Campus, 855 N Wolfe Street, Baltimore, MD 21205, USA, Department of Computer Science, University of Maryland, College Park, MD 20742, USA, Department of Epidemiology, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Center for Epigenetics and Department of Medicine, Johns Hopkins University School of Medicine, 570 Rangos, 725 N Wolfe Street, Baltimore, MD 21205, USA and Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.|Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA, Department of Biostatistics, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Lieber Institute of Brain Development, Johns Hopkins Medical Campus, 855 N Wolfe Street, Baltimore, MD 21205, USA, Department of Computer Science, University of Maryland, College Park, MD 20742, USA, Department of Epidemiology, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Center for Epigenetics and Department of Medicine, Johns Hopkins University School of Medicine, 570 Rangos, 725 N Wolfe Street, Baltimore, MD 21205, USA and Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.|Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA, Department of Biostatistics, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Lieber Institute of Brain Development, Johns Hopkins Medical Campus, 855 N Wolfe Street, Baltimore, MD 21205, USA, Department of Computer Science, University of Maryland, College Park, MD 20742, USA, Department of Epidemiology, Johns Hopkins School of Public Health, 615 N Wolfe Street, Baltimore, MD 21205, USA, Center for Epigenetics and Department of Medicine, Johns Hopkins University School of Medicine, 570 Rangos, 725 N Wolfe Street, Baltimore, MD 21205, USA and Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.', 'United States|United States|United States|United States|United States|United States|United States', 1150, 'Aged|Algorithms|Colonic Neoplasms|DNA Methylation|Genome|High-Throughput Nucleotide Sequencing|Humans|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btu049', '24478339', 'The recently released Infinium HumanMethylation450 array (the 450k array) provides a high-throughput assay to quantify DNA methylation (DNAm) at xe2x88xbc450 000 loci across a range of genomic features. Although less comprehensive than high-throughput sequencing-based techniques, this product is more cost-effective and promises to be the most widely used DNAm high-throughput measurement technology over the next several years.'),
(78216, 2014, 'bio', 'bwtool: a tool for bigWig files', 'Pohl, Andy|Beato, Miguel', 'Department of Gene Regulation, Stem Cells, and Cancer, Centre for Genomic Regulation (CRG) and Department of Experimental and Health Sciences (CEXS), Universitat Pompeu Fabra, 08003 Barcelona, SpainDepartment of Gene Regulation, Stem Cells, and Cancer, Centre for Genomic Regulation (CRG) and Department of Experimental and Health Sciences (CEXS), Universitat Pompeu Fabra, 08003 Barcelona, Spain.|Department of Gene Regulation, Stem Cells, and Cancer, Centre for Genomic Regulation (CRG) and Department of Experimental and Health Sciences (CEXS), Universitat Pompeu Fabra, 08003 Barcelona, SpainDepartment of Gene Regulation, Stem Cells, and Cancer, Centre for Genomic Regulation (CRG) and Department of Experimental and Health Sciences (CEXS), Universitat Pompeu Fabra, 08003 Barcelona, Spain.', 'Spain|Spain', 69, 'Chromatin Immunoprecipitation|Genomics|Histones|Sequence Analysis, DNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu056', '24489365', 'BigWig files are a compressed, indexed, binary format for genome-wide signal data for calculations (e.g. GC percent) or experiments (e.g. ChIP-seq/RNA-seq read depth). bwtool is a tool designed to read bigWig files rapidly and efficiently, providing functionality for extracting data and summarizing it in several ways, globally or at specific regions. Additionally, the tool enables the conversion of the positions of signal data from one genome assembly to another, also known as lifting. We believe bwtool can be useful for the analyst frequently working with bigWig data, which is becoming a standard format to represent functional signals along genomes. The article includes supplementary examples of running the software.'),
(78217, 2014, 'bio', 'Mobyle SNAP Workbench: a web-based analysis portal for population genetics and evolutionary genomics', 'Monacell, James T|Carbone, Ignazio', 'Center for Integrated Fungal Research, Department of Plant Pathology and Bioinformatics Research Center, North Carolina State University, NC 27695, USA.|Center for Integrated Fungal Research, Department of Plant Pathology and Bioinformatics Research Center, North Carolina State University, NC 27695, USA.', 'United States|United States', 43, 'Automation, Laboratory|Genetics, Population|Genomics|Internet|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btu055', '24489366', 'Previously we developed the stand-alone SNAP Workbench toolkit that integrated a wide array of bioinformatics tools for phylogenetic and population genetic analyses. We have now developed a web-based portal front-end, using the Mobyle portal framework, which executes all of the programs available in the stand-alone SNAP Workbench toolkit on a high-performance Linux cluster. Additionally, we have expanded the selection of programs to over 189 tools, including population genetic, genome assembly and analysis tools, as well as metagenomic and large-scale phylogenetic analyses. The Mobyle SNAP Workbench web portal allows end users to (i) execute and manage otherwise complex command-line programs, (ii) launch multiple exploratory analyses of parameter-rich and computationally intensive methods and (iii) track the sequence of steps and parameters that were used to perform a specific analysis. Analysis pipelines or workflows for population genetic, metagenomic and genome assembly provide automation of data conversion, analysis and graphical visualization for biological inference.'),
(78218, 2014, 'bio', 'Bayesian joint analysis of heterogeneous genomics data', 'Ray, Priyadip|Zheng, Lingling|Lucas, Joseph|Carin, Lawrence', 'G.S.Sanyal School of Telecommunications, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India, Computational Biology & Bioinformatics, Duke University, Durham, NC 27705, USA, Quintiles, Durham, NC 27703, USA and Electrical & Computer Engineering Department, Duke University, Durham, NC 27705, USA.|G.S.Sanyal School of Telecommunications, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India, Computational Biology & Bioinformatics, Duke University, Durham, NC 27705, USA, Quintiles, Durham, NC 27703, USA and Electrical & Computer Engineering Department, Duke University, Durham, NC 27705, USA.|G.S.Sanyal School of Telecommunications, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India, Computational Biology & Bioinformatics, Duke University, Durham, NC 27705, USA, Quintiles, Durham, NC 27703, USA and Electrical & Computer Engineering Department, Duke University, Durham, NC 27705, USA.|G.S.Sanyal School of Telecommunications, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India, Computational Biology & Bioinformatics, Duke University, Durham, NC 27705, USA, Quintiles, Durham, NC 27703, USA and Electrical & Computer Engineering Department, Duke University, Durham, NC 27705, USA.', 'India|India|India|India', 35, 'Bayes Theorem|DNA Copy Number Variations|DNA Methylation|Female|Gene Expression Regulation|Genomics|Humans|Ovarian Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btu064', '24489367', 'A non-parametric Bayesian factor model is proposed for joint analysis of multi-platform genomics data. The approach is based on factorizing the latent space (feature space) into a shared component and a data-specific component with the dimensionality of these components (spaces) inferred via a beta-Bernoulli process. The proposed approach is demonstrated by jointly analyzing gene expression/copy number variations and gene expression/methylation data for ovarian cancer patients, showing that the proposed model can potentially uncover key drivers related to cancer.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78219, 2014, 'bio', 'Event trigger identification for biomedical events extraction using domain knowledge', 'Zhou, Deyu|Zhong, Dayou|He, Yulan', 'School of Computer Science and Engineering, Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210096, China, and School of Engineering and Applied Science, Aston University, Birmingham B4 7ET, UK.|School of Computer Science and Engineering, Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210096, China, and School of Engineering and Applied Science, Aston University, Birmingham B4 7ET, UK.|School of Computer Science and Engineering, Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210096, China, and School of Engineering and Applied Science, Aston University, Birmingham B4 7ET, UK.', 'China|China|China', 37, 'Artificial Intelligence|Data Mining|MEDLINE|Neural Networks (Computer)|Semantics', 'Journal Article', '10.1093/bioinformatics/btu061', '24489368', 'In molecular biology, molecular events describe observable alterations of biomolecules, such as binding of proteins or RNA production. These events might be responsible for drug reactions or development of certain diseases. As such, biomedical event extraction, the process of automatically detecting description of molecular interactions in research articles, attracted substantial research interest recently. Event trigger identification, detecting the words describing the event types, is a crucial and prerequisite step in the pipeline process of biomedical event extraction. Taking the event types as classes, event trigger identification can be viewed as a classification task. For each word in a sentence, a trained classifier predicts whether the word corresponds to an event type and which event type based on the context features. Therefore, a well-designed feature set with a good level of discrimination and generalization is crucial for the performance of event trigger identification.'),
(78220, 2014, 'bio', 'Comparing DNA integration site clusters with scan statistics', 'Berry, Charles C|Ocwieja, Karen E|Malani, Nirav|Bushman, Frederic D', 'Division of Biostatistics and BioInformatics, Department of Family and Preventive Medicine, University of California at San Diego, La Jolla, CA 92093-0901 and Department of Microbiology, Perelman School of Medicine at the University of Pennsylvania, 425 Johnson Pavilion, Philadelphia, PA 19104-6076, USA.|Division of Biostatistics and BioInformatics, Department of Family and Preventive Medicine, University of California at San Diego, La Jolla, CA 92093-0901 and Department of Microbiology, Perelman School of Medicine at the University of Pennsylvania, 425 Johnson Pavilion, Philadelphia, PA 19104-6076, USA.|Division of Biostatistics and BioInformatics, Department of Family and Preventive Medicine, University of California at San Diego, La Jolla, CA 92093-0901 and Department of Microbiology, Perelman School of Medicine at the University of Pennsylvania, 425 Johnson Pavilion, Philadelphia, PA 19104-6076, USA.|Division of Biostatistics and BioInformatics, Department of Family and Preventive Medicine, University of California at San Diego, La Jolla, CA 92093-0901 and Department of Microbiology, Perelman School of Medicine at the University of Pennsylvania, 425 Johnson Pavilion, Philadelphia, PA 19104-6076, USA.', 'United States|United States|United States|United States', 13, 'Algorithms|Artificial Intelligence|DNA|Data Interpretation, Statistical|Genetic Vectors|Genomics|HIV|Humans|Jurkat Cells|Software|Virus Integration', 'Journal Article', '10.1093/bioinformatics/btu035', '24489369', 'Gene therapy with retroviral vectors can induce adverse effects when those vectors integrate in sensitive genomic regions. Retroviral vectors are preferred that target sensitive regions less frequently, motivating the search for localized clusters of integration sites and comparison of the clusters formed by integration of different vectors. Scan statistics allow the discovery of spatial differences in clustering and calculation of false discovery rates providing statistical methods for comparing retroviral vectors.'),
(78221, 2014, 'bio', 'Integrative gene set analysis of multi-platform data with sample heterogeneity', 'Hu, Jun|Tzeng, Jung-Ying', 'Bioinformatics Research Center, North Carolina State University, Ricks Hall, 1 Lampe Dr., Raleigh, NC 27607, USA, Division of Bioinformatics, Omicsoft Inc., 200 Cascade Pointe Lane, Suite 101, Cary, NC 27513, USA, Department of Statistics, North Carolina State University, Ricks Hall, 1 Lampe Dr., Raleigh, NC 27607, USA and Department of Statistics, National Cheng-Kung University, No.1, University Road, Tainan 701, TaiwanBioinformatics Research Center, North Carolina State University, Ricks Hall, 1 Lampe Dr., Raleigh, NC 27607, USA, Division of Bioinformatics, Omicsoft Inc., 200 Cascade Pointe Lane, Suite 101, Cary, NC 27513, USA, Department of Statistics, North Carolina State University, Ricks Hall, 1 Lampe Dr., Raleigh, NC 27607, USA and Department of Statistics, National Cheng-Kung University, No.1, University Road, Tainan 701, Taiwan.|Bioinformatics Research Center, North Carolina State University, Ricks Hall, 1 Lampe Dr., Raleigh, NC 27607, USA, Division of Bioinformatics, Omicsoft Inc., 200 Cascade Pointe Lane, Suite 101, Cary, NC 27513, USA, Department of Statistics, North Carolina State University, Ricks Hall, 1 Lampe Dr., Raleigh, NC 27607, USA and Department of Statistics, National Cheng-Kung University, No.1, University Road, Tainan 701, TaiwanBioinformatics Research Center, North Carolina State University, Ricks Hall, 1 Lampe Dr., Raleigh, NC 27607, USA, Division of Bioinformatics, Omicsoft Inc., 200 Cascade Pointe Lane, Suite 101, Cary, NC 27513, USA, Department of Statistics, North Carolina State University, Ricks Hall, 1 Lampe Dr., Raleigh, NC 27607, USA and Department of Statistics, National Cheng-Kung University, No.1, University Road, Tainan 701, TaiwanBioinformatics Research Center, North Carolina State University, Ricks Hall, 1 Lampe Dr., Raleigh, NC 27607, USA, Division of Bioinformatics, Omicsoft Inc., 200 Cascade Pointe Lane, Suite 101, Cary, NC 27513, USA, Department of Statistics, North Carolina State University, Ricks Hall, 1 Lampe Dr., Raleigh, NC 27607, USA and Department of Statistics, National Cheng-Kung University, No.1, University Road, Tainan 701, Taiwan.', '-|-', 4, 'Breast Neoplasms|DNA Copy Number Variations|DNA Methylation|Female|Gene Expression Profiling|Genes|Genomics|Humans|Sequence Analysis, RNA|Statistics, Nonparametric', 'Journal Article', '10.1093/bioinformatics/btu060', '24489370', 'Gene set analysis is a popular method for large-scale genomic studies. Because genes that have common biological features are analyzed jointly, gene set analysis often achieves better power and generates more biologically informative results. With the advancement of technologies, genomic studies with multi-platform data have become increasingly common. Several strategies have been proposed that integrate genomic data from multiple platforms to perform gene set analysis. To evaluate the performances of existing integrative gene set methods under various scenarios, we conduct a comparative simulation analysis based on The Cancer Genome Atlas breast cancer dataset.'),
(78222, 2014, 'bio', 'StochHMM: a flexible hidden Markov model tool and C++ library', 'Lott, Paul C|Korf, Ian', 'Genome Center, One Shields Ave., University of California, Davis, CA 95616, USA.|Genome Center, One Shields Ave., University of California, Davis, CA 95616, USA.', 'United States|United States', 8, 'Algorithms|Markov Chains|Models, Statistical|Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btu057', '24489371', 'Hidden Markov models (HMMs) are probabilistic models that are well-suited to solve many different classification problems in computation biology. StochHMM provides a command-line program and C++ library that can implement a traditional HMM from a simple text file. StochHMM provides researchers the flexibility to create higher-order emissions, integrate additional data sources and/or user-defined functions into multiple points within the HMM framework. Additional features include user-defined alphabets, ability to handle ambiguous characters in an emission-dependent manner, user-defined weighting of state paths and ability to tie transition probabilities to sequence.'),
(78223, 2014, 'bio', 'Adaption of the global test idea to proteomics data with missing values', 'Jung, Klaus|Dihazi, Hassan|Bibi, Asima|Dihazi, Gry H|Beißbarth, Tim', 'Department of Medical Statistics, and Department of Nephrology and Rheumatology, University Medical Center Göttingen, Göttingen 37099, Germany.|Department of Medical Statistics, and Department of Nephrology and Rheumatology, University Medical Center Göttingen, Göttingen 37099, Germany.|Department of Medical Statistics, and Department of Nephrology and Rheumatology, University Medical Center Göttingen, Göttingen 37099, Germany.|Department of Medical Statistics, and Department of Nephrology and Rheumatology, University Medical Center Göttingen, Göttingen 37099, Germany.|Department of Medical Statistics, and Department of Nephrology and Rheumatology, University Medical Center Göttingen, Göttingen 37099, Germany.', 'Germany|Germany|Germany|Germany|Germany', 7, 'Algorithms|Animals|Electrophoresis, Gel, Two-Dimensional|Linear Models|Mice|Myocardium|Proteome|Proteomics', 'Journal Article', '10.1093/bioinformatics/btu062', '24489372', 'Global test procedures are frequently used in gene expression analysis to study the relationship between a functional subset of RNA transcripts and an experimental group factor. However, these procedures have been rarely used for the analysis of high-throughput data from other sources, such as proteome expression data. The main difficulties in transferring global test procedures from genomics to proteomics data are the more complicated way of obtaining functional annotations and the handling of missing values in some types of proteomics data.'),
(78224, 2014, 'bio', 'CoNtRol: an open source framework for the analysis of chemical reaction networks', 'Donnell, Pete|Banaji, Murad|Marginean, Anca|Pantea, Casian', 'Department of Mathematics, University of Portsmouth, Portsmouth PO1 3HF, UK, Computer Science Department, Technical University of Cluj-Napoca, 400027 Cluj-Napoca, Romania and Department of Mathematics, West Virginia University, Morgantown, WV 26506-6310, USA.|Department of Mathematics, University of Portsmouth, Portsmouth PO1 3HF, UK, Computer Science Department, Technical University of Cluj-Napoca, 400027 Cluj-Napoca, Romania and Department of Mathematics, West Virginia University, Morgantown, WV 26506-6310, USA.|Department of Mathematics, University of Portsmouth, Portsmouth PO1 3HF, UK, Computer Science Department, Technical University of Cluj-Napoca, 400027 Cluj-Napoca, Romania and Department of Mathematics, West Virginia University, Morgantown, WV 26506-6310, USA.|Department of Mathematics, University of Portsmouth, Portsmouth PO1 3HF, UK, Computer Science Department, Technical University of Cluj-Napoca, 400027 Cluj-Napoca, Romania and Department of Mathematics, West Virginia University, Morgantown, WV 26506-6310, USA.', 'Romania|Romania|Romania|Romania', 17, 'Internet|Models, Chemical|Software', 'Journal Article', '10.1093/bioinformatics/btu063', '24489373', 'We introduce CoNtRol, a web-based framework for analysis of chemical reaction networks (CRNs). It is designed to be both extensible and simple to use, complementing existing CRN-related tools. CoNtRol currently implements a number of necessary and/or sufficient structural tests for multiple equilibria, stable periodic orbits, convergence to equilibria and persistence, with the potential for incorporation of further tests.'),
(78225, 2014, 'bio', 'The cleverSuite approach for protein characterization: predictions of structural properties, solubility, chaperone requirements and RNA-binding abilities', 'Klus, Petr|Bolognesi, Benedetta|Agostini, Federico|Marchese, Domenica|Zanzoni, Andreas|Tartaglia, Gian Gaetano', 'Gene Function and Evolution, Centre for Genomic Regulation (CRG), Dr. Aiguader 88 and Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain.|Gene Function and Evolution, Centre for Genomic Regulation (CRG), Dr. Aiguader 88 and Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain.|Gene Function and Evolution, Centre for Genomic Regulation (CRG), Dr. Aiguader 88 and Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain.|Gene Function and Evolution, Centre for Genomic Regulation (CRG), Dr. Aiguader 88 and Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain.|Gene Function and Evolution, Centre for Genomic Regulation (CRG), Dr. Aiguader 88 and Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain.|Gene Function and Evolution, Centre for Genomic Regulation (CRG), Dr. Aiguader 88 and Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain', 21, 'Algorithms|Intrinsically Disordered Proteins|Molecular Chaperones|Protein Structure, Secondary|Proteins|RNA-Binding Proteins|Sequence Analysis, Protein|Software|Solubility', 'Journal Article', '10.1093/bioinformatics/btu074', '24493033', 'The recent shift towards high-throughput screening is posing new challenges for the interpretation of experimental results. Here we propose the cleverSuite approach for large-scale characterization of protein groups.'),
(78226, 2014, 'bio', 'SegAnnDB: interactive Web-based genomic segmentation', 'Hocking, Toby D|Boeva, Valentina|Rigaill, Guillem|Schleiermacher, Gudrun|Janoueix-Lerosey, Isabelle|Delattre, Olivier|Richer, Wilfrid|Bourdeaut, Franck|Suguro, Miyuki|Seto, Masao|Bach, Francis|Vert, Jean-Philippe', 'Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, France.|Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, FranceDepartment of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, FranceDepartment of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, France.|Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, France.|Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, FranceDepartment of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, France.|Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, FranceDepartment of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, France.|Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, FranceDepartment of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, France.|Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, France.|Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, France.|Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, France.|Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, France.|Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, France.|Department of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, FranceDepartment of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, FranceDepartment of Computer Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Unité de Recherche en Génomique Végétale INRA-CNRS-Université dEvry Val dEssonne, Évry 91057, France, INSERM U830, Paris F-75248, France, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya-city 464-8681, Japan and INRIA-Sierra Project-Team, Département dInformatique de lÉcole Normale Supérieure, Paris F-75013, France.', 'France|France|France|France|France|France|France|France|France|France|France|France', 9, 'Algorithms|Chromosome Breakpoints|DNA Copy Number Variations|Genomics|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btu072', '24493034', 'DNA copy number profiles characterize regions of chromosome gains, losses and breakpoints in tumor genomes. Although many models have been proposed to detect these alterations, it is not clear which model is appropriate before visual inspection the signal, noise and models for a particular profile.'),
(78227, 2014, 'bio', 'ARTS: automated randomization of multiple traits for study design', 'Maienschein-Cline, Mark|Lei, Zhengdeng|Gardeux, Vincent|Abbasi, Taimur|Machado, Roberto F|Gordeuk, Victor|Desai, Ankit A|Saraf, Santosh|Bahroos, Neil|Lussier, Yves', 'Center for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USA.|Center for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USA.|Center for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USACenter for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USACenter for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USA.|Center for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USA.|Center for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USA.|Center for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USA.|Center for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USA.|Center for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USA.|Center for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USA.|Center for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USACenter for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USACenter for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USACenter for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USACenter for Research Informatics, Institute for Interventional Health Informatics, Department of Medicine, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, Computation Institute of The University of Chicago, Chicago and Argonne National Laboratory, The University of Chicago, Lemont, IL, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 2, 'Algorithms|Female|High-Throughput Nucleotide Sequencing|Humans|Male|Microarray Analysis|Middle Aged|Random Allocation|Software', 'Journal Article', '10.1093/bioinformatics/btu075', '24493035', 'Collecting data from large studies on high-throughput platforms, such as microarray or next-generation sequencing, typically requires processing samples in batches. There are often systematic but unpredictable biases from batch-to-batch, so proper randomization of biologically relevant traits across batches is crucial for distinguishing true biological differences from experimental artifacts. When a large number of traits are biologically relevant, as is common for clinical studies of patients with varying sex, age, genotype and medical background, proper randomization can be extremely difficult to prepare by hand, especially because traits may affect biological inferences, such as differential expression, in a combinatorial manner. Here we present ARTS (automated randomization of multiple traits for study design), which aids researchers in study design by automatically optimizing batch assignment for any number of samples, any number of traits and any batch size.'),
(78228, 2014, 'bio', 'Complete enumeration of elementary flux modes through scalable demand-based subnetwork definition', 'Hunt, Kristopher A|Folsom, James P|Taffs, Reed L|Carlson, Ross P', 'Center for Biofilm Engineering, Montana State University, Bozeman, MT 59717-3980 and Department of Chemical and Biological Engineering, Montana State University, Bozeman, MT 59717-3920, USACenter for Biofilm Engineering, Montana State University, Bozeman, MT 59717-3980 and Department of Chemical and Biological Engineering, Montana State University, Bozeman, MT 59717-3920, USA.|Center for Biofilm Engineering, Montana State University, Bozeman, MT 59717-3980 and Department of Chemical and Biological Engineering, Montana State University, Bozeman, MT 59717-3920, USACenter for Biofilm Engineering, Montana State University, Bozeman, MT 59717-3980 and Department of Chemical and Biological Engineering, Montana State University, Bozeman, MT 59717-3920, USA.|Center for Biofilm Engineering, Montana State University, Bozeman, MT 59717-3980 and Department of Chemical and Biological Engineering, Montana State University, Bozeman, MT 59717-3920, USACenter for Biofilm Engineering, Montana State University, Bozeman, MT 59717-3980 and Department of Chemical and Biological Engineering, Montana State University, Bozeman, MT 59717-3920, USA.|Center for Biofilm Engineering, Montana State University, Bozeman, MT 59717-3980 and Department of Chemical and Biological Engineering, Montana State University, Bozeman, MT 59717-3920, USACenter for Biofilm Engineering, Montana State University, Bozeman, MT 59717-3980 and Department of Chemical and Biological Engineering, Montana State University, Bozeman, MT 59717-3920, USA.', 'United States|United States|United States|United States', 30, 'Algorithms|Diatoms|Genomics|Metabolic Networks and Pathways|Models, Biological|Software', 'Journal Article', '10.1093/bioinformatics/btu021', '24497502', 'Elementary flux mode analysis (EFMA) decomposes complex metabolic network models into tractable biochemical pathways, which have been used for rational design and analysis of metabolic and regulatory networks. However, application of EFMA has often been limited to targeted or simplified metabolic network representations due to computational demands of the method.'),
(78229, 2014, 'bio', 'AMASS: a database for investigating protein structures', 'Mielke, Clinton J|Mandarino, Lawrence J|Dinu, Valentin', 'Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA, The Center for Metabolic and Vascular Biology, Mayo Clinic, Scottsdale, AZ 85259, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USABiodesign Institute, Arizona State University, Tempe, AZ 85287, USA, The Center for Metabolic and Vascular Biology, Mayo Clinic, Scottsdale, AZ 85259, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USABiodesign Institute, Arizona State University, Tempe, AZ 85287, USA, The Center for Metabolic and Vascular Biology, Mayo Clinic, Scottsdale, AZ 85259, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA.|Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA, The Center for Metabolic and Vascular Biology, Mayo Clinic, Scottsdale, AZ 85259, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA.|Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA, The Center for Metabolic and Vascular Biology, Mayo Clinic, Scottsdale, AZ 85259, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA.', 'United States|United States|United States', 3, 'Databases, Protein|Humans|Internet|Mass Spectrometry|Mitochondrial Proton-Translocating ATPases|Molecular Sequence Annotation|Protein Conformation|Protein Processing, Post-Translational|Proteins|Pyruvate Dehydrogenase Complex|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btu073', '24497503', 'Modern techniques have produced many sequence annotation databases and protein structure portals, but these Web resources are rarely integrated in ways that permit straightforward exploration of protein functional residues and their co-localization.'),
(78230, 2014, 'bio', 'Visualization and probability-based scoring of structural variants within repetitive sequences', 'Halper-Stromberg, Eitan|Steranka, Jared|Burns, Kathleen H|Sabunciyan, Sarven|Irizarry, Rafael A', 'Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Department of Pathology, Johns Hopkins University, High Throughput Biology Center, Johns Hopkins University School of Medicine, Johns Hopkins University, Center for Epigenetics, Johns Hopkins University School of Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD and Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, MA, USADepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Department of Pathology, Johns Hopkins University, High Throughput Biology Center, Johns Hopkins University School of Medicine, Johns Hopkins University, Center for Epigenetics, Johns Hopkins University School of Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD and Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, MA, USADepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Cente|Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Department of Pathology, Johns Hopkins University, High Throughput Biology Center, Johns Hopkins University School of Medicine, Johns Hopkins University, Center for Epigenetics, Johns Hopkins University School of Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD and Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, MA, USA.|Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Department of Pathology, Johns Hopkins University, High Throughput Biology Center, Johns Hopkins University School of Medicine, Johns Hopkins University, Center for Epigenetics, Johns Hopkins University School of Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD and Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, MA, USADepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Department of Pathology, Johns Hopkins University, High Throughput Biology Center, Johns Hopkins University School of Medicine, Johns Hopkins University, Center for Epigenetics, Johns Hopkins University School of Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD and Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, MA, USADepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Cente|Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Department of Pathology, Johns Hopkins University, High Throughput Biology Center, Johns Hopkins University School of Medicine, Johns Hopkins University, Center for Epigenetics, Johns Hopkins University School of Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD and Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, MA, USADepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Department of Pathology, Johns Hopkins University, High Throughput Biology Center, Johns Hopkins University School of Medicine, Johns Hopkins University, Center for Epigenetics, Johns Hopkins University School of Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD and Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, MA, USA.|Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Department of Pathology, Johns Hopkins University, High Throughput Biology Center, Johns Hopkins University School of Medicine, Johns Hopkins University, Center for Epigenetics, Johns Hopkins University School of Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD and Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, MA, USADepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Department of Pathology, Johns Hopkins University, High Throughput Biology Center, Johns Hopkins University School of Medicine, Johns Hopkins University, Center for Epigenetics, Johns Hopkins University School of Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD and Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, MA, USA.', 'United States|United States|United States|United States|United States', 3, 'Cell Line, Transformed|Cell Line, Tumor|DNA|Genome, Human|Genomic Structural Variation|Genomics|High-Throughput Nucleotide Sequencing|Humans|Probability|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu054', '24501098', 'Repetitive sequences account for approximately half of the human genome. Accurately ascertaining sequences in these regions with next generation sequencers is challenging, and requires a different set of analytical techniques than for reads originating from unique sequences. Complicating the matter are repetitive regions subject to programmed rearrangements, as is the case with the antigen-binding domains in the Immunoglobulin (Ig) and T-cell receptor (TCR) loci.'),
(78231, 2014, 'bio', 'Learning phenotype densities conditional on many interacting predictors', 'Kessler, David C|Taylor, Jack A|Dunson, David B', 'Advanced Analytics Division, SAS Institute Inc., Cary, NC 27513, Molecular and Genetic Epidemiology Section, Epidemiology Branch and Laboratory of Molecular Carcinogenesis, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709 and Department of Statistical Science, Duke University, Durham, NC 27708.|Advanced Analytics Division, SAS Institute Inc., Cary, NC 27513, Molecular and Genetic Epidemiology Section, Epidemiology Branch and Laboratory of Molecular Carcinogenesis, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709 and Department of Statistical Science, Duke University, Durham, NC 27708.|Advanced Analytics Division, SAS Institute Inc., Cary, NC 27513, Molecular and Genetic Epidemiology Section, Epidemiology Branch and Laboratory of Molecular Carcinogenesis, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709 and Department of Statistical Science, Duke University, Durham, NC 27708.', '-|-|-', 3, 'Algorithms|Bayes Theorem|Humans|Phenotype|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btu040', '24501099', 'Estimating a phenotype distribution conditional on a set of discrete-valued predictors is a commonly encountered task. For example, interest may be in how the density of a quantitative trait varies with single nucleotide polymorphisms and patient characteristics. The subset of important predictors is not usually known in advance. This becomes more challenging with a high-dimensional predictor set when there is the possibility of interaction.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78232, 2014, 'bio', 'iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition', 'Guo, Shou-Hui|Deng, En-Ze|Xu, Li-Qin|Ding, Hui|Lin, Hao|Chen, Wei|Chou, Kuo-Chen', 'Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China, Gordon Life Science Institute, Belmont, Massachusetts, USA, Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia.|Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China, Gordon Life Science Institute, Belmont, Massachusetts, USA, Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia.|Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China, Gordon Life Science Institute, Belmont, Massachusetts, USA, Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia.|Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China, Gordon Life Science Institute, Belmont, Massachusetts, USA, Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia.|Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China, Gordon Life Science Institute, Belmont, Massachusetts, USA, Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi ArabiaKey Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China, Gordon Life Science Institute, Belmont, Massachusetts, USA, Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia.|Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China, Gordon Life Science Institute, Belmont, Massachusetts, USA, Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi ArabiaKey Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China, Gordon Life Science Institute, Belmont, Massachusetts, USA, Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia.|Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China, Gordon Life Science Institute, Belmont, Massachusetts, USA, Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi ArabiaKey Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China, Gordon Life Science Institute, Belmont, Massachusetts, USA, Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China and Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia.', 'China|China|China|China|China|China|China', 305, 'Animals|Caenorhabditis elegans|DNA|Drosophila melanogaster|Genome|Genomics|Humans|Nucleosomes|Nucleotides|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu083', '24504871', 'Nucleosome positioning participates in many cellular activities and plays significant roles in regulating cellular processes. With the avalanche of genome sequences generated in the post-genomic age, it is highly desired to develop automated methods for rapidly and effectively identifying nucleosome positioning. Although some computational methods were proposed, most of them were species specific and neglected the intrinsic local structural properties that might play important roles in determining the nucleosome positioning on a DNA sequence.'),
(78233, 2014, 'bio', 'HiBrowse: multi-purpose statistical analysis of genome-wide chromatin 3D organization', 'Paulsen, Jonas|Sandve, Geir Kjetil|Gundersen, Sveinung|Lien, Tonje G|Trengereid, Kai|Hovig, Eivind', 'Institute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Norway.|Institute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Norway.|Institute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Norway.|Institute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Norway.|Institute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Norway.|Institute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, NorwayInstitute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, NorwayInstitute for Cancer Genetics and Informatics, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, PO Box 4950, Nydalen, 0424 Oslo, Department of Mathematics, University of Oslo, Problemveien 7, 0313 Oslo and ELIXIR project, Department of Informatics, University of Oslo, Problemveien 7, 0313 Oslo, Norway.', 'Norway|Norway|Norway|Norway|Norway|Norway', 0, 'Chromatin|Data Interpretation, Statistical|Genome|Genomics|High-Throughput Nucleotide Sequencing|Software', 'Journal Article', '10.1093/bioinformatics/btu082', '24511080', 'Recently developed methods that couple next-generation sequencing with chromosome conformation capture-based techniques, such as Hi-C and ChIA-PET, allow for characterization of genome-wide chromatin 3D structure. Understanding the organization of chromatin in three dimensions is a crucial next step in the unraveling of global gene regulation, and methods for analyzing such data are needed. We have developed HiBrowse, a user-friendly web-tool consisting of a range of hypothesis-based and descriptive statistics, using realistic assumptions in null-models.'),
(78234, 2014, 'bio', 'SurvMicro: assessment of miRNA-based prognostic signatures for cancer clinical outcomes by multivariate survival analysis', 'Aguirre-Gamboa, Raul|Trevino, Victor', 'Departamento de Investigación e Innovación, Escuela de Medicina, Tecnológico de Monterrey, 64849 México.|Departamento de Investigación e Innovación, Escuela de Medicina, Tecnológico de Monterrey, 64849 México.', '-|-', 35, 'Biomarkers, Tumor|Gene Expression Profiling|Humans|Liver Neoplasms|Lung Neoplasms|MicroRNAs|Multivariate Analysis|Neoplasms|Prognosis|Software|Survival Analysis', 'Journal Article', '10.1093/bioinformatics/btu087', '24519378', 'MicroRNAs (miRNAs) play a key role in post-transcriptional regulation of mRNA levels. Their function in cancer has been studied by high-throughput methods generating valuable sources of public information. Thus, miRNA signatures predicting cancer clinical outcomes are emerging. An important step to propose miRNA-based biomarkers before clinical validation is their evaluation in independent cohorts. Although it can be carried out using public data, such task is time-consuming and requires a specialized analysis. Therefore, to aid and simplify the evaluation of prognostic miRNA signatures in cancer, we developed SurvMicro, a free and easy-to-use web tool that assesses miRNA signatures from publicly available miRNA profiles using multivariate survival analysis. SurvMicro is composed of a wide and updated database of >40 cohorts in different tissues and a web tool where survival analysis can be done in minutes. We presented evaluations to portray the straightforward functionality of SurvMicro in liver and lung cancer. To our knowledge, SurvMicro is the only bioinformatic tool that aids the evaluation of multivariate prognostic miRNA signatures in cancer.'),
(78235, 2014, 'bio', 'Analysis of gene expression data using a linear mixed model/finite mixture model approach: application to regional differences in the human brain', 'Trabzuni, Daniah|United Kingdom Brain Expression Consortium (UKBEC)|Thomson, Peter C', 'Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK, Department of Genetics, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia and ReproGen - Animal Bioscience Group, Faculty of Veterinary Science, The University of Sydney, 425 Werombi Road, Camden, NSW 2570, AustraliaDepartment of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK, Department of Genetics, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia and ReproGen - Animal Bioscience Group, Faculty of Veterinary Science, The University of Sydney, 425 Werombi Road, Camden, NSW 2570, Australia.|Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK, Department of Genetics, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia and ReproGen - Animal Bioscience Group, Faculty of Veterinary Science, The University of Sydney, 425 Werombi Road, Camden, NSW 2570, AustraliaDepartment of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK, Department of Genetics, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia and ReproGen - Animal Bioscience Group, Faculty of Veterinary Science, The University of Sydney, 425 Werombi Road, Camden, NSW 2570, Australia.|Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK, Department of Genetics, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia and ReproGen - Animal Bioscience Group, Faculty of Veterinary Science, The University of Sydney, 425 Werombi Road, Camden, NSW 2570, Australia.', 'Australia|Australia|Australia', 11, 'Brain|Female|Gene Expression Profiling|Genome, Human|Humans|Linear Models|Male', 'Journal Article', '10.1093/bioinformatics/btu088', '24519379', 'Gene expression data exhibit common information over the genome. This article shows how data can be analysed from an efficient whole-genome perspective. Further, the methods have been developed so that users with limited expertise in bioinformatics and statistical computing techniques could use and modify this procedure to their own needs. The method outlined first uses a large-scale linear mixed model for the expression data genome-wide, and then uses finite mixture models to separate differentially expressed (DE) from non-DE transcripts. These methods are illustrated through application to an exceptional UK Brain Expression Consortium involving 12 human frozen post-mortem brain regions.'),
(78236, 2014, 'bio', 'An efficient algorithm for accurate computation of the Dirichlet-multinomial log-likelihood function', 'Yu, Peng|Shaw, Chad A', 'Department of Electrical and Computer Engineering & TEES-AgriLife Center for Bioinformatics and Genomic Systems Engineering (CBGSE), Texas A&M University, College Station, TX 77843, USA and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.|Department of Electrical and Computer Engineering & TEES-AgriLife Center for Bioinformatics and Genomic Systems Engineering (CBGSE), Texas A&M University, College Station, TX 77843, USA and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.', 'United States|United States', 13, 'Algorithms|Humans|Likelihood Functions|Metagenomics|Microbiota', 'Journal Article', '10.1093/bioinformatics/btu079', '24519380', 'The Dirichlet-multinomial (DMN) distribution is a fundamental model for multicategory count data with overdispersion. This distribution has many uses in bioinformatics including applications to metagenomics data, transctriptomics and alternative splicing. The DMN distribution reduces to the multinomial distribution when the overdispersion parameter xcfx88 is 0. Unfortunately, numerical computation of the DMN log-likelihood function by conventional methods results in instability in the neighborhood of [Formula: see text]. An alternative formulation circumvents this instability, but it leads to long runtimes that make it impractical for large count data common in bioinformatics. We have developed a new method for computation of the DMN log-likelihood to solve the instability problem without incurring long runtimes. The new approach is composed of a novel formula and an algorithm to extend its applicability. Our numerical experiments show that this new method both improves the accuracy of log-likelihood evaluation and the runtime by several orders of magnitude, especially in high-count data situations that are common in deep sequencing data. Using real metagenomic data, our method achieves manyfold runtime improvement. Our method increases the feasibility of using the DMN distribution to model many high-throughput problems in bioinformatics. We have included in our work an R package giving access to this method and a vingette applying this approach to metagenomic data.'),
(78237, 2014, 'bio', 'Identifying critical transitions of complex diseases based on a single sample', 'Liu, Rui|Yu, Xiangtian|Liu, Xiaoping|Xu, Dong|Aihara, Kazuyuki|Chen, Luonan', 'School of Mathematics, South China University of Technology, Guangzhou 510640, China, Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, School of Mathematics, Shandong University, Jinan 250100, China, Collaborative Research Center for Innovative Mathematical Modelling, Institute of Industrial Science, University of Tokyo, Tokyo 153-8505, Japan and Department of Computer Science and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA.|School of Mathematics, South China University of Technology, Guangzhou 510640, China, Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, School of Mathematics, Shandong University, Jinan 250100, China, Collaborative Research Center for Innovative Mathematical Modelling, Institute of Industrial Science, University of Tokyo, Tokyo 153-8505, Japan and Department of Computer Science and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USASchool of Mathematics, South China University of Technology, Guangzhou 510640, China, Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, School of Mathematics, Shandong University, Jinan 250100, China, Collaborative Research Center for Innovative Mathematical Modelling, Institute of Industrial Science, University of Tokyo, Tokyo 153-8505, Japan and Department of Computer Science and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA.|School of Mathematics, South China University of Technology, Guangzhou 510640, China, Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, School of Mathematics, Shandong University, Jinan 250100, China, Collaborative Research Center for Innovative Mathematical Modelling, Institute of Industrial Science, University of Tokyo, Tokyo 153-8505, Japan and Department of Computer Science and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA.|School of Mathematics, South China University of Technology, Guangzhou 510640, China, Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, School of Mathematics, Shandong University, Jinan 250100, China, Collaborative Research Center for Innovative Mathematical Modelling, Institute of Industrial Science, University of Tokyo, Tokyo 153-8505, Japan and Department of Computer Science and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA.|School of Mathematics, South China University of Technology, Guangzhou 510640, China, Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, School of Mathematics, Shandong University, Jinan 250100, China, Collaborative Research Center for Innovative Mathematical Modelling, Institute of Industrial Science, University of Tokyo, Tokyo 153-8505, Japan and Department of Computer Science and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA.|School of Mathematics, South China University of Technology, Guangzhou 510640, China, Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, School of Mathematics, Shandong University, Jinan 250100, China, Collaborative Research Center for Innovative Mathematical Modelling, Institute of Industrial Science, University of Tokyo, Tokyo 153-8505, Japan and Department of Computer Science and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USASchool of Mathematics, South China University of Technology, Guangzhou 510640, China, Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, School of Mathematics, Shandong University, Jinan 250100, China, Collaborative Research Center for Innovative Mathematical Modelling, Institute of Industrial Science, University of Tokyo, Tokyo 153-8505, Japan and Department of Computer Science and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA.', 'China|China|China|China|China|China', 54, 'Acute Lung Injury|Algorithms|Animals|Asymptomatic Diseases|Biomarkers|Breast Neoplasms|Disease Progression|Female|Humans|Influenza, Human|Rats', 'Journal Article', '10.1093/bioinformatics/btu084', '24519381', 'Unlike traditional diagnosis of an existing disease state, detecting the pre-disease state just before the serious deterioration of a disease is a challenging task, because the state of the system may show little apparent change or symptoms before this critical transition during disease progression. By exploring the rich interaction information provided by high-throughput data, the dynamical network biomarker (DNB) can identify the pre-disease state, but this requires multiple samples to reach a correct diagnosis for one individual, thereby restricting its clinical application.'),
(78238, 2014, 'bio', 'Unraveling the outcome of 16S rDNA-based taxonomy analysis through mock data and simulations', 'May, Ali|Abeln, Sanne|Crielaard, Wim|Heringa, Jaap|Brandt, Bernd W', 'Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and VU University Amsterdam, Amsterdam, The Netherlands, Centre for Integrative Bioinformatics VU and AIMMS Amsterdam Institute for Molecules Medicines and Systems, VU University Amsterdam, Amsterdam, The Netherlands and NBIC Netherlands Bioinformatics Centre, Nijmegen, The NetherlandsDepartment of Preventive Dentistry, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and VU University Amsterdam, Amsterdam, The Netherlands, Centre for Integrative Bioinformatics VU and AIMMS Amsterdam Institute for Molecules Medicines and Systems, VU University Amsterdam, Amsterdam, The Netherlands and NBIC Netherlands Bioinformatics Centre, Nijmegen, The Netherlands.|Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and VU University Amsterdam, Amsterdam, The Netherlands, Centre for Integrative Bioinformatics VU and AIMMS Amsterdam Institute for Molecules Medicines and Systems, VU University Amsterdam, Amsterdam, The Netherlands and NBIC Netherlands Bioinformatics Centre, Nijmegen, The NetherlandsDepartment of Preventive Dentistry, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and VU University Amsterdam, Amsterdam, The Netherlands, Centre for Integrative Bioinformatics VU and AIMMS Amsterdam Institute for Molecules Medicines and Systems, VU University Amsterdam, Amsterdam, The Netherlands and NBIC Netherlands Bioinformatics Centre, Nijmegen, The Netherlands.|Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and VU University Amsterdam, Amsterdam, The Netherlands, Centre for Integrative Bioinformatics VU and AIMMS Amsterdam Institute for Molecules Medicines and Systems, VU University Amsterdam, Amsterdam, The Netherlands and NBIC Netherlands Bioinformatics Centre, Nijmegen, The Netherlands.|Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and VU University Amsterdam, Amsterdam, The Netherlands, Centre for Integrative Bioinformatics VU and AIMMS Amsterdam Institute for Molecules Medicines and Systems, VU University Amsterdam, Amsterdam, The Netherlands and NBIC Netherlands Bioinformatics Centre, Nijmegen, The NetherlandsDepartment of Preventive Dentistry, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and VU University Amsterdam, Amsterdam, The Netherlands, Centre for Integrative Bioinformatics VU and AIMMS Amsterdam Institute for Molecules Medicines and Systems, VU University Amsterdam, Amsterdam, The Netherlands and NBIC Netherlands Bioinformatics Centre, Nijmegen, The NetherlandsDepartment of Preventive Dentistry, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and VU University Amsterdam, Amsterdam, The Netherlands, Centre for Integrative Bioinformatics VU and AIMMS Amsterdam Institute for Molecules Medicines and Systems, VU University Amsterdam, Amsterdam, The Netherlands and NBIC Netherlands Bioinformatics Centre, Nijmegen, The Netherlands.|Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and VU University Amsterdam, Amsterdam, The Netherlands, Centre for Integrative Bioinformatics VU and AIMMS Amsterdam Institute for Molecules Medicines and Systems, VU University Amsterdam, Amsterdam, The Netherlands and NBIC Netherlands Bioinformatics Centre, Nijmegen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 23, 'Algorithms|Classification|Cluster Analysis|Computer Simulation|DNA, Ribosomal|Microbiota|Phylogeny|RNA, Ribosomal, 16S|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu085', '24519382', '16S rDNA pyrosequencing is a powerful approach that requires extensive usage of computational methods for delineating microbial compositions. Previously, it was shown that outcomes of studies relying on this approach vastly depend on the choice of pre-processing and clustering algorithms used. However, obtaining insights into the effects and accuracy of these algorithms is challenging due to difficulties in generating samples of known composition with high enough diversity. Here, we use in silico microbial datasets to better understand how the experimental data are transformed into taxonomic clusters by computational methods.'),
(78239, 2014, 'bio', 'HUM calculator and HUM package for R: easy-to-use software tools for multicategory receiver operating characteristic analysis', 'Novoselova, Natalia|Della Beffa, Cristina|Wang, Junxi|Li, Jialiang|Pessler, Frank|Klawonn, Frank', 'Laboratory of Bioinformatics, United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganova 6, 220012 Minsk, Belarus, Bioinformatics and Statistics, Helmholtz Centre for Infection Research, Braunschweig, Germany, Department of Statistics and Applied Probability, National University of Singapore, Singapore, TWINCORE Center for Experimental and Clinical Infection Research, Hannover and Department of Computer Science, Ostfalia University of Applied Sciences, Wolfenbxc3xbcttel, GermanyLaboratory of Bioinformatics, United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganova 6, 220012 Minsk, Belarus, Bioinformatics and Statistics, Helmholtz Centre for Infection Research, Braunschweig, Germany, Department of Statistics and Applied Probability, National University of Singapore, Singapore, TWINCORE Center for Experimental and Clinical Infection Research, Hannover and Department of Computer Science, Ostfalia University of Applied Sciences, Wolfenbxc3xbcttel, Germany.|Laboratory of Bioinformatics, United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganova 6, 220012 Minsk, Belarus, Bioinformatics and Statistics, Helmholtz Centre for Infection Research, Braunschweig, Germany, Department of Statistics and Applied Probability, National University of Singapore, Singapore, TWINCORE Center for Experimental and Clinical Infection Research, Hannover and Department of Computer Science, Ostfalia University of Applied Sciences, Wolfenbxc3xbcttel, Germany.|Laboratory of Bioinformatics, United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganova 6, 220012 Minsk, Belarus, Bioinformatics and Statistics, Helmholtz Centre for Infection Research, Braunschweig, Germany, Department of Statistics and Applied Probability, National University of Singapore, Singapore, TWINCORE Center for Experimental and Clinical Infection Research, Hannover and Department of Computer Science, Ostfalia University of Applied Sciences, Wolfenbxc3xbcttel, Germany.|Laboratory of Bioinformatics, United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganova 6, 220012 Minsk, Belarus, Bioinformatics and Statistics, Helmholtz Centre for Infection Research, Braunschweig, Germany, Department of Statistics and Applied Probability, National University of Singapore, Singapore, TWINCORE Center for Experimental and Clinical Infection Research, Hannover and Department of Computer Science, Ostfalia University of Applied Sciences, Wolfenbxc3xbcttel, Germany.|Laboratory of Bioinformatics, United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganova 6, 220012 Minsk, Belarus, Bioinformatics and Statistics, Helmholtz Centre for Infection Research, Braunschweig, Germany, Department of Statistics and Applied Probability, National University of Singapore, Singapore, TWINCORE Center for Experimental and Clinical Infection Research, Hannover and Department of Computer Science, Ostfalia University of Applied Sciences, Wolfenbxc3xbcttel, Germany.|Laboratory of Bioinformatics, United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganova 6, 220012 Minsk, Belarus, Bioinformatics and Statistics, Helmholtz Centre for Infection Research, Braunschweig, Germany, Department of Statistics and Applied Probability, National University of Singapore, Singapore, TWINCORE Center for Experimental and Clinical Infection Research, Hannover and Department of Computer Science, Ostfalia University of Applied Sciences, Wolfenbxc3xbcttel, GermanyLaboratory of Bioinformatics, United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganova 6, 220012 Minsk, Belarus, Bioinformatics and Statistics, Helmholtz Centre for Infection Research, Braunschweig, Germany, Department of Statistics and Applied Probability, National University of Singapore, Singapore, TWINCORE Center for Experimental and Clinical Infection Research, Hannover and Department of Computer Science, Ostfalia University of Applied Sciences, Wolfenbxc3xbcttel, Germany.', 'Belarus|Belarus|Belarus|Belarus|Belarus|Belarus', 14, 'Internet|ROC Curve|Software', 'Journal Article', '10.1093/bioinformatics/btu086', '24519383', 'Receiver operating characteristic (ROC) analysis is usually applied in bioinformatics to evaluate the abilities of biological markers to differentiate between the presence or absence of a disease. It includes the derivation of the useful scalar performance measure area under the ROC curve for binary classification tasks. As real applications often deal with more than two classes, multicategory ROC analysis and the corresponding hypervolume under the manifold (HUM) measure have become a topic of growing interest. To support researchers in carrying out multicategory ROC analysis, we have developed two tools in different programming environments which feature user-friendly, object-oriented and flexible interfaces and enable the user to compute HUM values and plot 2D- and 3D-ROC curves.'),
(78240, 2014, 'bio', 'BIMA V3: an aligner customized for mate pair library sequencing', 'Drucker, Travis M|Johnson, Sarah H|Murphy, Stephen J|Cradic, Kendall W|Therneau, Terry M|Vasmatzis, George', 'Department of Information Technology, MN 55905, Department of Molecular Medicine, Department of Laboratory Medicine and Pathology and Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.|Department of Information Technology, MN 55905, Department of Molecular Medicine, Department of Laboratory Medicine and Pathology and Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.|Department of Information Technology, MN 55905, Department of Molecular Medicine, Department of Laboratory Medicine and Pathology and Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.|Department of Information Technology, MN 55905, Department of Molecular Medicine, Department of Laboratory Medicine and Pathology and Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.|Department of Information Technology, MN 55905, Department of Molecular Medicine, Department of Laboratory Medicine and Pathology and Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.|Department of Information Technology, MN 55905, Department of Molecular Medicine, Department of Laboratory Medicine and Pathology and Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.', 'United States|United States|United States|United States|United States|United States', 50, 'Algorithms|Gene Library|Genome|Genomic Structural Variation|High-Throughput Nucleotide Sequencing|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu078', '24526710', 'Mate pair library sequencing is an effective and economical method for detecting genomic structural variants and chromosomal abnormalities. Unfortunately, the mapping and alignment of mate-pair read pairs to a reference genome is a challenging and time-consuming process for most next-generation sequencing alignment programs. Large insert sizes, introduction of library preparation protocol artifacts (biotin junction reads, paired-end read contamination, chimeras, etc.) and presence of structural variant breakpoints within reads increase mapping and alignment complexity. We describe an algorithm that is up to 20 times faster and 25% more accurate than popular next-generation sequencing alignment programs when processing mate pair sequencing.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78241, 2014, 'bio', 'A benchmark for comparison of cell tracking algorithms', 'Maxc5xa1ka, Martin|Ulman, Vladimxc3xadr|Svoboda, David|Matula, Pavel|Matula, Petr|Ederra, Cristina|Urbiola, Ainhoa|Espaxc3xb1a, Tomxc3xa1s|Venkatesan, Subramanian|Balak, Deepak M W|Karas, Pavel|Bolckovxc3xa1, Tereza|Streitovxc3xa1, Markxc3xa9ta|Carthel, Craig|Coraluppi, Stefano|Harder, Nathalie|Rohr, Karl|Magnusson, Klas E G|Jaldxc3xa9n, Joakim|Blau, Helen M|Dzyubachyk, Oleh|Kxc5x99xc3xadxc5xbeek, Pavel|Hagen, Guy M|Pastor-Escuredo, David|Jimenez-Carretero, Daniel|Ledesma-Carbayo, Maria J|Muxc3xb1oz-Barrutia, Arrate|Meijering, Erik|Kozubek, Michal|Ortiz-de-Solorzano, Carlos', 'Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, SpainCenter for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and |Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.|Center for Biomedical Image Analysis, Masaryk University, 602 00 Brno, Czech Republic, Cancer Imaging Laboratory, Oncology Division, Center for Applied Medical Research, University of Navarra, 31008 Pamplona, Spain, Biomedical Imaging Group Rotterdam, Erasmus University Medical Center, 3015 GE Rotterdam, The Netherlands, Fusion Technology and Systems Department, Compunetix Inc., Monroeville, PA 15146, USA, Biomedical Computer Vision Group, Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB and DKFZ, 69120 Heidelberg, Germany, KTH Royal Institute of Technology, ACCESS Linnaeus Center, Department of Signal Processing, 100 44 Stockholm, Sweden, Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden, The Netherlands, Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, 12801 Prague 2, Czech Republic and Biomedical Image Technologies, Universidad Politxc3xa9cnica de Madrid & CIBER BBN, 28040 Madrid, Spain.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 203, 'Algorithms|Benchmarking|Cell Tracking|Microscopy, Fluorescence', 'Journal Article', '10.1093/bioinformatics/btu080', '24526711', 'Automatic tracking of cells in multidimensional time-lapse fluorescence microscopy is an important task in many biomedical applications. A novel framework for objective evaluation of cell tracking algorithms has been established under the auspices of the IEEE International Symposium on Biomedical Imaging 2013 Cell Tracking Challenge. In this article, we present the logistics, datasets, methods and results of the challenge and lay down the principles for future uses of this benchmark.'),
(78242, 2014, 'bio', 'Supercomputing for the parallelization of whole genome analysis', 'Puckelwartz, Megan J|Pesce, Lorenzo L|Nelakuditi, Viswateja|Dellefave-Castillo, Lisa|Golbus, Jessica R|Day, Sharlene M|Cappola, Thomas P|Dorn, Gerald W|Foster, Ian T|McNally, Elizabeth M', 'Department of Medicine, Computation Institute and Argonne National Laboratory, 9700 S. Cass Ave. Argonne, IL 60439, USA, Department of Human Genetics, The University of Chicago, 5841 S. Maryland Ave Chicago, IL 60637, USA, Department of Internal Medicine, The University of Michigan, 1150 W Medical Center Dr. Ann Arbor, MI 48109, USA, Perelman School of Medicine, Penn Cardiovascular Institute and Department of Medicine, University of Pennsylvania, 3400 Civic Center Blvd. Philadelphia, PA 19104, USA and Washington University School of Medicine, 660 S. Euclid Ave. St. Louis, MO 63110, USA.|Department of Medicine, Computation Institute and Argonne National Laboratory, 9700 S. Cass Ave. Argonne, IL 60439, USA, Department of Human Genetics, The University of Chicago, 5841 S. Maryland Ave Chicago, IL 60637, USA, Department of Internal Medicine, The University of Michigan, 1150 W Medical Center Dr. Ann Arbor, MI 48109, USA, Perelman School of Medicine, Penn Cardiovascular Institute and Department of Medicine, University of Pennsylvania, 3400 Civic Center Blvd. Philadelphia, PA 19104, USA and Washington University School of Medicine, 660 S. Euclid Ave. St. Louis, MO 63110, USA.|Department of Medicine, Computation Institute and Argonne National Laboratory, 9700 S. Cass Ave. Argonne, IL 60439, USA, Department of Human Genetics, The University of Chicago, 5841 S. Maryland Ave Chicago, IL 60637, USA, Department of Internal Medicine, The University of Michigan, 1150 W Medical Center Dr. Ann Arbor, MI 48109, USA, Perelman School of Medicine, Penn Cardiovascular Institute and Department of Medicine, University of Pennsylvania, 3400 Civic Center Blvd. Philadelphia, PA 19104, USA and Washington University School of Medicine, 660 S. Euclid Ave. St. Louis, MO 63110, USA.|Department of Medicine, Computation Institute and Argonne National Laboratory, 9700 S. Cass Ave. Argonne, IL 60439, USA, Department of Human Genetics, The University of Chicago, 5841 S. Maryland Ave Chicago, IL 60637, USA, Department of Internal Medicine, The University of Michigan, 1150 W Medical Center Dr. Ann Arbor, MI 48109, USA, Perelman School of Medicine, Penn Cardiovascular Institute and Department of Medicine, University of Pennsylvania, 3400 Civic Center Blvd. Philadelphia, PA 19104, USA and Washington University School of Medicine, 660 S. Euclid Ave. St. Louis, MO 63110, USA.|Department of Medicine, Computation Institute and Argonne National Laboratory, 9700 S. Cass Ave. Argonne, IL 60439, USA, Department of Human Genetics, The University of Chicago, 5841 S. Maryland Ave Chicago, IL 60637, USA, Department of Internal Medicine, The University of Michigan, 1150 W Medical Center Dr. Ann Arbor, MI 48109, USA, Perelman School of Medicine, Penn Cardiovascular Institute and Department of Medicine, University of Pennsylvania, 3400 Civic Center Blvd. Philadelphia, PA 19104, USA and Washington University School of Medicine, 660 S. Euclid Ave. St. Louis, MO 63110, USA.|Department of Medicine, Computation Institute and Argonne National Laboratory, 9700 S. Cass Ave. Argonne, IL 60439, USA, Department of Human Genetics, The University of Chicago, 5841 S. Maryland Ave Chicago, IL 60637, USA, Department of Internal Medicine, The University of Michigan, 1150 W Medical Center Dr. Ann Arbor, MI 48109, USA, Perelman School of Medicine, Penn Cardiovascular Institute and Department of Medicine, University of Pennsylvania, 3400 Civic Center Blvd. Philadelphia, PA 19104, USA and Washington University School of Medicine, 660 S. Euclid Ave. St. Louis, MO 63110, USA.|Department of Medicine, Computation Institute and Argonne National Laboratory, 9700 S. Cass Ave. Argonne, IL 60439, USA, Department of Human Genetics, The University of Chicago, 5841 S. Maryland Ave Chicago, IL 60637, USA, Department of Internal Medicine, The University of Michigan, 1150 W Medical Center Dr. Ann Arbor, MI 48109, USA, Perelman School of Medicine, Penn Cardiovascular Institute and Department of Medicine, University of Pennsylvania, 3400 Civic Center Blvd. Philadelphia, PA 19104, USA and Washington University School of Medicine, 660 S. Euclid Ave. St. Louis, MO 63110, USA.|Department of Medicine, Computation Institute and Argonne National Laboratory, 9700 S. Cass Ave. Argonne, IL 60439, USA, Department of Human Genetics, The University of Chicago, 5841 S. Maryland Ave Chicago, IL 60637, USA, Department of Internal Medicine, The University of Michigan, 1150 W Medical Center Dr. Ann Arbor, MI 48109, USA, Perelman School of Medicine, Penn Cardiovascular Institute and Department of Medicine, University of Pennsylvania, 3400 Civic Center Blvd. Philadelphia, PA 19104, USA and Washington University School of Medicine, 660 S. Euclid Ave. St. Louis, MO 63110, USA.|Department of Medicine, Computation Institute and Argonne National Laboratory, 9700 S. Cass Ave. Argonne, IL 60439, USA, Department of Human Genetics, The University of Chicago, 5841 S. Maryland Ave Chicago, IL 60637, USA, Department of Internal Medicine, The University of Michigan, 1150 W Medical Center Dr. Ann Arbor, MI 48109, USA, Perelman School of Medicine, Penn Cardiovascular Institute and Department of Medicine, University of Pennsylvania, 3400 Civic Center Blvd. Philadelphia, PA 19104, USA and Washington University School of Medicine, 660 S. Euclid Ave. St. Louis, MO 63110, USA.|Department of Medicine, Computation Institute and Argonne National Laboratory, 9700 S. Cass Ave. Argonne, IL 60439, USA, Department of Human Genetics, The University of Chicago, 5841 S. Maryland Ave Chicago, IL 60637, USA, Department of Internal Medicine, The University of Michigan, 1150 W Medical Center Dr. Ann Arbor, MI 48109, USA, Perelman School of Medicine, Penn Cardiovascular Institute and Department of Medicine, University of Pennsylvania, 3400 Civic Center Blvd. Philadelphia, PA 19104, USA and Washington University School of Medicine, 660 S. Euclid Ave. St. Louis, MO 63110, USADepartment of Medicine, Computation Institute and Argonne National Laboratory, 9700 S. Cass Ave. Argonne, IL 60439, USA, Department of Human Genetics, The University of Chicago, 5841 S. Maryland Ave Chicago, IL 60637, USA, Department of Internal Medicine, The University of Michigan, 1150 W Medical Center Dr. Ann Arbor, MI 48109, USA, Perelman School of Medicine, Penn Cardiovascular Institute and Department of Medicine, University of Pennsylvania, 3400 Civic Center Blvd. Philadelphia, PA 19104, USA and Washington University School of Medicine, 660 S. Euclid Ave. St. Louis, MO 63110, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 32, 'Computers|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu071', '24526712', 'The declining cost of generating DNA sequence is promoting an increase in whole genome sequencing, especially as applied to the human genome. Whole genome analysis requires the alignment and comparison of raw sequence data, and results in a computational bottleneck because of limited ability to analyze multiple genomes simultaneously.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78243, 2014, 'bio', 'The 3DGD: a database of genome 3D structure', 'Li, Chao|Dong, Xiao|Fan, Haiwei|Wang, Chuan|Ding, Guohui|Li, Yixue', 'Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, P. R. China, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, National Center for Protein Science, Shanghai 333 Haike Road, Pudong District, Shanghai 201210 and Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai 201203, P. R. ChinaKey Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, P. R. China, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, National Center for Protein Science, Shanghai 333 Haike Road, Pudong District, Shanghai 201210 and Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai 201203, P. R. China.|Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, P. R. China, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, National Center for Protein Science, Shanghai 333 Haike Road, Pudong District, Shanghai 201210 and Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai 201203, P. R. ChinaKey Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, P. R. China, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, National Center for Protein Science, Shanghai 333 Haike Road, Pudong District, Shanghai 201210 and Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai 201203, P. R. China.|Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, P. R. China, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, National Center for Protein Science, Shanghai 333 Haike Road, Pudong District, Shanghai 201210 and Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai 201203, P. R. China.|Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, P. R. China, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, National Center for Protein Science, Shanghai 333 Haike Road, Pudong District, Shanghai 201210 and Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai 201203, P. R. China.|Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, P. R. China, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, National Center for Protein Science, Shanghai 333 Haike Road, Pudong District, Shanghai 201210 and Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai 201203, P. R. ChinaKey Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, P. R. China, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, National Center for Protein Science, Shanghai 333 Haike Road, Pudong District, Shanghai 201210 and Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai 201203, P. R. China.|Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, P. R. China, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, National Center for Protein Science, Shanghai 333 Haike Road, Pudong District, Shanghai 201210 and Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai 201203, P. R. ChinaKey Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, P. R. China, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, National Center for Protein Science, Shanghai 333 Haike Road, Pudong District, Shanghai 201210 and Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai 201203, P. R. China.', 'China|China|China|China|China|China', 10, 'Animals|Chromatin|DNA-Binding Proteins|Databases, Genetic|Genome|Humans|Mice', 'Journal Article', '10.1093/bioinformatics/btu081', '24526713', 'The studies of chromatin 3D structure help us to understand its formation and function. Techniques combining chromosome conformation capture and next generation sequencing can capture chromatin structure information and has been applied to several different species and cell lines. We built 3DGD (3D Genome Database), a database that currently collected Hi-C data on four species, for easy accessing and visualization of chromatin 3D structure data. With the integration of other omics data such as genome-wide protein-DNA-binding data, this data source would be useful for researchers interested in chromatin structure and its biological functions.'),
(78244, 2014, 'bio', 'TSSV: a tool for characterization of complex allelic variants in pure and mixed genomes', 'Anvar, Seyed Yahya|van der Gaag, Kristiaan J|van der Heijden, Jaap W F|Veltrop, Marcel H A M|Vossen, Rolf H A M|de Leeuw, Rick H|Breukel, Cor|Buermans, Henk P J|Verbeek, J Sjef|de Knijff, Peter|den Dunnen, Johan T|Laros, Jeroen F J', 'Department of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The NetherlandsDepartment of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The Netherlands.|Department of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The Netherlands.|Department of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The Netherlands.|Department of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The Netherlands.|Department of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The Netherlands.|Department of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The Netherlands.|Department of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The Netherlands.|Department of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The NetherlandsDepartment of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The Netherlands.|Department of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The Netherlands.|Department of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The Netherlands.|Department of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The NetherlandsDepartment of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The Netherlands.|Department of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The NetherlandsDepartment of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The NetherlandsDepartment of Human Genetic, Leiden Genome Technology Center, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands and Netherlands Bioinformatics Centre, Leiden, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Neth', 28, 'Algorithms|Alleles|Deoxyribonucleases|Dystrophin|Female|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Male|Microsatellite Repeats|Mutation|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu068', '24532718', 'Advances in sequencing technologies and computational algorithms have enabled the study of genomic variants to dissect their functional consequence. Despite this unprecedented progress, current tools fail to reliably detect and characterize more complex allelic variants, such as short tandem repeats (STRs). We developed TSSV as an efficient and sensitive tool to specifically profile all allelic variants present in targeted loci. Based on its design, requiring only two short flanking sequences, TSSV can work without the use of a complete reference sequence to reliably profile highly polymorphic, repetitive or uncharacterized regions.'),
(78245, 2014, 'bio', 'SOAPdenovo-Trans: de novo transcriptome assembly with short RNA-Seq reads', 'Xie, Yinlong|Wu, Gengxiong|Tang, Jingbo|Luo, Ruibang|Patterson, Jordan|Liu, Shanlin|Huang, Weihua|He, Guangzhu|Gu, Shengchang|Li, Shengkang|Zhou, Xin|Lam, Tak-Wah|Li, Yingrui|Xu, Xun|Wong, Gane Ka-Shu|Wang, Jun', 'School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi ArabiaSchool of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawha|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia.|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi ArabiaSchool of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawha|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi ArabiaSchool of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawha|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia.|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia.|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia.|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia.|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi ArabiaSchool of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawha|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia.|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia.|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia.|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia.|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia.|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi ArabiaSchool of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawha|School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi ArabiaSchool of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, Institute of Biomedical Engineering, XiangYa School of Medicine, Central South University, Changsha 410008, China, BGI-tech, BGI-Shenzhen, Shenzhen 518083, China, Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada, The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen DK-2200, Denmark, Department of Biology, University of Copenhagen, Copenhagen DK-2200, Denmark and Princess Al Jawha', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Ca', 441, 'Algorithms|Alternative Splicing|Animals|Gene Expression Profiling|Genomics|High-Throughput Nucleotide Sequencing|Mice|Oryza|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btu077', '24532719', 'Transcriptome sequencing has long been the favored method for quickly and inexpensively obtaining a large number of gene sequences from an organism with no reference genome. Owing to the rapid increase in throughputs and decrease in costs of next- generation sequencing, RNA-Seq in particular has become the method of choice. However, the very short reads (e.g. 2 × 90 bp paired ends) from next generation sequencing makes de novo assembly to recover complete or full-length transcript sequences an algorithmic challenge.'),
(78246, 2014, 'bio', 'LPmerge: an R package for merging genetic maps by linear programming', 'Endelman, Jeffrey B|Plomion, Christophe', 'Department of Horticulture, University of Wisconsin, Madison, WI 53706, USA, INRA, UMR1202, BIOGECO, F-33610 Cestas and Université de Bordeaux, UMR1202 BIOGECO, F-33170 Talence, France.|Department of Horticulture, University of Wisconsin, Madison, WI 53706, USA, INRA, UMR1202, BIOGECO, F-33610 Cestas and Université de Bordeaux, UMR1202 BIOGECO, F-33170 Talence, FranceDepartment of Horticulture, University of Wisconsin, Madison, WI 53706, USA, INRA, UMR1202, BIOGECO, F-33610 Cestas and Université de Bordeaux, UMR1202 BIOGECO, F-33170 Talence, France.', 'France|France', 62, 'Algorithms|Chromosome Mapping|Genetic Linkage|Programming, Linear|Software', 'Journal Article', '10.1093/bioinformatics/btu091', '24532720', 'Consensus genetic maps constructed from multiple populations are an important resource for both basic and applied research, including genome-wide association analysis, genome sequence assembly and studies of evolution. The LPmerge software uses linear programming to efficiently minimize the mean absolute error between the consensus map and the linkage maps from each population. This minimization is performed subject to linear inequality constraints that ensure the ordering of the markers in the linkage maps is preserved. When marker order is inconsistent between linkage maps, a minimum set of ordinal constraints is deleted to resolve the conflicts.'),
(78247, 2014, 'bio', 'SBARS: fast creation of dotplots for DNA sequences on different scales using GA-,GC-content', 'Pyatkov, Maxim I|Pankratov, Anton N', 'Institute of Mathematical Problems of Biology, Russian Academy of Sciences, Pushchino, Moscow region 142290, Russia.|Institute of Mathematical Problems of Biology, Russian Academy of Sciences, Pushchino, Moscow region 142290, Russia.', '-|-', 5, 'Base Composition|DNA|Genomics|Repetitive Sequences, Nucleic Acid|Sequence Analysis, DNA|Software|Tandem Repeat Sequences', 'Journal Article', '10.1093/bioinformatics/btu095', '24532721', 'Structural analysis of long DNA fragments, including chromosomes and whole genomes, is one of the main challenges in modern bioinformatics. Here, we propose an original approach based on spectral methods and its implementation called SBARS (Spectral-Based Approach for Repeats Search. The main idea of our approach is that repeated DNA structures are recognized not within the nucleotide sequence directly but within the function derived from this sequence. This allows us to investigate nucleotide sequences on different scales and decrease time complexity for dotplot creation down to [Formula: see text].'),
(78248, 2014, 'bio', 'fast_protein_cluster: parallel and optimized clustering of large-scale protein modeling data', 'Hung, Ling-Hong|Samudrala, Ram', 'Department of Microbiology, University of Washington, Seattle, WA 98109, USA.|Department of Microbiology, University of Washington, Seattle, WA 98109, USA.', 'United States|United States', 8, 'Algorithms|Cluster Analysis|Models, Molecular|Protein Conformation|Software', 'Journal Article', '10.1093/bioinformatics/btu098', '24532722', 'fast_protein_cluster is a fast, parallel and memory efficient package used to cluster 60 000 sets of protein models (with up to 550 000 models per set) generated by the Nutritious Rice for the World project.'),
(78249, 2014, 'bio', 'Discrete mixture modeling to address genetic heterogeneity in time-to-event regression', 'Eng, Kevin H|Hanlon, Bret M', 'Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, USA and Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53705, USA.|Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, USA and Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53705, USA.', 'United States|United States', 5, 'Algorithms|Cluster Analysis|DNA Repair|Epidermal Growth Factor|Epiregulin|Female|Gene Expression|Genetic Heterogeneity|Humans|Models, Genetic|Models, Statistical|Ovarian Neoplasms|Regression Analysis|Survival Analysis', 'Journal Article', '10.1093/bioinformatics/btu065', '24532723', 'Time-to-event regression models are a critical tool for associating survival time outcomes with molecular data. Despite mounting evidence that genetic subgroups of the same clinical disease exist, little attention has been given to exploring how this heterogeneity affects time-to-event model building and how to accommodate it. Methods able to diagnose and model heterogeneity should be valuable additions to the biomarker discovery toolset.'),
(78250, 2014, 'bio', 'ADaCGH2: parallelized analysis of (big) CNA data', 'Diaz-Uriarte, Ramon', 'Department of Biochemistry, Universidad Autónoma de Madrid, Instituto de Investigaciones Biomédicas Alberto Sols (UAM-CSIC), 28029 Madrid, Spain.', 'Spain', 1, 'Algorithms|DNA Copy Number Variations|Genomics|Software', 'Journal Article', '10.1093/bioinformatics/btu099', '24532724', 'Studies of genomic DNA copy number alteration can deal with datasets with several million probes and thousands of subjects. Analyzing these data with currently available software (e.g. as available from BioConductor) can be extremely slow and may not be feasible because of memory requirements.'),
(78251, 2014, 'bio', 'EXTREME: an online EM algorithm for motif discovery', 'Quang, Daniel|Xie, Xiaohui', 'Department of Computer Science, University of California, Irvine, CA 92697, USA and Center for Complex Biological Systems, University of California, Irvine, CA 92697, USADepartment of Computer Science, University of California, Irvine, CA 92697, USA and Center for Complex Biological Systems, University of California, Irvine, CA 92697, USA.|Department of Computer Science, University of California, Irvine, CA 92697, USA and Center for Complex Biological Systems, University of California, Irvine, CA 92697, USADepartment of Computer Science, University of California, Irvine, CA 92697, USA and Center for Complex Biological Systems, University of California, Irvine, CA 92697, USA.', 'United States|United States', 28, 'Algorithms|Chromatin Immunoprecipitation|Nucleotide Motifs|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btu093', '24532725', 'Identifying regulatory elements is a fundamental problem in the field of gene transcription. Motif discovery-the task of identifying the sequence preference of transcription factor proteins, which bind to these elements-is an important step in this challenge. MEME is a popular motif discovery algorithm. Unfortunately, MEMEs running time scales poorly with the size of the dataset. Experiments such as ChIP-Seq and DNase-Seq are providing a rich amount of information on the binding preference of transcription factors. MEME cannot discover motifs in data from these experiments in a practical amount of time without a compromising strategy such as discarding a majority of the sequences.'),
(78252, 2014, 'bio', 'ZDOCK server: interactive docking prediction of protein-protein complexes and symmetric multimers', 'Pierce, Brian G|Wiehe, Kevin|Hwang, Howook|Kim, Bong-Hyun|Vreven, Thom|Weng, Zhiping', 'Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605 and Bioinformatics Program, Boston University, 44 Cummington Mall, Boston, MA 02215 USAProgram in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605 and Bioinformatics Program, Boston University, 44 Cummington Mall, Boston, MA 02215 USA.|Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605 and Bioinformatics Program, Boston University, 44 Cummington Mall, Boston, MA 02215 USA.|Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605 and Bioinformatics Program, Boston University, 44 Cummington Mall, Boston, MA 02215 USAProgram in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605 and Bioinformatics Program, Boston University, 44 Cummington Mall, Boston, MA 02215 USA.|Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605 and Bioinformatics Program, Boston University, 44 Cummington Mall, Boston, MA 02215 USA.|Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605 and Bioinformatics Program, Boston University, 44 Cummington Mall, Boston, MA 02215 USA.|Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605 and Bioinformatics Program, Boston University, 44 Cummington Mall, Boston, MA 02215 USAProgram in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605 and Bioinformatics Program, Boston University, 44 Cummington Mall, Boston, MA 02215 USA.', 'United States|United States|United States|United States|United States|United States', 588, 'Algorithms|Molecular Docking Simulation|Multiprotein Complexes|Protein Multimerization|Software', 'Journal Article', '10.1093/bioinformatics/btu097', '24532726', 'Protein-protein interactions are essential to cellular and immune function, and in many cases, because of the absence of an experimentally determined structure of the complex, these interactions must be modeled to obtain an understanding of their molecular basis. We present a user-friendly protein docking server, based on the rigid-body docking programs ZDOCK and M-ZDOCK, to predict structures of protein-protein complexes and symmetric multimers. With a goal of providing an accessible and intuitive interface, we provide options for users to guide the scoring and the selection of output models, in addition to dynamic visualization of input structures and output docking models. This server enables the research community to easily and quickly produce structural models of protein-protein complexes and symmetric multimers for their own analysis.'),
(78253, 2014, 'bio', 'Condition-specific target prediction from motifs and expression', 'Meng, Guofeng|Vingron, Martin', 'Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.', 'Germany|Germany', 3, 'Binding Sites|Chromatin Immunoprecipitation|Estradiol|Gene Expression Profiling|Humans|MCF-7 Cells|Nucleotide Motifs|Oligonucleotide Array Sequence Analysis|Position-Specific Scoring Matrices|Promoter Regions, Genetic|Receptors, Estrogen|Regulatory Elements, Transcriptional|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btu066', '24532727', 'It is commonplace to predict targets of transcription factors (TFs) by sequence matching with their binding motifs. However, this ignores the particular condition of the cells. Gene expression data can provide condition-specific information, as is, e.g. exploited in Motif Enrichment Analysis.'),
(78254, 2014, 'bio', 'GUILDify: a web server for phenotypic characterization of genes through biological data integration and network-based prioritization algorithms', 'Guney, Emre|Garcia-Garcia, Javier|Oliva, Baldo', 'Departament de Ciencies Experimentals i de la Salut, Structural Bioinformatics Group (GRIB-IMIM), Universitat Pompeu Fabra, Barcelona, 08003 Catalonia, Spain.|Departament de Ciencies Experimentals i de la Salut, Structural Bioinformatics Group (GRIB-IMIM), Universitat Pompeu Fabra, Barcelona, 08003 Catalonia, Spain.|Departament de Ciencies Experimentals i de la Salut, Structural Bioinformatics Group (GRIB-IMIM), Universitat Pompeu Fabra, Barcelona, 08003 Catalonia, Spain.', 'Spain|Spain|Spain', 25, 'Algorithms|Disease|Drug Repositioning|Genes|Humans|Internet|Phenotype|Protein Interaction Maps|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu092', '24532728', 'Determining genetic factors underlying various phenotypes is hindered by the involvement of multiple genes acting cooperatively. Over the past years, disease-gene prioritization has been central to identify genes implicated in human disorders. Special attention has been paid on using physical interactions between the proteins encoded by the genes to link them with diseases. Such methods exploit the guilt-by-association principle in the protein interaction network to uncover novel disease-gene associations. These methods rely on the proximity of a gene in the network to the genes associated with a phenotype and require a set of initial associations. Here, we present GUILDify, an easy-to-use web server for the phenotypic characterization of genes. GUILDify offers a prioritization approach based on the protein-protein interaction network where the initial phenotype-gene associations are retrieved via free text search on biological databases. GUILDify web server does not restrict the prioritization to any predefined phenotype, supports multiple species and accepts user-specified genes. It also prioritizes drugs based on the ranking of their targets, unleashing opportunities for repurposing drugs for novel therapies.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78255, 2014, 'bio', 'SKINK: a web server for string kernel based kink prediction in xcexb1-helices', 'Seifert, Tim|Lund, Andreas|Kneissl, Benny|Mueller, Sabine C|Tautermann, Christofer S|Hildebrandt, Andreas', 'Department of Software Engineering and Bioinformatics, Johannes Gutenberg University of Mainz, 55128 Mainz, Institute for Computer Science, Johann Wolfgang Goethe-University Frankfurt am Main, 60054 Frankfurt am Main, Data Science, Pharma Research and Early Development Informatics (pREDi), Roche Diagnostics GmbH, 82377 Penzberg, Department of Human Genetics, Saarland University Faculty of Medicine, 66421 Homburg and Lead Identification and Optimization Support, Boehringer-Ingelheim Pharma GmbH & Co. KG, 88397 Biberach, Germany.|Department of Software Engineering and Bioinformatics, Johannes Gutenberg University of Mainz, 55128 Mainz, Institute for Computer Science, Johann Wolfgang Goethe-University Frankfurt am Main, 60054 Frankfurt am Main, Data Science, Pharma Research and Early Development Informatics (pREDi), Roche Diagnostics GmbH, 82377 Penzberg, Department of Human Genetics, Saarland University Faculty of Medicine, 66421 Homburg and Lead Identification and Optimization Support, Boehringer-Ingelheim Pharma GmbH & Co. KG, 88397 Biberach, Germany.|Department of Software Engineering and Bioinformatics, Johannes Gutenberg University of Mainz, 55128 Mainz, Institute for Computer Science, Johann Wolfgang Goethe-University Frankfurt am Main, 60054 Frankfurt am Main, Data Science, Pharma Research and Early Development Informatics (pREDi), Roche Diagnostics GmbH, 82377 Penzberg, Department of Human Genetics, Saarland University Faculty of Medicine, 66421 Homburg and Lead Identification and Optimization Support, Boehringer-Ingelheim Pharma GmbH & Co. KG, 88397 Biberach, Germany.|Department of Software Engineering and Bioinformatics, Johannes Gutenberg University of Mainz, 55128 Mainz, Institute for Computer Science, Johann Wolfgang Goethe-University Frankfurt am Main, 60054 Frankfurt am Main, Data Science, Pharma Research and Early Development Informatics (pREDi), Roche Diagnostics GmbH, 82377 Penzberg, Department of Human Genetics, Saarland University Faculty of Medicine, 66421 Homburg and Lead Identification and Optimization Support, Boehringer-Ingelheim Pharma GmbH & Co. KG, 88397 Biberach, Germany.|Department of Software Engineering and Bioinformatics, Johannes Gutenberg University of Mainz, 55128 Mainz, Institute for Computer Science, Johann Wolfgang Goethe-University Frankfurt am Main, 60054 Frankfurt am Main, Data Science, Pharma Research and Early Development Informatics (pREDi), Roche Diagnostics GmbH, 82377 Penzberg, Department of Human Genetics, Saarland University Faculty of Medicine, 66421 Homburg and Lead Identification and Optimization Support, Boehringer-Ingelheim Pharma GmbH & Co. KG, 88397 Biberach, Germany.|Department of Software Engineering and Bioinformatics, Johannes Gutenberg University of Mainz, 55128 Mainz, Institute for Computer Science, Johann Wolfgang Goethe-University Frankfurt am Main, 60054 Frankfurt am Main, Data Science, Pharma Research and Early Development Informatics (pREDi), Roche Diagnostics GmbH, 82377 Penzberg, Department of Human Genetics, Saarland University Faculty of Medicine, 66421 Homburg and Lead Identification and Optimization Support, Boehringer-Ingelheim Pharma GmbH & Co. KG, 88397 Biberach, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 1, 'Computational Biology|Internet|Protein Structure, Secondary|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btu096', '24532729', 'The reasons for distortions from optimal xcexb1-helical geometry are widely unknown, but their influences on structural changes of proteins are significant. Hence, their prediction is a crucial problem in structural bioinformatics. Here, we present a new web server, called SKINK, for string kernel based kink prediction. Extending our previous study, we also annotate the most probable kink position in a given xcexb1-helix sequence.'),
(78256, 2014, 'bio', 'An APN model for Arrhythmic beat classification', 'Chiang, Hsiu-Sen|Shih, Dong-Her|Lin, Binshan|Shih, Ming-Hung', 'Department of Information Management, National Taichung University of Science and Technology, 129, Section 3, Sanmin Road, Taichung City 404, Taiwan, Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Douliu City, Yunlin County, Taiwan, College of Business Administration, BE321, Louisiana State University in Shreveport, Shreveport, LA 71115, USA and Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Department of Information Management, National Taichung University of Science and Technology, 129, Section 3, Sanmin Road, Taichung City 404, Taiwan, Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Douliu City, Yunlin County, Taiwan, College of Business Administration, BE321, Louisiana State University in Shreveport, Shreveport, LA 71115, USA and Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Department of Information Management, National Taichung University of Science and Technology, 129, Section 3, Sanmin Road, Taichung City 404, Taiwan, Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Douliu City, Yunlin County, Taiwan, College of Business Administration, BE321, Louisiana State University in Shreveport, Shreveport, LA 71115, USA and Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Department of Information Management, National Taichung University of Science and Technology, 129, Section 3, Sanmin Road, Taichung City 404, Taiwan, Department of Information Management, National Yunlin University of Science and Technology, 123, Section 3, University Road, Douliu City, Yunlin County, Taiwan, College of Business Administration, BE321, Louisiana State University in Shreveport, Shreveport, LA 71115, USA and Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.', 'United States|United States|United States|United States', 2, 'Adult|Aged|Aged, 80 and over|Algorithms|Arrhythmias, Cardiac|Electrocardiography|Female|Humans|Male|Middle Aged|Young Adult', 'Journal Article', '10.1093/bioinformatics/btu101', '24535096', 'Changes in the normal rhythm of a human heart may result in different cardiac arrhythmias, which may be immediately fatal or cause irreparable damage to the heart sustained over long periods of time. Therefore, the ability to automatically identify arrhythmias from ECG recordings is important for clinical diagnosis and treatment. In this article, classification by using associative Petri net (APN) for personalized ECG-arrhythmia-pattern identification is proposed for the first time in literature.'),
(78257, 2014, 'bio', 'SeqGSEA: a Bioconductor package for gene set enrichment analysis of RNA-Seq data integrating differential expression and splicing', 'Wang, Xi|Cairns, Murray J', 'School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle, Hunter Medical Research Institute, New Lambton, and Schizophrenia Research Institute, Sydney, NSW, AustraliaSchool of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle, Hunter Medical Research Institute, New Lambton, and Schizophrenia Research Institute, Sydney, NSW, Australia.|School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle, Hunter Medical Research Institute, New Lambton, and Schizophrenia Research Institute, Sydney, NSW, AustraliaSchool of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle, Hunter Medical Research Institute, New Lambton, and Schizophrenia Research Institute, Sydney, NSW, AustraliaSchool of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle, Hunter Medical Research Institute, New Lambton, and Schizophrenia Research Institute, Sydney, NSW, Australia.', 'Australia|Australia', 0, 'Gene Expression Profiling|Humans|RNA Splicing|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu090', '24535097', 'SeqGSEA is an open-source Bioconductor package for the functional integration of differential expression and splicing analysis in RNA-Seq data. SeqGSEA implements an analysis pipeline, which first computes differential splicing and differential expression scores, followed by integrating them into a per-gene score that quantifies each genes association with a phenotype of interest, and finally executes gene set enrichment analysis in a cutoff-free manner to achieve biological insights. SeqGSEA accounts for biological variability and determines the statistical significance of gene pathways and networks using subject permutation, and thus requires at least five samples per group. Real applications show that SeqGSEA detects more biologically meaningful gene sets without biases toward long or highly expressed genes. SeqGSEA can be set up to run in parallel to reduce the analysis time.'),
(78258, 2014, 'bio', 'Dynamic networks reveal key players in aging', 'Faisal, Fazle E|Milenkovixc4x87, Tijana', 'Department of Computer Science and Engineering, ECK Institute for Global Health and Interdisciplinary Center for Network Science and Applications, University of Notre Dame, Notre Dame, IN 46556, USA.|Department of Computer Science and Engineering, ECK Institute for Global Health and Interdisciplinary Center for Network Science and Applications, University of Notre Dame, Notre Dame, IN 46556, USA.', 'United States|United States', 52, 'Adult|Aged|Aged, 80 and over|Aging|Gene Expression Profiling|Gene Ontology|Humans|Middle Aged|Models, Biological|Protein Interaction Mapping|Young Adult', 'Journal Article', '10.1093/bioinformatics/btu089', '24554629', 'Because susceptibility to diseases increases with age, studying aging gains importance. Analyses of gene expression or sequence data, which have been indispensable for investigating aging, have been limited to studying genes and their protein products in isolation, ignoring their connectivities. However, proteins function by interacting with other proteins, and this is exactly what biological networks (BNs) model. Thus, analyzing the proteins BN topologies could contribute to the understanding of aging. Current methods for analyzing systems-level BNs deal with their static representations, even though cells are dynamic. For this reason, and because different data types can give complementary biological insights, we integrate current static BNs with aging-related gene expression data to construct dynamic age-specific BNs. Then, we apply sensitive measures of topology to the dynamic BNs to study cellular changes with age.'),
(78259, 2014, 'bio', 'Automated analysis of giant unilamellar vesicles using circular Hough transformation', 'Hermann, Eduard|Bleicken, Stephanie|Subburaj, Yamunadevi|García-Sáez, Ana J', 'Max-Planck Institute for Intelligent Systems, Heisenbergstr. 3, 70569 Stuttgart and Interfaculty Institute for Biochemistry, University of Tübingen, Hoppe-Seyler-Straße 4, 72076 Tübingen, Germany.|Max-Planck Institute for Intelligent Systems, Heisenbergstr. 3, 70569 Stuttgart and Interfaculty Institute for Biochemistry, University of Tübingen, Hoppe-Seyler-Straße 4, 72076 Tübingen, Germany.|Max-Planck Institute for Intelligent Systems, Heisenbergstr. 3, 70569 Stuttgart and Interfaculty Institute for Biochemistry, University of Tübingen, Hoppe-Seyler-Straße 4, 72076 Tübingen, Germany.|Max-Planck Institute for Intelligent Systems, Heisenbergstr. 3, 70569 Stuttgart and Interfaculty Institute for Biochemistry, University of Tübingen, Hoppe-Seyler-Straße 4, 72076 Tübingen, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Cell Membrane Permeability|Membrane Proteins|Microscopy, Confocal|Software|Unilamellar Liposomes|bcl-2-Associated X Protein', 'Journal Article', '10.1093/bioinformatics/btu102', '24554630', 'In order to obtain statistically relevant results, the study of membrane effects at the single-vesicle level requires the analysis of several hundreds of giant unilamellar vesicles (GUVs), which becomes a very time-consuming task if carried out manually. Complete and user-friendly software for fast and bias-free automated analysis has not been reported yet.'),
(78260, 2014, 'bio', 'MRHMMs: multivariate regression hidden Markov models and the variantS', 'Lee, Yeonok|Ghosh, Debashis|Hardison, Ross C|Zhang, Yu', 'Department of Statistics and Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16803, USA.|Department of Statistics and Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16803, USA.|Department of Statistics and Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16803, USA.|Department of Statistics and Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16803, USA.', 'United States|United States|United States|United States', 2, 'Algorithms|Animals|GATA1 Transcription Factor|Genome|Genomics|Logistic Models|Markov Chains|Mice|Multivariate Analysis|Normal Distribution|Software', 'Journal Article', '10.1093/bioinformatics/btu070', '24558116', 'Hidden Markov models (HMMs) are flexible and widely used in scientific studies. Particularly in genomics and genetics, there are multiple distinct regimes in the genome within each of which the relationships among multivariate features are distinct. Examples include differential gene regulation depending on gene functions and experimental conditions, and varying combinatorial patterns of multiple transcription factors. We developed a software package called MRHMMs (Multivariate Regression Hidden Markov Models and the variantS) that accommodates a variety of HMMs that can be flexibly applied to many biological studies and beyond. MRHMMs supplements existing HMM software packages in two aspects. First, MRHMMs provides a diverse set of emission probability structures, including mixture of multivariate normal distributions and (logistic) regression models. Second, MRHMMs is computationally efficient for analyzing large data-sets generated in current genome-wide studies. Especially, the software is written in C for the speed advantage and further amenable to implement alternative models to meet users own purposes.'),
(78261, 2014, 'bio', 'Assessing single nucleotide variant detection and genotype calling on whole-genome sequenced individuals', 'Cheng, Anthony Youzhi|Teo, Yik-Ying|Ong, Rick Twee-Hee', 'Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117597, Life Sciences Institute, National University of Singapore, Singapore 117456, Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore 117456 and Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672.|Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117597, Life Sciences Institute, National University of Singapore, Singapore 117456, Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore 117456 and Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117597, Life Sciences Institute, National University of Singapore, Singapore 117456, Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore 117456 and Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117597, Life Sciences Institute, National University of Singapore, Singapore 117456, Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore 117456 and Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117597, Life Sciences Institute, National University of Singapore, Singapore 117456, Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore 117456 and Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672Saw Swee Hock School of Public Health, National University of Singapore, Singapore 11759|Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117597, Life Sciences Institute, National University of Singapore, Singapore 117456, Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore 117456 and Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672.', 'Singapore|Singapore|Singapore', 44, 'Female|Genome, Human|Genotype|Genotyping Techniques|High-Throughput Nucleotide Sequencing|Humans|Male|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/btu067', '24558117', 'Whole-genome sequencing (WGS) is now routinely used for the detection and identification of genetic variants, particularly single nucleotide polymorphisms (SNPs) in humans, and this has provided valuable new insights into human diversity, population histories and genetic association studies of traits and diseases. However, this relies on accurate detection and genotyping calling of the polymorphisms present in the samples sequenced. To minimize cost, the majority of current WGS studies, including the 1000 Genomes Project (1 KGP) have adopted low coverage sequencing of large number of samples, where such designs have inadvertently influenced the development of variant calling methods on WGS data. Assessment of variant accuracy are usually performed on the same set of low coverage individuals or a smaller number of deeply sequenced individuals. It is thus unclear how these variant calling methods would fare for a dataset of xe2x88xbc100 samples from a population not part of the 1 KGP that have been sequenced at various coverage depths.'),
(78262, 2014, 'bio', 'Mantra 20: an online collaborative resource for drug mode of action and repurposing by network analysis', 'Carrella, Diego|Napolitano, Francesco|Rispoli, Rossella|Miglietta, Mario|Carissimo, Annamaria|Cutillo, Luisa|Sirci, Francesco|Gregoretti, Francesco|Di Bernardo, Diego', 'Telethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli Parthenope, Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy.|Telethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli Parthenope, Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy.|Telethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli Parthenope, Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy.|Telethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli Parthenope, Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy.|Telethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli Parthenope, Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy.|Telethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli Parthenope, Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, 80125 Naples, ItalyTelethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli Parthenope, Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy.|Telethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli Parthenope, Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy.|Telethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli Parthenope, Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy.|Telethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli Parthenope, Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, 80125 Naples, ItalyTelethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli Parthenope, Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Cooperative Behavior|Drug Discovery|Drug Repositioning|Gene Expression Profiling|Internet|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btu058', '24558125', 'Elucidation of molecular targets of a compound [mode of action (MoA)] and its off-targets is a crucial step in drug development. We developed an online collaborative resource (MANTRA 2.0) that supports this process by exploiting similarities between drug-induced transcriptional profiles. Drugs are organized in a network of nodes (drugs) and edges (similarities) highlighting communities of drugs sharing a similar MoA. A user can upload gene expression profiles before and after drug treatment in one or multiple cell types. An automated processing pipeline transforms the gene expression profiles into a unique drug node embedded in the drug-network. Visual inspection of the neighbouring drugs and communities helps in revealing its MoA and to suggest new applications of known drugs (drug repurposing). MANTRA 2.0 allows storing and sharing user-generated network nodes, thus making MANTRA 2.0 a collaborative ever-growing resource.'),
(78263, 2014, 'bio', 'Improved protein-ligand binding affinity prediction by using a curvature-dependent surface-area model', 'Cao, Yang|Li, Lei', 'Center for Growth, Metabolism and Aging, Key Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, China.|Center for Growth, Metabolism and Aging, Key Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, China.', 'China|China', 0, 'Entropy|Hydrogen Bonding|Hydrophobic and Hydrophilic Interactions|Ligands|Models, Chemical|Protein Binding|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu104', '24563257', 'Hydrophobic effect plays a pivotal role in most protein-ligand binding. State-of-the-art protein-ligand scoring methods usually treat hydrophobic free energy as surface tension, which is proportional to interfacial surface area for simplicity and efficiency. However, this treatment ignores the role of molecular shape, which has been found very important by either experimental or theoretical studies.'),
(78264, 2014, 'bio', 'jHeatmap: an interactive heatmap viewer for the web', 'Deu-Pons, Jordi|Schroeder, Michael P|Lopez-Bigas, Nuria', 'Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Dr. Aiguader 88, Barcelona, Spain and Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys, 23, Barcelona, Spain.|Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Dr. Aiguader 88, Barcelona, Spain and Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys, 23, Barcelona, Spain.|Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Dr. Aiguader 88, Barcelona, Spain and Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys, 23, Barcelona, SpainResearch Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Dr. Aiguader 88, Barcelona, Spain and Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys, 23, Barcelona, Spain.', 'Spain|Spain|Spain', 0, 'Computer Graphics|Genomics|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btu094', '24567544', 'The generation of large volumes of omics data to conduct exploratory studies has become feasible and is now extensively used to gain new insights in life sciences. The effective exploration of the generated data by experts is a crucial step for the successful extraction of knowledge from these datasets. This requires availability of intuitive and interactive visualization tools that can display complex data. Matrix heatmaps are graphical representations frequently used for the description of complex omics data. Here, we present jHeatmap, a web-based tool that allows interactive matrix heatmap visualization and exploration. It is an adaptable javascript library designed to be embedded by means of basic coding skills into web portals to visualize data matrices as interactive and customizable heatmaps.'),
(78265, 2014, 'bio', 'iCall: a genotype-calling algorithm for rare, low-frequency and common variants on the Illumina exome array', 'Zhou, Jin|Tantoso, Erwin|Wong, Lai-Ping|Ong, Rick Twee-Hee|Bei, Jin-Xin|Li, Yi|Liu, Jianjun|Khor, Chiea-Chuen|Teo, Yik-Ying', 'Department of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, Singapore.|Department of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, Singapore.|Department of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, Singapore.|Department of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, Singapore.|Department of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, Singapore.|Department of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, Singapore.|Department of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, Singapore.|Department of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, SingaporeDepartment of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, Singapore.|Department of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, SingaporeDepartment of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, SingaporeDepartment of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, SingaporeDepartment of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, SingaporeDepartment of Statistics and Applied Probability, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Genome Institute of Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore and Life Sciences Institute, National University of Singapore, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 1, 'Algorithms|Cluster Analysis|Exome|Gene Frequency|Genome, Human|Genotyping Techniques|High-Throughput Nucleotide Sequencing|Humans|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu107', '24567545', 'Next-generation genotyping microarrays have been designed with insights from 1000 Genomes Project and whole-exome sequencing studies. These arrays additionally include variants that are typically present at lower frequencies. Determining the genotypes of these variants from hybridization intensities is challenging because there is less support to locate the presence of the minor alleles when the allele counts are low. Existing algorithms are mainly designed for calling common variants and are notorious for failing to generate accurate calls for low-frequency and rare variants. Here, we introduce a new calling algorithm, iCall, to call genotypes for variants across the whole spectrum of allele frequencies.'),
(78266, 2014, 'bio', 'Incorporating post-translational modifications and unnatural amino acids into high-throughput modeling of protein structures', 'Nagata, Ken|Randall, Arlo|Baldi, Pierre', 'Department of Computer Science and Institute for Genomics and Bioinformatics, University of California, Irvine, CA, USADepartment of Computer Science and Institute for Genomics and Bioinformatics, University of California, Irvine, CA, USA.|Department of Computer Science and Institute for Genomics and Bioinformatics, University of California, Irvine, CA, USADepartment of Computer Science and Institute for Genomics and Bioinformatics, University of California, Irvine, CA, USA.|Department of Computer Science and Institute for Genomics and Bioinformatics, University of California, Irvine, CA, USADepartment of Computer Science and Institute for Genomics and Bioinformatics, University of California, Irvine, CA, USA.', 'United States|United States|United States', 0, 'Amino Acids|Artificial Intelligence|Models, Molecular|Neural Networks (Computer)|Phosphorylation|Protein Conformation|Protein Processing, Post-Translational|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu106', '24574112', 'Accurately predicting protein side-chain conformations is an important subproblem of the broader protein structure prediction problem. Several methods exist for generating fairly accurate models for moderate-size proteins in seconds or less. However, a major limitation of these methods is their inability to model post-translational modifications (PTMs) and unnatural amino acids. In natural living systems, the chemical groups added following translation are often critical for the function of the protein. In engineered systems, unnatural amino acids are incorporated into proteins to explore structure-function relationships and create novel proteins.'),
(78267, 2014, 'bio', 'CanSNPer: a hierarchical genotype classifier of clonal pathogens', 'Lärkeryd, Adrian|Myrtennäs, Kerstin|Karlsson, Edvin|Dwibedi, Chinmay Kumar|Forsman, Mats|Larsson, Pär|Johansson, Anders|Sjödin, Andreas', 'Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden.|Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden.|Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden.|Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, SwedenDepartment of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden.|Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden.|Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden.|Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden.|Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, SwedenDepartment of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 15, 'Genomics|Genotype|Genotyping Techniques|Molecular Typing|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btu113', '24574113', 'Advances in typing methodologies have recently reformed the field of molecular epidemiology of pathogens. The falling cost of sequencing technologies is creating a deluge of whole genome sequencing data that burdens bioinformatics resources and tool development. In particular, single nucleotide polymorphisms in core genomes of pathogens are recognized as the most important markers for inferring genetic relationships because they are evolutionarily stable and amenable to high-throughput detection methods. Sequence data will provide an excellent opportunity to extend our understanding of infectious disease when the challenge of extracting knowledge from available sequence resources is met. Here, we present an efficient and user-friendly genotype classification pipeline, CanSNPer, based on an easily expandable database of predefined canonical single nucleotide polymorphisms.'),
(78268, 2014, 'bio', 'Optimization of gene set annotations via entropy minimization over variable clusters (EMVC)', 'Frost, H Robert|Moore, Jason H', 'Departments of Genetics and Community and Family Medicine, Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH 03755, USA.|Departments of Genetics and Community and Family Medicine, Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH 03755, USA.', 'United States|United States', 0, 'Algorithms|Gene Expression Profiling|Humans|Leukemia|Molecular Sequence Annotation|Oligonucleotide Array Sequence Analysis|Tumor Suppressor Protein p53', 'Journal Article', '10.1093/bioinformatics/btu110', '24574114', 'Gene set enrichment has become a critical tool for interpreting the results of high-throughput genomic experiments. Inconsistent annotation quality and lack of annotation specificity, however, limit the statistical power of enrichment methods and make it difficult to replicate enrichment results across biologically similar datasets.'),
(78269, 2014, 'bio', 'BioPlat: a software for human cancer biomarker discovery', 'Butti, Matias D|Chanfreau, Hernan|Martinez, Diego|García, Diego|Lacunza, Ezequiel|Abba, Martin C', 'Basic and Applied Immunological Research Center, Faculty of Medical Sciences, National University of La Plata, 1900 La Plata, Argentina.|Basic and Applied Immunological Research Center, Faculty of Medical Sciences, National University of La Plata, 1900 La Plata, Argentina.|Basic and Applied Immunological Research Center, Faculty of Medical Sciences, National University of La Plata, 1900 La Plata, Argentina.|Basic and Applied Immunological Research Center, Faculty of Medical Sciences, National University of La Plata, 1900 La Plata, Argentina.|Basic and Applied Immunological Research Center, Faculty of Medical Sciences, National University of La Plata, 1900 La Plata, Argentina.|Basic and Applied Immunological Research Center, Faculty of Medical Sciences, National University of La Plata, 1900 La Plata, Argentina.', 'Argentina|Argentina|Argentina|Argentina|Argentina|Argentina', 5, 'Algorithms|Biomarkers, Tumor|Breast Neoplasms|Data Mining|Databases, Genetic|Female|Gene Expression Profiling|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btu111', '24574115', 'Development of effective tools such as oligo-microarrays and next-generation sequencing methods for monitoring gene expression on a large scale has resulted in the discovery of gene signatures with prognostic/predictive value in various malignant neoplastic diseases. However, with the exponential growth of gene expression databases, biologists are faced with the challenge of extracting useful information from these repositories. Here, we present a software package, BioPlat (Biomarkers Platform), which allows biologists to identify novel prognostic and predictive cancer biomarkers based on the data mining of gene expression signatures and gene expression profiling databases. BioPlat has been designed as an easy-to-use and flexible desktop software application, which provides a set of analytical tools related to data extraction, preprocessing, filtering, gene expression signature calculation, in silico validation, feature selection and annotation that leverage the integration and reuse of gene expression signatures in the context of follow-up data.'),
(78270, 2014, 'bio', 'MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes', 'Huerta, Mario|Munyi, Marc|Expósito, David|Querol, Enric|Cedano, Juan', 'Institut de Biotecnologia i Biomedicina, Escola Tècnica Superior de Ingenieria, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain and Laboratorio de Inmunología, Universidad de la República Regional Norte-Salto, Rivera 1350, CP 50000 Salto, Uruguay.|Institut de Biotecnologia i Biomedicina, Escola Tècnica Superior de Ingenieria, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain and Laboratorio de Inmunología, Universidad de la República Regional Norte-Salto, Rivera 1350, CP 50000 Salto, Uruguay.|Institut de Biotecnologia i Biomedicina, Escola Tècnica Superior de Ingenieria, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain and Laboratorio de Inmunología, Universidad de la República Regional Norte-Salto, Rivera 1350, CP 50000 Salto, Uruguay.|Institut de Biotecnologia i Biomedicina, Escola Tècnica Superior de Ingenieria, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain and Laboratorio de Inmunología, Universidad de la República Regional Norte-Salto, Rivera 1350, CP 50000 Salto, Uruguay.|Institut de Biotecnologia i Biomedicina, Escola Tècnica Superior de Ingenieria, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain and Laboratorio de Inmunología, Universidad de la República Regional Norte-Salto, Rivera 1350, CP 50000 Salto, Uruguay.', 'Spain|Spain|Spain|Spain|Spain', 0, 'Databases, Genetic|Gene Expression Profiling|Genetic Markers|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btu109', '24574116', 'The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researchers microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78271, 2014, 'bio', 'Deciphering kinase-substrate relationships by analysis of domain-specific phosphorylation network', 'Damle, Nikhil Prakash|Mohanty, Debasisa', 'Bioinformatics Centre, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India.|Bioinformatics Centre, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India.', 'India|India', 0, 'Animals|Humans|Mice|Phosphoproteins|Phosphorylation|Protein Kinases|Protein Structure, Tertiary|Rats|Software', 'Journal Article', '10.1093/bioinformatics/btu112', '24574117', 'In silico prediction of site-specific kinase-substrate relationships (ssKSRs) is crucial for deciphering phosphorylation networks by linking kinomes to phosphoproteomes. However, currently available predictors for ssKSRs give rise to a large number of false-positive results because they use only a short sequence stretch around phosphosite as determinants of kinase specificity and do not consider the biological context of kinase-substrate recognition.'),
(78272, 2014, 'bio', 'Canto: an online tool for community literature curation', 'Rutherford, Kim M|Harris, Midori A|Lock, Antonia|Oliver, Stephen G|Wood, Valerie', 'Cambridge Systems Biology Centre, Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA and Department of Genetics, Evolution and Environment, and UCL Cancer Institute, University College London, Darwin Building, Gower Street, London WC1E 6BT, UKCambridge Systems Biology Centre, Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA and Department of Genetics, Evolution and Environment, and UCL Cancer Institute, University College London, Darwin Building, Gower Street, London WC1E 6BT, UK.|Cambridge Systems Biology Centre, Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA and Department of Genetics, Evolution and Environment, and UCL Cancer Institute, University College London, Darwin Building, Gower Street, London WC1E 6BT, UKCambridge Systems Biology Centre, Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA and Department of Genetics, Evolution and Environment, and UCL Cancer Institute, University College London, Darwin Building, Gower Street, London WC1E 6BT, UK.|Cambridge Systems Biology Centre, Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA and Department of Genetics, Evolution and Environment, and UCL Cancer Institute, University College London, Darwin Building, Gower Street, London WC1E 6BT, UK.|Cambridge Systems Biology Centre, Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA and Department of Genetics, Evolution and Environment, and UCL Cancer Institute, University College London, Darwin Building, Gower Street, London WC1E 6BT, UKCambridge Systems Biology Centre, Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA and Department of Genetics, Evolution and Environment, and UCL Cancer Institute, University College London, Darwin Building, Gower Street, London WC1E 6BT, UK.|Cambridge Systems Biology Centre, Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA and Department of Genetics, Evolution and Environment, and UCL Cancer Institute, University College London, Darwin Building, Gower Street, London WC1E 6BT, UKCambridge Systems Biology Centre, Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA and Department of Genetics, Evolution and Environment, and UCL Cancer Institute, University College London, Darwin Building, Gower Street, London WC1E 6BT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 27, 'Biological Ontologies|Databases, Factual|Internet|Schizosaccharomyces|Software', 'Journal Article', '10.1093/bioinformatics/btu103', '24574118', 'Detailed curation of published molecular data is essential for any model organism database. Community curation enables researchers to contribute data from their papers directly to databases, supplementing the activity of professional curators and improving coverage of a growing body of literature. We have developed Canto, a web-based tool that provides an intuitive curation interface for both curators and researchers, to support community curation in the fission yeast database, PomBase. Canto supports curation using OBO ontologies, and can be easily configured for use with any species.'),
(78273, 2014, 'bio', 'Derivative processes for modelling metabolic fluxes', 'Zurauskienxc4x97, Justina|Kirk, Paul|Thorne, Thomas|Pinney, John|Stumpf, Michael', 'Theoretical Systems Biology Group, Centre for Bioinformatics, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.|Theoretical Systems Biology Group, Centre for Bioinformatics, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.|Theoretical Systems Biology Group, Centre for Bioinformatics, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.|Theoretical Systems Biology Group, Centre for Bioinformatics, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.|Theoretical Systems Biology Group, Centre for Bioinformatics, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Bayes Theorem|Escherichia coli|Metabolic Networks and Pathways|Models, Biological|Nitrogen', 'Journal Article', '10.1093/bioinformatics/btu069', '24578401', 'One of the challenging questions in modelling biological systems is to characterize the functional forms of the processes that control and orchestrate molecular and cellular phenotypes. Recently proposed methods for the analysis of metabolic pathways, for example, dynamic flux estimation, can only provide estimates of the underlying fluxes at discrete time points but fail to capture the complete temporal behaviour. To describe the dynamic variation of the fluxes, we additionally require the assumption of specific functional forms that can capture the temporal behaviour. However, it also remains unclear how to address the noise which might be present in experimentally measured metabolite concentrations.'),
(78274, 2014, 'bio', 'ngsCAT: a tool to assess the efficiency of targeted enrichment sequencing', 'López-Domingo, Francisco J|Florido, Javier P|Rueda, Antonio|Dopazo, Joaquín|Santoyo-Lopez, Javier', 'Bioinformatics Department, Genomics and Bioinformatics Platform of Andalusia (GBPA), 41092 Seville, Computational Genomics Department, Centro de Investigación Príncipe Felipe, 46012 Valencia, Spain and Functional Genomics Node (INB), Centro de Investigación Príncipe Felipe, 46012 Valencia, Spain.|Bioinformatics Department, Genomics and Bioinformatics Platform of Andalusia (GBPA), 41092 Seville, Computational Genomics Department, Centro de Investigación Príncipe Felipe, 46012 Valencia, Spain and Functional Genomics Node (INB), Centro de Investigación Príncipe Felipe, 46012 Valencia, Spain.|Bioinformatics Department, Genomics and Bioinformatics Platform of Andalusia (GBPA), 41092 Seville, Computational Genomics Department, Centro de Investigación Príncipe Felipe, 46012 Valencia, Spain and Functional Genomics Node (INB), Centro de Investigación Príncipe Felipe, 46012 Valencia, Spain.|Bioinformatics Department, Genomics and Bioinformatics Platform of Andalusia (GBPA), 41092 Seville, Computational Genomics Department, Centro de Investigación Príncipe Felipe, 46012 Valencia, Spain and Functional Genomics Node (INB), Centro de Investigación Príncipe Felipe, 46012 Valencia, SpainBioinformatics Department, Genomics and Bioinformatics Platform of Andalusia (GBPA), 41092 Seville, Computational Genomics Department, Centro de Investigación Príncipe Felipe, 46012 Valencia, Spain and Functional Genomics Node (INB), Centro de Investigación Príncipe Felipe, 46012 Valencia, SpainBioinformatics Department, Genomics and Bioinformatics Platform of Andalusia (GBPA), 41092 Seville, Computational Genomics Department, Centro de Investigación Príncipe Felipe, 46012 Valencia, Spain and Functional Genomics Node (INB), Centro de Investigación Príncipe Felipe, 46012 Valencia, Spain.|Bioinformatics Department, Genomics and Bioinformatics Platform of Andalusia (GBPA), 41092 Seville, Computational Genomics Department, Centro de Investigación Príncipe Felipe, 46012 Valencia, Spain and Functional Genomics Node (INB), Centro de Investigación Príncipe Felipe, 46012 Valencia, Spain.', 'Spain|Spain|Spain|Spain|Spain', 3, 'Exome|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu108', '24578402', 'Targeted enrichment sequencing by next-generation sequencing is a common approach to interrogate specific loci or the whole exome in the human genome. The efficiency and the lack of bias in the enrichment process need to be assessed as a quality control step before performing downstream analysis of the sequence data. Tools that can report on the sensitivity, specificity, uniformity and other enrichment-specific features are needed.'),
(78275, 2014, 'bio', 'LASAGNA-Search 20: integrated transcription factor binding site search and visualization in a browser', 'Lee, Chih|Huang, Chun-Hsi', 'Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA.|Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA.', 'United States|United States', 29, 'Algorithms|Animals|Binding Sites|Gene Regulatory Networks|Genome|Humans|Internet|Mice|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btu115', '24578403', 'LASAGNA-Search 2.0 is an integrated webtool for transcription factor (TF) binding site search and visualization. The tool is based on the LASAGNA (Length-Aware Site Alignment Guided by Nucleotide Association) algorithm. It eliminates manual TF model collection and promoter sequence retrieval. Search results can be visualized locally or in the University of California Santa Cruz Genome Browser. Gene regulatory network inference based on the search results offers another way of visualization. A list of TFs and target genes is all a user needs to start using the tool. LASAGNA-Search 2.0 currently offers 1792 TF models and supports 15 species for automatic promoter retrieval and visualization in the University of California Santa Cruz Genome Browser. It is a user-friendly tool designed for non-bioinformaticians and is suitable for research and teaching. We describe important changes made since the initial release.'),
(78276, 2014, 'bio', 'Accurate computational prediction of the transcribed strand of CRISPR non-coding RNAs', 'Biswas, Ambarish|Fineran, Peter C|Brown, Chris M', 'Department of Biochemistry, Department of Microbiology and Immunology and Genetics Otago, University of Otago, Dunedin 9054, New Zealand.|Department of Biochemistry, Department of Microbiology and Immunology and Genetics Otago, University of Otago, Dunedin 9054, New ZealandDepartment of Biochemistry, Department of Microbiology and Immunology and Genetics Otago, University of Otago, Dunedin 9054, New Zealand.|Department of Biochemistry, Department of Microbiology and Immunology and Genetics Otago, University of Otago, Dunedin 9054, New ZealandDepartment of Biochemistry, Department of Microbiology and Immunology and Genetics Otago, University of Otago, Dunedin 9054, New Zealand.', 'New Zealand|New Zealand|New Zealand', 0, 'Algorithms|Archaea|Clustered Regularly Interspaced Short Palindromic Repeats|Nucleic Acid Conformation|RNA, Untranslated', 'Journal Article', '10.1093/bioinformatics/btu114', '24578404', 'CRISPR RNAs (crRNAs) are a type of small non-coding RNA that form a key part of an acquired immune system in prokaryotes. Specific prediction methods find crRNA-encoding loci in nearly half of sequenced bacterial, and three quarters of archaeal, species. These Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) arrays consist of repeat elements alternating with specific spacers. Generally one strand is transcribed, producing long pre-crRNAs, which are processed to short crRNAs that base pair with invading nucleic acids to facilitate their destruction. No current software for the discovery of CRISPR loci predicts the direction of crRNA transcription.'),
(78277, 2014, 'bio', 'Wrangling Galaxys reference data', 'Blankenberg, Daniel|Johnson, James E|Galaxy Team|Taylor, James|Nekrutenko, Anton', 'Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA, http://www.galaxyproject.org, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA, Department of Biology and Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322, USADepartment of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA, http://www.galaxyproject.org, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA, Department of Biology and Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322, USA.|Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA, http://www.galaxyproject.org, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA, Department of Biology and Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322, USA.|Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA, http://www.galaxyproject.org, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA, Department of Biology and Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322, USA.|Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA, http://www.galaxyproject.org, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA, Department of Biology and Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322, USADepartment of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA, http://www.galaxyproject.org, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA, Department of Biology and Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322, USADepartment of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA, http://www.galaxyproject.org, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA, Department of Biology and Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322, USA.|Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA, http://www.galaxyproject.org, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA, Department of Biology and Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322, USADepartment of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA, http://www.galaxyproject.org, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA, Department of Biology and Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322, USA.', 'United States|United States|United States|United States|United States', 0, 'Humans|Reproducibility of Results|Software', 'Journal Article', '10.1093/bioinformatics/btu119', '24585771', 'The Galaxy platform has developed into a fully featured collaborative workbench, with goals of inherently capturing provenance to enable reproducible data analysis, and of making it straightforward to run ones own server. However, many Galaxy platform tools rely on the presence of reference data, such as alignment indexes, to function efficiently. Until now, the building of this cache of data for Galaxy has been an error-prone manual process lacking reproducibility and provenance. The Galaxy Data Manager framework is an enhancement that changes the management of Galaxys built-in data cache from a manual procedure to an automated graphical user interface (GUI) driven process, which contains the same openness, reproducibility and provenance that is afforded to Galaxys analysis tools. Data Manager tools allow the Galaxy administrator to download, create and install additional datasets for any type of reference data in real time.'),
(78278, 2014, 'bio', 'Beyond the proteome: Mass Spectrometry Special Interest Group (MS-SIG) at ISMB/ECCB 2013', 'MS-SIG 2013 Organizers|Ryu, So Young|Payne, Samuel H|Schaab, Christoph|Xiao, Wenzhong', 'Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA, http://www.galaxyproject.org, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA, Department of Biology and Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322, USADepartment of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA, http://www.galaxyproject.org, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA, Department of Biology and Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322, USA.|Stanford Genome Technology Center, Stanford University, Palo Alto, CA 94304, Pacific Northwest National Laboratory, Richland, WA 99352, USA Max Planck Institute of Biochemistry and Evotec AG 82152, Martinsried, Germany and Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.|Stanford Genome Technology Center, Stanford University, Palo Alto, CA 94304, Pacific Northwest National Laboratory, Richland, WA 99352, USA Max Planck Institute of Biochemistry and Evotec AG 82152, Martinsried, Germany and Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.|Stanford Genome Technology Center, Stanford University, Palo Alto, CA 94304, Pacific Northwest National Laboratory, Richland, WA 99352, USA Max Planck Institute of Biochemistry and Evotec AG 82152, Martinsried, Germany and Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA Stanford Genome Technology Center, Stanford University, Palo Alto, CA 94304, Pacific Northwest National Laboratory, Richland, WA 99352, USA Max Planck Institute of Biochemistry and Evotec AG 82152, Martinsried, Germany and Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.|Stanford Genome Technology Center, Stanford University, Palo Alto, CA 94304, Pacific Northwest National Laboratory, Richland, WA 99352, USA Max Planck Institute of Biochemistry and Evotec AG 82152, Martinsried, Germany and Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA Stanford Genome Technology Center, Stanford University, Palo Alto, CA 94304, Pacific Northwest National Laboratory, Richland, WA 99352, USA Max Planck Institute of Biochemistry and Evotec AG 82152, Martinsried, Germany and Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.', 'United States|Germany|Germany|Germany|Germany', 0, 'Humans|Mass Spectrometry|Proteome|Proteomics|Software|Systems Biology', 'Congress', '10.1093/bioinformatics/btu116', '24590439', '-'),
(78279, 2014, 'bio', 'Tospovirus ambisense genomic RNA segments use almost complete repertoire of stable tetraloops in the intergenic region', 'Clabbers, Max T B|Olsthoorn, Rene C L|Gultyaev, Alexander P', 'Institute of Chemistry, Leiden University, 2300 RA Leiden and Department of Viroscience, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands.|Institute of Chemistry, Leiden University, 2300 RA Leiden and Department of Viroscience, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands.|Institute of Chemistry, Leiden University, 2300 RA Leiden and Department of Viroscience, Erasmus Medical Center, 3000 CA Rotterdam, The NetherlandsInstitute of Chemistry, Leiden University, 2300 RA Leiden and Department of Viroscience, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 0, 'DNA, Intergenic|Genome, Viral|Genomics|Nucleic Acid Conformation|RNA, Viral|Tospovirus', 'Journal Article', '10.1093/bioinformatics/btu122', '24590440', 'The intergenic regions of the ambisense RNA segments of viruses from the Tospovirus genus form large extended RNA structures that regulate virus replication. Using comparative structure analysis, we show the presence of conserved alternative conformations at the apical parts of these structures. In one conformation, a branched Y-shape, the 5-proximal hairpin arms are mostly capped by exceptionally stable tetraloop motifs. The tetraloop hairpins are folded in both virus and virus-complementary sense RNAs, and different tetraloops can functionally replace each other. Folding simulations show that the branched Y-shape structures can undergo a conformational transition to alternative extended rod-like conformations. Functional importance of both alternatives is supported by nucleotide covariations. The balanced equilibrium between alternative structures is evidenced by native gel electrophoresis of mutant RNA transcripts with shifted equilibria. The tetraloops play a role in the stability and dynamics of structures but may also be recognized by proteins involved in translation and/or replication.'),
(78280, 2014, 'bio', 'Protein fold recognition using geometric kernel data fusion', 'Zakeri, Pooya|Jeuris, Ben|Vandebril, Raf|Moreau, Yves', 'Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, iMinds Medical IT and Department of Computer Science, KU Leuven, 3001 Leuven, BelgiumDepartment of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, iMinds Medical IT and Department of Computer Science, KU Leuven, 3001 Leuven, Belgium.|Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, iMinds Medical IT and Department of Computer Science, KU Leuven, 3001 Leuven, Belgium.|Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, iMinds Medical IT and Department of Computer Science, KU Leuven, 3001 Leuven, Belgium.|Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, iMinds Medical IT and Department of Computer Science, KU Leuven, 3001 Leuven, BelgiumDepartment of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, iMinds Medical IT and Department of Computer Science, KU Leuven, 3001 Leuven, BelgiumDepartment of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, iMinds Medical IT and Department of Computer Science, KU Leuven, 3001 Leuven, Belgium.', 'Belgium|Belgium|Belgium|Belgium', 18, 'Algorithms|Pattern Recognition, Automated|Position-Specific Scoring Matrices|Protein Folding|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu118', '24590441', 'Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information.'),
(78281, 2014, 'bio', 'BicOverlapper 20: visual analysis for gene expression', 'Santamaría, Rodrigo|Therón, Roberto|Quintales, Luis', 'Department of Computer Science, University of Salamanca, 37008 Salamanca, Spain and Instituto de Biología Funcional y Genómica, CSIC/USAL, 37007 Salamanca, Spain.|Department of Computer Science, University of Salamanca, 37008 Salamanca, Spain and Instituto de Biología Funcional y Genómica, CSIC/USAL, 37007 Salamanca, Spain.|Department of Computer Science, University of Salamanca, 37008 Salamanca, Spain and Instituto de Biología Funcional y Genómica, CSIC/USAL, 37007 Salamanca, SpainDepartment of Computer Science, University of Salamanca, 37008 Salamanca, Spain and Instituto de Biología Funcional y Genómica, CSIC/USAL, 37007 Salamanca, Spain.', 'Spain|Spain|Spain', 0, 'Computer Graphics|Gene Expression Profiling|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btu120', '24590442', 'Systems biology demands the use of several point of views to get a more comprehensive understanding of biological problems. This usually leads to take into account different data regarding the problem at hand, but it also has to do with using different perspectives of the same data. This multifaceted aspect of systems biology often requires the use of several tools, and it is often hard to get a seamless integration of all of them, which would help the analyst to have an interactive discourse with the data.'),
(78282, 2014, 'bio', 'Challenges in RNA virus bioinformatics', 'Marz, Manja|Beerenwinkel, Niko|Drosten, Christian|Fricke, Markus|Frishman, Dmitrij|Hofacker, Ivo L|Hoffmann, Dieter|Middendorf, Martin|Rattei, Thomas|Stadler, Peter F|Töpfer, Armin', 'Friedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz Center Munich-German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany, Moscow Institute of Physics and Technology, Institutskii Per. 9, Moscow Region, Dolgoprudny 141700, Russia, Institut für theoretische Chemie, Universität Wien, Währingerstraße 17, A-1090 Wien, Austria, Institute of Virology, Technical University of Munich, Trogerstr. 30, 81675 München, Germany, University of Leipzig, Faculty of Mathematics and Computer Science, Institute for Computer Science, Augustusplatz 10, 04109 Leipzig, Germany, Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, Universität Wien, Althanstraße 14, 1090 Wien, Austria, Department of Computer Science and Interdisciplinary Center of Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany and The Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA.|Friedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz Center Munich-German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany, Moscow Institute of Physics and Technology, Institutskii Per. 9, Moscow Region, Dolgoprudny 141700, Russia, Institut für theoretische Chemie, Universität Wien, Währingerstraße 17, A-1090 Wien, Austria, Institute of Virology, Technical University of Munich, Trogerstr. 30, 81675 München, Germany, University of Leipzig, Faculty of Mathematics and Computer Science, Institute for Computer Science, Augustusplatz 10, 04109 Leipzig, Germany, Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, Universität Wien, Althanstraße 14, 1090 Wien, Austria, Department of Computer Science and Interdisciplinary Center of Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany and The Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USAFriedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz |Friedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz Center Munich-German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany, Moscow Institute of Physics and Technology, Institutskii Per. 9, Moscow Region, Dolgoprudny 141700, Russia, Institut für theoretische Chemie, Universität Wien, Währingerstraße 17, A-1090 Wien, Austria, Institute of Virology, Technical University of Munich, Trogerstr. 30, 81675 München, Germany, University of Leipzig, Faculty of Mathematics and Computer Science, Institute for Computer Science, Augustusplatz 10, 04109 Leipzig, Germany, Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, Universität Wien, Althanstraße 14, 1090 Wien, Austria, Department of Computer Science and Interdisciplinary Center of Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany and The Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA.|Friedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz Center Munich-German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany, Moscow Institute of Physics and Technology, Institutskii Per. 9, Moscow Region, Dolgoprudny 141700, Russia, Institut für theoretische Chemie, Universität Wien, Währingerstraße 17, A-1090 Wien, Austria, Institute of Virology, Technical University of Munich, Trogerstr. 30, 81675 München, Germany, University of Leipzig, Faculty of Mathematics and Computer Science, Institute for Computer Science, Augustusplatz 10, 04109 Leipzig, Germany, Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, Universität Wien, Althanstraße 14, 1090 Wien, Austria, Department of Computer Science and Interdisciplinary Center of Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany and The Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA.|Friedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz Center Munich-German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany, Moscow Institute of Physics and Technology, Institutskii Per. 9, Moscow Region, Dolgoprudny 141700, Russia, Institut für theoretische Chemie, Universität Wien, Währingerstraße 17, A-1090 Wien, Austria, Institute of Virology, Technical University of Munich, Trogerstr. 30, 81675 München, Germany, University of Leipzig, Faculty of Mathematics and Computer Science, Institute for Computer Science, Augustusplatz 10, 04109 Leipzig, Germany, Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, Universität Wien, Althanstraße 14, 1090 Wien, Austria, Department of Computer Science and Interdisciplinary Center of Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany and The Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USAFriedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz |Friedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz Center Munich-German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany, Moscow Institute of Physics and Technology, Institutskii Per. 9, Moscow Region, Dolgoprudny 141700, Russia, Institut für theoretische Chemie, Universität Wien, Währingerstraße 17, A-1090 Wien, Austria, Institute of Virology, Technical University of Munich, Trogerstr. 30, 81675 München, Germany, University of Leipzig, Faculty of Mathematics and Computer Science, Institute for Computer Science, Augustusplatz 10, 04109 Leipzig, Germany, Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, Universität Wien, Althanstraße 14, 1090 Wien, Austria, Department of Computer Science and Interdisciplinary Center of Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany and The Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA.|Friedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz Center Munich-German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany, Moscow Institute of Physics and Technology, Institutskii Per. 9, Moscow Region, Dolgoprudny 141700, Russia, Institut für theoretische Chemie, Universität Wien, Währingerstraße 17, A-1090 Wien, Austria, Institute of Virology, Technical University of Munich, Trogerstr. 30, 81675 München, Germany, University of Leipzig, Faculty of Mathematics and Computer Science, Institute for Computer Science, Augustusplatz 10, 04109 Leipzig, Germany, Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, Universität Wien, Althanstraße 14, 1090 Wien, Austria, Department of Computer Science and Interdisciplinary Center of Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany and The Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA.|Friedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz Center Munich-German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany, Moscow Institute of Physics and Technology, Institutskii Per. 9, Moscow Region, Dolgoprudny 141700, Russia, Institut für theoretische Chemie, Universität Wien, Währingerstraße 17, A-1090 Wien, Austria, Institute of Virology, Technical University of Munich, Trogerstr. 30, 81675 München, Germany, University of Leipzig, Faculty of Mathematics and Computer Science, Institute for Computer Science, Augustusplatz 10, 04109 Leipzig, Germany, Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, Universität Wien, Althanstraße 14, 1090 Wien, Austria, Department of Computer Science and Interdisciplinary Center of Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany and The Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA.|Friedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz Center Munich-German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany, Moscow Institute of Physics and Technology, Institutskii Per. 9, Moscow Region, Dolgoprudny 141700, Russia, Institut für theoretische Chemie, Universität Wien, Währingerstraße 17, A-1090 Wien, Austria, Institute of Virology, Technical University of Munich, Trogerstr. 30, 81675 München, Germany, University of Leipzig, Faculty of Mathematics and Computer Science, Institute for Computer Science, Augustusplatz 10, 04109 Leipzig, Germany, Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, Universität Wien, Althanstraße 14, 1090 Wien, Austria, Department of Computer Science and Interdisciplinary Center of Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany and The Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA.|Friedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz Center Munich-German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany, Moscow Institute of Physics and Technology, Institutskii Per. 9, Moscow Region, Dolgoprudny 141700, Russia, Institut für theoretische Chemie, Universität Wien, Währingerstraße 17, A-1090 Wien, Austria, Institute of Virology, Technical University of Munich, Trogerstr. 30, 81675 München, Germany, University of Leipzig, Faculty of Mathematics and Computer Science, Institute for Computer Science, Augustusplatz 10, 04109 Leipzig, Germany, Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, Universität Wien, Althanstraße 14, 1090 Wien, Austria, Department of Computer Science and Interdisciplinary Center of Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany and The Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USAFriedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz |Friedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz Center Munich-German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany, Moscow Institute of Physics and Technology, Institutskii Per. 9, Moscow Region, Dolgoprudny 141700, Russia, Institut für theoretische Chemie, Universität Wien, Währingerstraße 17, A-1090 Wien, Austria, Institute of Virology, Technical University of Munich, Trogerstr. 30, 81675 München, Germany, University of Leipzig, Faculty of Mathematics and Computer Science, Institute for Computer Science, Augustusplatz 10, 04109 Leipzig, Germany, Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, Universität Wien, Althanstraße 14, 1090 Wien, Austria, Department of Computer Science and Interdisciplinary Center of Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany and The Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USAFriedrich-Schiller-University Jena, Faculty of Mathematics und Computer Science, Leutragraben 1, 07743 Jena, Germany, Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, SIB Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland, Universitätsklinikum Bonn, Institut für Virologie, Sigmund-Freud-Str. 25, 53127 Bonn, Technische Universität Muenchen, Wissenschaftszentrum Weihenstephan, Am Forum 1, 85354 Freising, Helmholtz ', 'Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria', 0, 'Animals|Computational Biology|Evolution, Molecular|High-Throughput Nucleotide Sequencing|Humans|Phylogeny|RNA Viruses|RNA, Viral', 'Journal Article', '10.1093/bioinformatics/btu105', '24590443', 'Computer-assisted studies of structure, function and evolution of viruses remains a neglected area of research. The attention of bioinformaticians to this interesting and challenging field is far from commensurate with its medical and biotechnological importance. It is telling that out of >200 talks held at ISMB 2013, the largest international bioinformatics conference, only one presentation explicitly dealt with viruses. In contrast to many broad, established and well-organized bioinformatics communities (e.g. structural genomics, ontologies, next-generation sequencing, expression analysis), research groups focusing on viruses can probably be counted on the fingers of two hands.'),
(78283, 2014, 'bio', 'The automated function prediction SIG looks back at 2013 and prepares for 2014', 'Wass, Mark N|Mooney, Sean D|Linial, Michal|Radivojac, Predrag|Friedberg, Iddo', 'School of Biosciences, University of Kent, Canterbury, Kent CT2 7NH, UK, The Buck Institute for Research on Aging, Novato, CA 94945, USA, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Jerusalem Israel, Department of Computer Science and Informatics, Indiana University, Bloomington, IN 47405, USA, Department of Microbiology, Miami University and Department of Computer Science and Software Engineering, Miami University, Oxford, OH 45056, USA.|School of Biosciences, University of Kent, Canterbury, Kent CT2 7NH, UK, The Buck Institute for Research on Aging, Novato, CA 94945, USA, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Jerusalem Israel, Department of Computer Science and Informatics, Indiana University, Bloomington, IN 47405, USA, Department of Microbiology, Miami University and Department of Computer Science and Software Engineering, Miami University, Oxford, OH 45056, USA.|School of Biosciences, University of Kent, Canterbury, Kent CT2 7NH, UK, The Buck Institute for Research on Aging, Novato, CA 94945, USA, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Jerusalem Israel, Department of Computer Science and Informatics, Indiana University, Bloomington, IN 47405, USA, Department of Microbiology, Miami University and Department of Computer Science and Software Engineering, Miami University, Oxford, OH 45056, USA.|School of Biosciences, University of Kent, Canterbury, Kent CT2 7NH, UK, The Buck Institute for Research on Aging, Novato, CA 94945, USA, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Jerusalem Israel, Department of Computer Science and Informatics, Indiana University, Bloomington, IN 47405, USA, Department of Microbiology, Miami University and Department of Computer Science and Software Engineering, Miami University, Oxford, OH 45056, USA.|School of Biosciences, University of Kent, Canterbury, Kent CT2 7NH, UK, The Buck Institute for Research on Aging, Novato, CA 94945, USA, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Jerusalem Israel, Department of Computer Science and Informatics, Indiana University, Bloomington, IN 47405, USA, Department of Microbiology, Miami University and Department of Computer Science and Software Engineering, Miami University, Oxford, OH 45056, USASchool of Biosciences, University of Kent, Canterbury, Kent CT2 7NH, UK, The Buck Institute for Research on Aging, Novato, CA 94945, USA, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Jerusalem Israel, Department of Computer Science and Informatics, Indiana University, Bloomington, IN 47405, USA, Department of Microbiology, Miami University and Department of Computer Science and Software Engineering, Miami University, Oxford, OH 45056, USA.', 'India|India|India|India|India', 9, 'Computational Biology|Proteins|Sequence Analysis, Protein', 'Congress', '10.1093/bioinformatics/btu117', '24590444', '-');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78284, 2014, 'bio', 'FragrUs: knowledge-based sampling of protein backbone conformations for de novo structure-based protein design', 'Bonet, Jaume|Segura, Joan|Planas-Iglesias, Joan|Oliva, Baldomero|Fernandez-Fuentes, Narcis', 'Structural Bioinformatics Lab (GRIB), Universitat Pompeu Fabra, Barcelona, Catalonia 08003, Spain, Department of Structure of Macromolecules, CNB-CSIC, Cantoblanco, 28049 Madrid, Spain and Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA Ceredigion, UK.|Structural Bioinformatics Lab (GRIB), Universitat Pompeu Fabra, Barcelona, Catalonia 08003, Spain, Department of Structure of Macromolecules, CNB-CSIC, Cantoblanco, 28049 Madrid, Spain and Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA Ceredigion, UK.|Structural Bioinformatics Lab (GRIB), Universitat Pompeu Fabra, Barcelona, Catalonia 08003, Spain, Department of Structure of Macromolecules, CNB-CSIC, Cantoblanco, 28049 Madrid, Spain and Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA Ceredigion, UK.|Structural Bioinformatics Lab (GRIB), Universitat Pompeu Fabra, Barcelona, Catalonia 08003, Spain, Department of Structure of Macromolecules, CNB-CSIC, Cantoblanco, 28049 Madrid, Spain and Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA Ceredigion, UK.|Structural Bioinformatics Lab (GRIB), Universitat Pompeu Fabra, Barcelona, Catalonia 08003, Spain, Department of Structure of Macromolecules, CNB-CSIC, Cantoblanco, 28049 Madrid, Spain and Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA Ceredigion, UK.', 'Spain|Spain|Spain|Spain|Spain', 0, 'Knowledge Bases|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu129', '24603983', 'The remodeling of short fragment(s) of the protein backbone to accommodate new function(s), fine-tune binding specificities or change/create novel protein interactions is a common task in structure-based computational design. Alternative backbone conformations can be generated de novo or by redeploying existing fragments extracted from protein structures i.e. knowledge-based. We present FragrUs, a web server designed to sample alternative protein backbone conformations in loop regions. The method relies on a database of super secondary structural motifs called smotifs. Thus, sampling of conformations reflects structurally feasible fragments compiled from existing protein structures. Availability and implementation FragrUs has been implemented as web application and is available at http://www.bioinsilico.org/FRAGRUS.'),
(78285, 2014, 'bio', 'Induction of T-cell memory by a dendritic cell vaccine: a computational model', 'Pappalardo, Francesco|Pennisi, Marzio|Ricupito, Alessia|Topputo, Francesco|Bellone, Matteo', 'Department of Drug Science and Department of Mathematics and Computer Science, University of Catania, 95125 Catania, San Raffaele Scientific Institute and Università Vita Salute San Raffaele, 20132 Milan, Politecnico di Milano, 20133 Milano and San Raffaele Scientific Institute, 20132 Milan, Italy.|Department of Drug Science and Department of Mathematics and Computer Science, University of Catania, 95125 Catania, San Raffaele Scientific Institute and Università Vita Salute San Raffaele, 20132 Milan, Politecnico di Milano, 20133 Milano and San Raffaele Scientific Institute, 20132 Milan, ItalyDepartment of Drug Science and Department of Mathematics and Computer Science, University of Catania, 95125 Catania, San Raffaele Scientific Institute and Università Vita Salute San Raffaele, 20132 Milan, Politecnico di Milano, 20133 Milano and San Raffaele Scientific Institute, 20132 Milan, Italy.|Department of Drug Science and Department of Mathematics and Computer Science, University of Catania, 95125 Catania, San Raffaele Scientific Institute and Università Vita Salute San Raffaele, 20132 Milan, Politecnico di Milano, 20133 Milano and San Raffaele Scientific Institute, 20132 Milan, Italy.|Department of Drug Science and Department of Mathematics and Computer Science, University of Catania, 95125 Catania, San Raffaele Scientific Institute and Università Vita Salute San Raffaele, 20132 Milan, Politecnico di Milano, 20133 Milano and San Raffaele Scientific Institute, 20132 Milan, Italy.|Department of Drug Science and Department of Mathematics and Computer Science, University of Catania, 95125 Catania, San Raffaele Scientific Institute and Università Vita Salute San Raffaele, 20132 Milan, Politecnico di Milano, 20133 Milano and San Raffaele Scientific Institute, 20132 Milan, Italy.', 'Italy|Italy|Italy|Italy|Italy', 0, 'Animals|Antigens|Cancer Vaccines|Dendritic Cells|Immunologic Memory|Mice, Inbred C57BL|T-Lymphocytes|Vaccines', 'Journal Article', '10.1093/bioinformatics/btu059', '24603984', 'Although results from phase III clinical trials substantially support the use of prophylactic and therapeutic vaccines against cancer, what has yet to be defined is how many and how frequent boosts are needed to sustain a long-lasting and protecting memory T-cell response against tumor antigens. Common experience is that such preclinical tests require the sacrifice of a relatively large number of animals, and are particularly time- and money-consuming.'),
(78286, 2014, 'bio', 'PyRAD: assembly of de novo RADseq loci for phylogenetic analyses', 'Eaton, Deren A R', 'Committee on Evolutionary Biology, University of Chicago, 1025 E. 57th St. Chicago, IL 60637, USA and Botany Department, Field Museum of Natural History, 1400 S. Lake Shore Dr. Chicago, IL 60605, USACommittee on Evolutionary Biology, University of Chicago, 1025 E. 57th St. Chicago, IL 60637, USA and Botany Department, Field Museum of Natural History, 1400 S. Lake Shore Dr. Chicago, IL 60605, USA.', 'United States', 0, 'Algorithms|Cluster Analysis|Genetic Loci|High-Throughput Nucleotide Sequencing|Phylogeny|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu121', '24603985', 'Restriction-site-associated genomic markers are a powerful tool for investigating evolutionary questions at the population level, but are limited in their utility at deeper phylogenetic scales where fewer orthologous loci are typically recovered across disparate taxa. While this limitation stems in part from mutations to restriction recognition sites that disrupt data generation, an additional source of data loss comes from the failure to identify homology during bioinformatic analyses. Clustering methods that allow for lower similarity thresholds and the inclusion of indel variation will perform better at assembling RADseq loci at the phylogenetic scale.'),
(78287, 2014, 'bio', 'Estimating optimal window size for analysis of low-coverage next-generation sequence data', 'Gusnanto, Arief|Taylor, Charles C|Nafisah, Ibrahim|Wood, Henry M|Rabbitts, Pamela|Berri, Stefano', 'Department of Statistics, University of Leeds, Leeds LS2 9JT, United Kingdom, Department of Statistics, Faculty of Science, King Saud University, Riyadh, Saudi Arabia, Leeds Institute Cancer and Pathology, University of Leeds, Leeds LS9 7TF, UK and Illumina UK Ltd., Chesterford Research Park, Saffron Walden, CB10 1XL, UK.|Department of Statistics, University of Leeds, Leeds LS2 9JT, United Kingdom, Department of Statistics, Faculty of Science, King Saud University, Riyadh, Saudi Arabia, Leeds Institute Cancer and Pathology, University of Leeds, Leeds LS9 7TF, UK and Illumina UK Ltd., Chesterford Research Park, Saffron Walden, CB10 1XL, UK.|Department of Statistics, University of Leeds, Leeds LS2 9JT, United Kingdom, Department of Statistics, Faculty of Science, King Saud University, Riyadh, Saudi Arabia, Leeds Institute Cancer and Pathology, University of Leeds, Leeds LS9 7TF, UK and Illumina UK Ltd., Chesterford Research Park, Saffron Walden, CB10 1XL, UKDepartment of Statistics, University of Leeds, Leeds LS2 9JT, United Kingdom, Department of Statistics, Faculty of Science, King Saud University, Riyadh, Saudi Arabia, Leeds Institute Cancer and Pathology, University of Leeds, Leeds LS9 7TF, UK and Illumina UK Ltd., Chesterford Research Park, Saffron Walden, CB10 1XL, UK.|Department of Statistics, University of Leeds, Leeds LS2 9JT, United Kingdom, Department of Statistics, Faculty of Science, King Saud University, Riyadh, Saudi Arabia, Leeds Institute Cancer and Pathology, University of Leeds, Leeds LS9 7TF, UK and Illumina UK Ltd., Chesterford Research Park, Saffron Walden, CB10 1XL, UK.|Department of Statistics, University of Leeds, Leeds LS2 9JT, United Kingdom, Department of Statistics, Faculty of Science, King Saud University, Riyadh, Saudi Arabia, Leeds Institute Cancer and Pathology, University of Leeds, Leeds LS9 7TF, UK and Illumina UK Ltd., Chesterford Research Park, Saffron Walden, CB10 1XL, UK.|Department of Statistics, University of Leeds, Leeds LS2 9JT, United Kingdom, Department of Statistics, Faculty of Science, King Saud University, Riyadh, Saudi Arabia, Leeds Institute Cancer and Pathology, University of Leeds, Leeds LS9 7TF, UK and Illumina UK Ltd., Chesterford Research Park, Saffron Walden, CB10 1XL, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Likelihood Functions|Lung Neoplasms|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu123', '24603986', 'Current high-throughput sequencing has greatly transformed genome sequence analysis. In the context of very low-coverage sequencing (<0.1xc3x97), performing binning or windowing on mapped short sequences (reads) is critical to extract genomic information of interest for further evaluation, such as copy-number alteration analysis. If the window size is too small, many windows will exhibit zero counts and almost no pattern can be observed. In contrast, if the window size is too wide, the patterns or genomic features will be smoothed out. Our objective is to identify an optimal window size in between the two extremes.'),
(78288, 2014, 'bio', 'DMAP: differential methylation analysis package for RRBS and WGBS data', 'Stockwell, Peter A|Chatterjee, Aniruddha|Rodger, Euan J|Morison, Ian M', 'Department of Biochemistry, University of Otago, 710 Cumberland Street, Dunedin 9054, New Zealand, Department of Pathology, Dunedin School of Medicine, University of Otago, 270 Great King Street, Dunedin 9054, New Zealand and Gravida: National Centre for Growth and Development, 2-6 Park Ave, Grafton, Auckland 1142, New Zealand.|Department of Biochemistry, University of Otago, 710 Cumberland Street, Dunedin 9054, New Zealand, Department of Pathology, Dunedin School of Medicine, University of Otago, 270 Great King Street, Dunedin 9054, New Zealand and Gravida: National Centre for Growth and Development, 2-6 Park Ave, Grafton, Auckland 1142, New ZealandDepartment of Biochemistry, University of Otago, 710 Cumberland Street, Dunedin 9054, New Zealand, Department of Pathology, Dunedin School of Medicine, University of Otago, 270 Great King Street, Dunedin 9054, New Zealand and Gravida: National Centre for Growth and Development, 2-6 Park Ave, Grafton, Auckland 1142, New Zealand.|Department of Biochemistry, University of Otago, 710 Cumberland Street, Dunedin 9054, New Zealand, Department of Pathology, Dunedin School of Medicine, University of Otago, 270 Great King Street, Dunedin 9054, New Zealand and Gravida: National Centre for Growth and Development, 2-6 Park Ave, Grafton, Auckland 1142, New Zealand.|Department of Biochemistry, University of Otago, 710 Cumberland Street, Dunedin 9054, New Zealand, Department of Pathology, Dunedin School of Medicine, University of Otago, 270 Great King Street, Dunedin 9054, New Zealand and Gravida: National Centre for Growth and Development, 2-6 Park Ave, Grafton, Auckland 1142, New Zealand.', 'New Zealand|New Zealand|New Zealand|New Zealand', 0, 'CpG Islands|DNA Methylation|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu126', '24608764', 'The rapid development of high-throughput sequencing technologies has enabled epigeneticists to quantify DNA methylation on a massive scale. Progressive increase in sequencing capacity present challenges in terms of processing analysis and the interpretation of the large amount of data, investigating differential methylation between genome-scale data from multiple samples highlights this challenge.'),
(78289, 2014, 'bio', 'The Bio-Community Perl toolkit for microbial ecology', 'Angly, Florent E|Fields, Christopher J|Tyson, Gene W', 'Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, Level 5, Molecular Biosciences Building (76), The University of Queensland, Brisbane St Lucia, QLD 4072, Australia and HPCBio, Carver Biotechnology Center, Institute for Genomic Biology, 1206 West Gregory Drive | MC-195, Urbana, IL 61801, USA.|Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, Level 5, Molecular Biosciences Building (76), The University of Queensland, Brisbane St Lucia, QLD 4072, Australia and HPCBio, Carver Biotechnology Center, Institute for Genomic Biology, 1206 West Gregory Drive | MC-195, Urbana, IL 61801, USA.|Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, Level 5, Molecular Biosciences Building (76), The University of Queensland, Brisbane St Lucia, QLD 4072, Australia and HPCBio, Carver Biotechnology Center, Institute for Genomic Biology, 1206 West Gregory Drive | MC-195, Urbana, IL 61801, USA.', 'Australia|United States|Australia|United States|Australia|United States', 0, 'Computational Biology|Ecosystem|Humans|Microbiological Techniques|Microbiology|Software Design', 'Journal Article', '10.1093/bioinformatics/btu130', '24618462', 'The development of bioinformatic solutions for microbial ecology in Perl is limited by the lack of modules to represent and manipulate microbial community profiles from amplicon and meta-omics studies. Here we introduce Bio-Community, an open-source, collaborative toolkit that extends BioPerl. Bio-Community interfaces with commonly used programs using various file formats, including BIOM, and provides operations such as rarefaction and taxonomic summaries. Bio-Community will help bioinformaticians to quickly piece together custom analysis pipelines and develop novel software. Availability an implementation: Bio-Community is cross-platform Perl code available from http://search.cpan.org/dist/Bio-Community under the Perl license. A readme file describes software installation and how to contribute.'),
(78290, 2014, 'bio', 'A gradient-boosting approach for filtering de novo mutations in parent-offspring trios', 'Liu, Yongzhuang|Li, Bingshan|Tan, Renjie|Zhu, Xiaolin|Wang, Yadong', 'School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China, Center for Human Genome Variation, Duke University, Durham, NC 27708 and Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37235, USASchool of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China, Center for Human Genome Variation, Duke University, Durham, NC 27708 and Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37235, USA.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China, Center for Human Genome Variation, Duke University, Durham, NC 27708 and Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37235, USA.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China, Center for Human Genome Variation, Duke University, Durham, NC 27708 and Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37235, USASchool of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China, Center for Human Genome Variation, Duke University, Durham, NC 27708 and Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37235, USA.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China, Center for Human Genome Variation, Duke University, Durham, NC 27708 and Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37235, USA.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China, Center for Human Genome Variation, Duke University, Durham, NC 27708 and Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37235, USA.', 'China|China|China|China|China', 0, 'Algorithms|Artificial Intelligence|Exome|Female|Genome|Humans|Mutation|Software', 'Journal Article', '10.1093/bioinformatics/btu141', '24618463', 'Whole-genome and -exome sequencing on parent-offspring trios is a powerful approach to identifying disease-associated genes by detecting de novo mutations in patients. Accurate detection of de novo mutations from sequencing data is a critical step in trio-based genetic studies. Existing bioinformatic approaches usually yield high error rates due to sequencing artifacts and alignment issues, which may either miss true de novo mutations or call too many false ones, making downstream validation and analysis difficult. In particular, current approaches have much worse specificity than sensitivity, and developing effective filters to discriminate genuine from spurious de novo mutations remains an unsolved challenge.'),
(78291, 2014, 'bio', 'The Biological Reference Repository (BioR): a rapid and flexible system for genomics annotation', 'Kocher, Jean-Pierre A|Quest, Daniel J|Duffy, Patrick|Meiners, Michael A|Moore, Raymond M|Rider, David|Hossain, Asif|Hart, Steven N|Dinu, Valentin', 'Division of Biomedical Statistics and Informatics, Department of Health Sciences Research and Department of Research IT, Mayo Clinic, Rochester, MN 55905, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research and Department of Research IT, Mayo Clinic, Rochester, MN 55905, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research and Department of Research IT, Mayo Clinic, Rochester, MN 55905, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research and Department of Research IT, Mayo Clinic, Rochester, MN 55905, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research and Department of Research IT, Mayo Clinic, Rochester, MN 55905, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research and Department of Research IT, Mayo Clinic, Rochester, MN 55905, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research and Department of Research IT, Mayo Clinic, Rochester, MN 55905, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research and Department of Research IT, Mayo Clinic, Rochester, MN 55905, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research and Department of Research IT, Mayo Clinic, Rochester, MN 55905, USA and Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Genomics|Software Design', 'Journal Article', '10.1093/bioinformatics/btu137', '24618464', 'The Biological Reference Repository (BioR) is a toolkit for annotating variants. BioR stores public and user-specific annotation sources in indexed JSON-encoded flat files (catalogs). The BioR toolkit provides the functionality to combine and retrieve annotation from these catalogs via the command-line interface. Several catalogs from commonly used annotation sources and instructions for creating user-specific catalogs are provided. Commands from the toolkit can be combined with other UNIX commands for advanced annotation processing. We also provide instructions for the development of custom annotation pipelines.'),
(78292, 2014, 'bio', 'A personalized committee classification approach to improving prediction of breast cancer metastasis', 'Jahid, Md Jamiul|Huang, Tim H|Ruan, Jianhua', 'Department of Computer Science, University of Texas at San Antonio, San Antonio, TX 78249, USA, Department of Molecular Medicine and Cancer Therapy & Research Center, University of Texas Health Science Center, San Antonio, TX 78229, USA.|Department of Computer Science, University of Texas at San Antonio, San Antonio, TX 78249, USA, Department of Molecular Medicine and Cancer Therapy & Research Center, University of Texas Health Science Center, San Antonio, TX 78229, USADepartment of Computer Science, University of Texas at San Antonio, San Antonio, TX 78249, USA, Department of Molecular Medicine and Cancer Therapy & Research Center, University of Texas Health Science Center, San Antonio, TX 78229, USA.|Department of Computer Science, University of Texas at San Antonio, San Antonio, TX 78249, USA, Department of Molecular Medicine and Cancer Therapy & Research Center, University of Texas Health Science Center, San Antonio, TX 78229, USADepartment of Computer Science, University of Texas at San Antonio, San Antonio, TX 78249, USA, Department of Molecular Medicine and Cancer Therapy & Research Center, University of Texas Health Science Center, San Antonio, TX 78229, USA.', 'United States|United States|United States', 0, 'Algorithms|Breast Neoplasms|Cluster Analysis|Datasets as Topic|Humans|Neoplasm Metastasis', 'Journal Article', '10.1093/bioinformatics/btu128', '24618465', 'Metastasis prediction is a well-known problem in breast cancer research. As breast cancer is a complex and heterogeneous disease with many molecular subtypes, predictive models trained for one cohort often perform poorly on other cohorts, and a combined model may be suboptimal for individual patients. Furthermore, attempting to develop subtype-specific models is hindered by the ambiguity and stereotypical definitions of subtypes.'),
(78293, 2014, 'bio', 'FISH: fast and accurate diploid genotype imputation via segmental hidden Markov model', 'Zhang, Lei|Pei, Yu-Fang|Fu, Xiaoying|Lin, Yong|Wang, Yu-Ping|Deng, Hong-Wen', 'School of Public Health, Xian Jiaotong University, Shaanxi, China, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, USA and Center of System Biomedical Sciences, University of Shanghai for Science and Technology, Shanghai, ChinaSchool of Public Health, Xian Jiaotong University, Shaanxi, China, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, USA and Center of System Biomedical Sciences, University of Shanghai for Science and Technology, Shanghai, China.|School of Public Health, Xian Jiaotong University, Shaanxi, China, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, USA and Center of System Biomedical Sciences, University of Shanghai for Science and Technology, Shanghai, ChinaSchool of Public Health, Xian Jiaotong University, Shaanxi, China, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, USA and Center of System Biomedical Sciences, University of Shanghai for Science and Technology, Shanghai, China.|School of Public Health, Xian Jiaotong University, Shaanxi, China, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, USA and Center of System Biomedical Sciences, University of Shanghai for Science and Technology, Shanghai, China.|School of Public Health, Xian Jiaotong University, Shaanxi, China, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, USA and Center of System Biomedical Sciences, University of Shanghai for Science and Technology, Shanghai, China.|School of Public Health, Xian Jiaotong University, Shaanxi, China, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, USA and Center of System Biomedical Sciences, University of Shanghai for Science and Technology, Shanghai, China.|School of Public Health, Xian Jiaotong University, Shaanxi, China, Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, USA and Center of System Biomedical Sciences, University of Shanghai for Science and Technology, Shanghai, China.', 'China|China|China|China|China|China', 0, 'Algorithms|Diploidy|Genotype|Haplotypes|High-Throughput Nucleotide Sequencing|Markov Chains|Software', 'Journal Article', '10.1093/bioinformatics/btu143', '24618466', 'Fast and accurate genotype imputation is necessary for facilitating gene-mapping studies, especially with the ever increasing numbers of both common and rare variants generated by high-throughput-sequencing experiments. However, most of the existing imputation approaches suffer from either inaccurate results or heavy computational demand.'),
(78294, 2014, 'bio', 'An adaptive workflow coupled with Random Forest algorithm to identify intact N-glycopeptides detected from mass spectrometry', 'Liang, Suh-Yuen|Wu, Sz-Wei|Pu, Tsung-Hsien|Chang, Fang-Yu|Khoo, Kay-Hooi', 'Core Facilities for Protein Structural Analysis at Institute of Biological Chemistry and Institute of Biological Chemistry, Academia Sinica, Taipei 115, Taiwan.|Core Facilities for Protein Structural Analysis at Institute of Biological Chemistry and Institute of Biological Chemistry, Academia Sinica, Taipei 115, Taiwan.|Core Facilities for Protein Structural Analysis at Institute of Biological Chemistry and Institute of Biological Chemistry, Academia Sinica, Taipei 115, Taiwan.|Core Facilities for Protein Structural Analysis at Institute of Biological Chemistry and Institute of Biological Chemistry, Academia Sinica, Taipei 115, Taiwan.|Core Facilities for Protein Structural Analysis at Institute of Biological Chemistry and Institute of Biological Chemistry, Academia Sinica, Taipei 115, Taiwan.', '-|-|-|-|-', 14, 'Algorithms|Animals|Artificial Intelligence|Chromatography, High Pressure Liquid|Glycopeptides|Herpesvirus 2, Human|Humans|Mass Spectrometry|Mice|Workflow', 'Journal Article', '10.1093/bioinformatics/btu139', '24618467', 'Despite many attempts for algorithm development in recent years, automated identification of intact glycopeptides from LC-MS(2) spectral data is still a challenge in both sensitivity and precision.'),
(78295, 2014, 'bio', 'Genome-wide quantitative analysis of DNA methylation from bisulfite sequencing data', 'Akman, Kemal|Haaf, Thomas|Gravina, Silvia|Vijg, Jan|Tresch, Achim', 'Tresch Group, Max Planck Institute for Plant Breeding Research, 50829 Cologne, Germany, AG Haaf, Institute of Human Genetics, Julius Maximilians University, 97070 Wuerzburg, Germany and Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA.|Tresch Group, Max Planck Institute for Plant Breeding Research, 50829 Cologne, Germany, AG Haaf, Institute of Human Genetics, Julius Maximilians University, 97070 Wuerzburg, Germany and Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA.|Tresch Group, Max Planck Institute for Plant Breeding Research, 50829 Cologne, Germany, AG Haaf, Institute of Human Genetics, Julius Maximilians University, 97070 Wuerzburg, Germany and Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA.|Tresch Group, Max Planck Institute for Plant Breeding Research, 50829 Cologne, Germany, AG Haaf, Institute of Human Genetics, Julius Maximilians University, 97070 Wuerzburg, Germany and Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA.|Tresch Group, Max Planck Institute for Plant Breeding Research, 50829 Cologne, Germany, AG Haaf, Institute of Human Genetics, Julius Maximilians University, 97070 Wuerzburg, Germany and Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA.', 'Germany|Germany|Germany|Germany|Germany', 0, 'DNA Methylation|Genome|Genome-Wide Association Study|Genomics|High-Throughput Nucleotide Sequencing|Software Design|Sulfites', 'Journal Article', '10.1093/bioinformatics/btu142', '24618468', 'Here we present the open-source R/Bioconductor software package BEAT (BS-Seq Epimutation Analysis Toolkit). It implements all bioinformatics steps required for the quantitative high-resolution analysis of DNA methylation patterns from bisulfite sequencing data, including the detection of regional epimutation events, i.e. loss or gain of DNA methylation at CG positions relative to a reference. Using a binomial mixture model, the BEAT package aggregates methylation counts per genomic position, thereby compensating for low coverage, incomplete conversion and sequencing errors.'),
(78296, 2014, 'bio', 'pRESTO: a toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires', 'Vander Heiden, Jason A|Yaari, Gur|Uduman, Mohamed|Stern, Joel N H|OConnor, Kevin C|Hafler, David A|Vigneault, Francois|Kleinstein, Steven H', 'Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USA.|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USAInterdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USA.|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USAInterdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USA.|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USAInterdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USAInterdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USA.|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USAInterdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USA.|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USAInterdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USA.|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USA.|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USAInterdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA, Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan 52900, Israel, Department of Pathology, Yale School of Medicine, New Haven, CT 06511, Department of Science Education, Hofstra North Shore-LIJ School of Medicine, Hofstra University, Hempstead, NY 11530, Department of Neurology, Yale School of Medicine, New Haven, CT 06511, Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06511 and AbVitro Inc., Boston, MA 02210, USA.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 119, 'High-Throughput Nucleotide Sequencing|Lymphocytes|Receptors, Immunologic|Sequence Analysis, DNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu138', '24618469', 'Driven by dramatic technological improvements, large-scale characterization of lymphocyte receptor repertoires via high-throughput sequencing is now feasible. Although promising, the high germline and somatic diversity, especially of B-cell immunoglobulin repertoires, presents challenges for analysis requiring the development of specialized computational pipelines. We developed the REpertoire Sequencing TOolkit (pRESTO) for processing reads from high-throughput lymphocyte receptor studies. pRESTO processes raw sequences to produce error-corrected, sorted and annotated sequence sets, along with a wealth of metrics at each step. The toolkit supports multiplexed primer pools, single- or paired-end reads and emerging technologies that use single-molecule identifiers. pRESTO has been tested on data generated from Roche and Illumina platforms. It has a built-in capacity to parallelize the work between available processors and is able to efficiently process millions of sequences generated by typical high-throughput projects.'),
(78297, 2014, 'bio', 'Probabilistic PCA of censored data: accounting for uncertainties in the visualization of high-throughput single-cell qPCR data', 'Buettner, Florian|Moignard, Victoria|Göttgens, Berthold|Theis, Fabian J', 'Institute of Computational Biology, Helmholtz-Zentrum München, 85764 Neuherberg, Germany, Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome Trust & MRC Cambridge Stem Cell Institute, Cambridge CB2 0XY, UK and Department of Mathematics, TU München, 85748 Garching, Germany.|Institute of Computational Biology, Helmholtz-Zentrum München, 85764 Neuherberg, Germany, Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome Trust & MRC Cambridge Stem Cell Institute, Cambridge CB2 0XY, UK and Department of Mathematics, TU München, 85748 Garching, Germany.|Institute of Computational Biology, Helmholtz-Zentrum München, 85764 Neuherberg, Germany, Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome Trust & MRC Cambridge Stem Cell Institute, Cambridge CB2 0XY, UK and Department of Mathematics, TU München, 85748 Garching, Germany.|Institute of Computational Biology, Helmholtz-Zentrum München, 85764 Neuherberg, Germany, Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome Trust & MRC Cambridge Stem Cell Institute, Cambridge CB2 0XY, UK and Department of Mathematics, TU München, 85748 Garching, GermanyInstitute of Computational Biology, Helmholtz-Zentrum München, 85764 Neuherberg, Germany, Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome Trust & MRC Cambridge Stem Cell Institute, Cambridge CB2 0XY, UK and Department of Mathematics, TU München, 85748 Garching, Germany.', 'Germany|Germany|Germany|Germany', 12, 'Animals|Mice|Principal Component Analysis|Probability|Real-Time Polymerase Chain Reaction|Software|Stem Cells', 'Journal Article', '10.1093/bioinformatics/btu134', '24618470', 'High-throughput single-cell quantitative real-time polymerase chain reaction (qPCR) is a promising technique allowing for new insights in complex cellular processes. However, the PCR reaction can be detected only up to a certain detection limit, whereas failed reactions could be due to low or absent expression, and the true expression level is unknown. Because this censoring can occur for high proportions of the data, it is one of the main challenges when dealing with single-cell qPCR data. Principal component analysis (PCA) is an important tool for visualizing the structure of high-dimensional data as well as for identifying subpopulations of cells. However, to date it is not clear how to perform a PCA of censored data. We present a probabilistic approach that accounts for the censoring and evaluate it for two typical datasets containing single-cell qPCR data.'),
(78298, 2014, 'bio', 'Turtle: identifying frequent k-mers with cache-efficient algorithms', 'Roy, Rajat Shuvro|Bhattacharya, Debashish|Schliep, Alexander', 'Department of Computer Science, Department of Ecology, Evolution and Natural Resources, Institute of Marine and Coastal Sciences and BioMaPS Institute for Quantitative Biology, Rutgers University, New Brunswick, NJ 08901, USADepartment of Computer Science, Department of Ecology, Evolution and Natural Resources, Institute of Marine and Coastal Sciences and BioMaPS Institute for Quantitative Biology, Rutgers University, New Brunswick, NJ 08901, USADepartment of Computer Science, Department of Ecology, Evolution and Natural Resources, Institute of Marine and Coastal Sciences and BioMaPS Institute for Quantitative Biology, Rutgers University, New Brunswick, NJ 08901, USA.|Department of Computer Science, Department of Ecology, Evolution and Natural Resources, Institute of Marine and Coastal Sciences and BioMaPS Institute for Quantitative Biology, Rutgers University, New Brunswick, NJ 08901, USADepartment of Computer Science, Department of Ecology, Evolution and Natural Resources, Institute of Marine and Coastal Sciences and BioMaPS Institute for Quantitative Biology, Rutgers University, New Brunswick, NJ 08901, USA.|Department of Computer Science, Department of Ecology, Evolution and Natural Resources, Institute of Marine and Coastal Sciences and BioMaPS Institute for Quantitative Biology, Rutgers University, New Brunswick, NJ 08901, USADepartment of Computer Science, Department of Ecology, Evolution and Natural Resources, Institute of Marine and Coastal Sciences and BioMaPS Institute for Quantitative Biology, Rutgers University, New Brunswick, NJ 08901, USA.', 'United States|United States|United States', 0, 'Algorithms|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu132', '24618471', 'Counting the frequencies of k-mers in read libraries is often a first step in the analysis of high-throughput sequencing data. Infrequent k-mers are assumed to be a result of sequencing errors. The frequent k-mers constitute a reduced but error-free representation of the experiment, which can inform read error correction or serve as the input to de novo assembly methods. Ideally, the memory requirement for counting should be linear in the number of frequent k-mers and not in the, typically much larger, total number of k-mers in the read library.'),
(78299, 2014, 'bio', 'Dont use a cannon to kill the  miRNA mosquito', 'Karathanasis, Nestoras|Tsamardinos, Ioannis|Poirazi, Panayiota', 'Department of Biology, University of Crete, Heraklion, 71409, Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology-Hellas (FORTH), Heraklion, 70013, Department of Computer Science, University of Crete, Heraklion, 71409 and Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH), Heraklion, 70013, Greece.|Department of Biology, University of Crete, Heraklion, 71409, Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology-Hellas (FORTH), Heraklion, 70013, Department of Computer Science, University of Crete, Heraklion, 71409 and Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH), Heraklion, 70013, Greece.|Department of Biology, University of Crete, Heraklion, 71409, Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology-Hellas (FORTH), Heraklion, 70013, Department of Computer Science, University of Crete, Heraklion, 71409 and Institute of Computer Science, Foundation for Research and Technology-Hellas (FORTH), Heraklion, 70013, Greece.', 'Greece|Greece|Greece', 2, 'Base Sequence|MicroRNAs|Molecular Sequence Data|Nucleic Acid Conformation|Sequence Analysis, RNA', 'Letter', '10.1093/bioinformatics/btu100', '24618472', '-'),
(78300, 2014, 'bio', 'Orione, a web-based framework for NGS analysis in microbiology', 'Cuccuru, Gianmauro|Orsini, Massimiliano|Pinna, Andrea|Sbardellati, Andrea|Soranzo, Nicola|Travaglione, Antonella|Uva, Paolo|Zanetti, Gianluigi|Fotia, Giorgio', 'CRS4, Science and Technology Park Polaris, Piscina Manna, 09010 Pula (CA), Italy.|CRS4, Science and Technology Park Polaris, Piscina Manna, 09010 Pula (CA), Italy.|CRS4, Science and Technology Park Polaris, Piscina Manna, 09010 Pula (CA), Italy.|CRS4, Science and Technology Park Polaris, Piscina Manna, 09010 Pula (CA), Italy.|CRS4, Science and Technology Park Polaris, Piscina Manna, 09010 Pula (CA), Italy.|CRS4, Science and Technology Park Polaris, Piscina Manna, 09010 Pula (CA), Italy.|CRS4, Science and Technology Park Polaris, Piscina Manna, 09010 Pula (CA), Italy.|CRS4, Science and Technology Park Polaris, Piscina Manna, 09010 Pula (CA), Italy.|CRS4, Science and Technology Park Polaris, Piscina Manna, 09010 Pula (CA), Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 73, 'High-Throughput Nucleotide Sequencing|Internet|Metagenomics|Microbiological Techniques|Reproducibility of Results|Software', 'Journal Article', '10.1093/bioinformatics/btu135', '24618473', 'End-to-end next-generation sequencing microbiology data analysis requires a diversity of tools covering bacterial resequencing, de novo assembly, scaffolding, bacterial RNA-Seq, gene annotation and metagenomics. However, the construction of computational pipelines that use different software packages is difficult owing to a lack of interoperability, reproducibility and transparency. To overcome these limitations we present Orione, a Galaxy-based framework consisting of publicly available research software and specifically designed pipelines to build complex, reproducible workflows for next-generation sequencing microbiology data analysis. Enabling microbiology researchers to conduct their own custom analysis and data manipulation without software installation or programming, Orione provides new opportunities for data-intensive computational analyses in microbiology and metagenomics.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78301, 2014, 'bio', 'Characterization of p38 MAPK isoforms for drug resistance study using systems biology approach', 'Peng, Huiming|Peng, Tao|Wen, Jianguo|Engler, David A|Matsunami, Risxc3xab K|Su, Jing|Zhang, Le|Chang, Chung-Che Jeff|Zhou, Xiaobo', 'Center for Bioinformatics & Systems Biology and Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA, Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Department of Pathology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Proteomics Programmatic Core Laboratory, The Methodist Hospital Research Institute, Houston, TX 77030, USA, College of Computer and Information Science, Southwest University, Chongqing 400715, China, Department of Pathology, Florida Hospital, Orlando, FL 32803, USA.|Center for Bioinformatics & Systems Biology and Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA, Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Department of Pathology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Proteomics Programmatic Core Laboratory, The Methodist Hospital Research Institute, Houston, TX 77030, USA, College of Computer and Information Science, Southwest University, Chongqing 400715, China, Department of Pathology, Florida Hospital, Orlando, FL 32803, USA.|Center for Bioinformatics & Systems Biology and Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA, Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Department of Pathology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Proteomics Programmatic Core Laboratory, The Methodist Hospital Research Institute, Houston, TX 77030, USA, College of Computer and Information Science, Southwest University, Chongqing 400715, China, Department of Pathology, Florida Hospital, Orlando, FL 32803, USA.|Center for Bioinformatics & Systems Biology and Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA, Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Department of Pathology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Proteomics Programmatic Core Laboratory, The Methodist Hospital Research Institute, Houston, TX 77030, USA, College of Computer and Information Science, Southwest University, Chongqing 400715, China, Department of Pathology, Florida Hospital, Orlando, FL 32803, USA.|Center for Bioinformatics & Systems Biology and Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA, Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Department of Pathology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Proteomics Programmatic Core Laboratory, The Methodist Hospital Research Institute, Houston, TX 77030, USA, College of Computer and Information Science, Southwest University, Chongqing 400715, China, Department of Pathology, Florida Hospital, Orlando, FL 32803, USA.|Center for Bioinformatics & Systems Biology and Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA, Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Department of Pathology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Proteomics Programmatic Core Laboratory, The Methodist Hospital Research Institute, Houston, TX 77030, USA, College of Computer and Information Science, Southwest University, Chongqing 400715, China, Department of Pathology, Florida Hospital, Orlando, FL 32803, USA.|Center for Bioinformatics & Systems Biology and Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA, Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Department of Pathology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Proteomics Programmatic Core Laboratory, The Methodist Hospital Research Institute, Houston, TX 77030, USA, College of Computer and Information Science, Southwest University, Chongqing 400715, China, Department of Pathology, Florida Hospital, Orlando, FL 32803, USA.|Center for Bioinformatics & Systems Biology and Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA, Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Department of Pathology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Proteomics Programmatic Core Laboratory, The Methodist Hospital Research Institute, Houston, TX 77030, USA, College of Computer and Information Science, Southwest University, Chongqing 400715, China, Department of Pathology, Florida Hospital, Orlando, FL 32803, USA.|Center for Bioinformatics & Systems Biology and Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA, Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Department of Pathology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Proteomics Programmatic Core Laboratory, The Methodist Hospital Research Institute, Houston, TX 77030, USA, College of Computer and Information Science, Southwest University, Chongqing 400715, China, Department of Pathology, Florida Hospital, Orlando, FL 32803, USACenter for Bioinformatics & Systems Biology and Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA, Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Department of Pathology, The Methodist Hospital Research Institute, Houston, TX 77030, USA, Proteomics Programmatic Core Laboratory, The Methodist Hospital Research Institute, Houston, TX 77030, USA, College of Computer and Information Science, Southwest University, Chongqing 400715, China, Department of Pathology, Florida Hospital, Orlando, FL 32803, USA.', 'China|China|China|China|China|China|China|China|China', 29, 'Cell Line|Cell Proliferation|Drug Resistance|Humans|Isoenzymes|NF-kappa B|Phosphorylation|Signal Transduction|Systems Biology|p38 Mitogen-Activated Protein Kinases', 'Journal Article', '10.1093/bioinformatics/btu133', '24618474', 'p38 mitogen-activated protein kinase activation plays an important role in resistance to chemotherapeutic cytotoxic drugs in treating multiple myeloma (MM). However, how the p38 mitogen-activated protein kinase signaling pathway is involved in drug resistance, in particular the roles that the various p38 isoforms play, remains largely unknown.'),
(78302, 2014, 'bio', 'Lacking alignments? The next-generation sequencing mapper segemehl revisited', 'Otto, Christian|Stadler, Peter F|Hoffmann, Steve', 'Transcriptome Bioinformatics Junior Research Group, LIFE-Leipzig Research Center for Civilization Diseases, Interdisciplinary Center for Bioinformatics, Bioinformatics Group, Department of Computer Science, University Leipzig, RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany, Santa Fe Institute, Santa Fe, New Mexico, USA, Department of Theoretical Chemistry, University of Vienna, Austria, Max-Planck-Institute for Mathematics in Sciences, Leipzig, Germany and Center for non-coding RNA in Technology and Health, University of Copenhagen, DenmarkTranscriptome Bioinformatics Junior Research Group, LIFE-Leipzig Research Center for Civilization Diseases, Interdisciplinary Center for Bioinformatics, Bioinformatics Group, Department of Computer Science, University Leipzig, RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany, Santa Fe Institute, Santa Fe, New Mexico, USA, Department of Theoretical Chemistry, University of Vienna, Austria, Max-Planck-Institute for Mathematics in Sciences, Leipzig, Germany and Center for non-coding RNA in Technology and Health, University of Copenhagen, Denmark.|Transcriptome Bioinformatics Junior Research Group, LIFE-Leipzig Research Center for Civilization Diseases, Interdisciplinary Center for Bioinformatics, Bioinformatics Group, Department of Computer Science, University Leipzig, RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany, Santa Fe Institute, Santa Fe, New Mexico, USA, Department of Theoretical Chemistry, University of Vienna, Austria, Max-Planck-Institute for Mathematics in Sciences, Leipzig, Germany and Center for non-coding RNA in Technology and Health, University of Copenhagen, DenmarkTranscriptome Bioinformatics Junior Research Group, LIFE-Leipzig Research Center for Civilization Diseases, Interdisciplinary Center for Bioinformatics, Bioinformatics Group, Department of Computer Science, University Leipzig, RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany, Santa Fe Institute, Santa Fe, New Mexico, USA, Department of Theoretical Chemistry, University of Vienna, Austria, Max-Planck-Institute for Mathematics in Sciences, Leipzig, Germany and Center for non-coding RNA in Technology and Health, University of Copenhagen, DenmarkTranscriptome Bioinformatics Junior Research Group, LIFE-Leipzig Research Center for Civilization Diseases, Interdisciplinary Center for Bioinformatics, Bioinformatics Group, Department of Computer Science, University Leipzig, RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany, Santa Fe Institute, Santa Fe, New Mexico, USA, Department of Theoretical Chemistry, University of Vienna, Austria, Max-Planck-Institute for Mathematics in Sciences, Leipzig, Germany and Center for non-coding RNA in Technology and Health, University of Copenhagen, DenmarkTranscriptome Bioinformatics Junior Research Group, LIFE-Leipzig Research Center for Civilization Diseases, Interdisciplinary Center for Bioinformatics, Bioinformatics Group, Department of Computer Science, University Leipzig, RNomics Group, Fra|Transcriptome Bioinformatics Junior Research Group, LIFE-Leipzig Research Center for Civilization Diseases, Interdisciplinary Center for Bioinformatics, Bioinformatics Group, Department of Computer Science, University Leipzig, RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany, Santa Fe Institute, Santa Fe, New Mexico, USA, Department of Theoretical Chemistry, University of Vienna, Austria, Max-Planck-Institute for Mathematics in Sciences, Leipzig, Germany and Center for non-coding RNA in Technology and Health, University of Copenhagen, DenmarkTranscriptome Bioinformatics Junior Research Group, LIFE-Leipzig Research Center for Civilization Diseases, Interdisciplinary Center for Bioinformatics, Bioinformatics Group, Department of Computer Science, University Leipzig, RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany, Santa Fe Institute, Santa Fe, New Mexico, USA, Department of Theoretical Chemistry, University of Vienna, Austria, Max-Planck-Institute for Mathematics in Sciences, Leipzig, Germany and Center for non-coding RNA in Technology and Health, University of Copenhagen, Denmark.', 'Austria|Austria|Austria', 0, 'Algorithms|High-Throughput Nucleotide Sequencing|RNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu146', '24626854', 'Next-generation sequencing has become an important tool in molecular biology. Various protocols to investigate genomic, transcriptomic and epigenomic features across virtually all species and tissues have been devised. For most of these experiments, one of the first crucial steps of bioinformatic analysis is the mapping of reads to reference genomes.'),
(78303, 2014, 'bio', 'FSuite: exploiting inbreeding in dense SNP chip and exome data', 'Gazal, Steven|Sahbatou, Mourad|Babron, Marie-Claude|Génin, Emmanuelle|Leutenegger, Anne-Louise', 'Inserm, U946, Genetic variability and human diseases, Paris, 75010, Université Paris Sud, Kremlin-Bicêtre, 94270, Fondation Jean Dausset CEPH, Paris, 75010, Université Paris-Diderot, UMR 946, Institut Universitaire dHématologie, Paris, 75475, Inserm, U1078, Génétique, Génomique fonctionnelle et Biotechnologies, Brest, 29218 and Centre Hospitalier Régional Universitaire de Brest, Brest, 29200, France Inserm, U946, Genetic variability and human diseases, Paris, 75010, Université Paris Sud, Kremlin-Bicêtre, 94270, Fondation Jean Dausset CEPH, Paris, 75010, Université Paris-Diderot, UMR 946, Institut Universitaire dHématologie, Paris, 75475, Inserm, U1078, Génétique, Génomique fonctionnelle et Biotechnologies, Brest, 29218 and Centre Hospitalier Régional Universitaire de Brest, Brest, 29200, France.|Inserm, U946, Genetic variability and human diseases, Paris, 75010, Université Paris Sud, Kremlin-Bicêtre, 94270, Fondation Jean Dausset CEPH, Paris, 75010, Université Paris-Diderot, UMR 946, Institut Universitaire dHématologie, Paris, 75475, Inserm, U1078, Génétique, Génomique fonctionnelle et Biotechnologies, Brest, 29218 and Centre Hospitalier Régional Universitaire de Brest, Brest, 29200, France.|Inserm, U946, Genetic variability and human diseases, Paris, 75010, Université Paris Sud, Kremlin-Bicêtre, 94270, Fondation Jean Dausset CEPH, Paris, 75010, Université Paris-Diderot, UMR 946, Institut Universitaire dHématologie, Paris, 75475, Inserm, U1078, Génétique, Génomique fonctionnelle et Biotechnologies, Brest, 29218 and Centre Hospitalier Régional Universitaire de Brest, Brest, 29200, France Inserm, U946, Genetic variability and human diseases, Paris, 75010, Université Paris Sud, Kremlin-Bicêtre, 94270, Fondation Jean Dausset CEPH, Paris, 75010, Université Paris-Diderot, UMR 946, Institut Universitaire dHématologie, Paris, 75475, Inserm, U1078, Génétique, Génomique fonctionnelle et Biotechnologies, Brest, 29218 and Centre Hospitalier Régional Universitaire de Brest, Brest, 29200, France.|Inserm, U946, Genetic variability and human diseases, Paris, 75010, Université Paris Sud, Kremlin-Bicêtre, 94270, Fondation Jean Dausset CEPH, Paris, 75010, Université Paris-Diderot, UMR 946, Institut Universitaire dHématologie, Paris, 75475, Inserm, U1078, Génétique, Génomique fonctionnelle et Biotechnologies, Brest, 29218 and Centre Hospitalier Régional Universitaire de Brest, Brest, 29200, France Inserm, U946, Genetic variability and human diseases, Paris, 75010, Université Paris Sud, Kremlin-Bicêtre, 94270, Fondation Jean Dausset CEPH, Paris, 75010, Université Paris-Diderot, UMR 946, Institut Universitaire dHématologie, Paris, 75475, Inserm, U1078, Génétique, Génomique fonctionnelle et Biotechnologies, Brest, 29218 and Centre Hospitalier Régional Universitaire de Brest, Brest, 29200, France.|Inserm, U946, Genetic variability and human diseases, Paris, 75010, Université Paris Sud, Kremlin-Bicêtre, 94270, Fondation Jean Dausset CEPH, Paris, 75010, Université Paris-Diderot, UMR 946, Institut Universitaire dHématologie, Paris, 75475, Inserm, U1078, Génétique, Génomique fonctionnelle et Biotechnologies, Brest, 29218 and Centre Hospitalier Régional Universitaire de Brest, Brest, 29200, France Inserm, U946, Genetic variability and human diseases, Paris, 75010, Université Paris Sud, Kremlin-Bicêtre, 94270, Fondation Jean Dausset CEPH, Paris, 75010, Université Paris-Diderot, UMR 946, Institut Universitaire dHématologie, Paris, 75475, Inserm, U1078, Génétique, Génomique fonctionnelle et Biotechnologies, Brest, 29218 and Centre Hospitalier Régional Universitaire de Brest, Brest, 29200, France.', 'France|France|France|France|France', 24, 'Consanguinity|Exome|Genomics|Homozygote|Humans|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btu149', '24632498', 'FSuite is a user-friendly pipeline developed for exploiting inbreeding information derived from human genomic data. It can make use of single nucleotide polymorphism chip or exome data. Compared with other software, the advantage of FSuite is that it provides a complete suite of scripts to describe and use the inbreeding information. It includes a module to detect inbred individuals and estimate their inbreeding coefficient, a module to describe the proportion of different mating types in the population and the individual probability to be offspring of different mating types that can be useful for population genetic studies. It also allows the identification of shared regions of homozygosity between affected individuals (homozygosity mapping) that can be used to identify rare recessive mutations involved in monogenic or multifactorial diseases.'),
(78304, 2014, 'bio', 'A general method for accurate estimation of false discovery rates in identification of differentially expressed genes', 'Tan, Yuan-De|Xu, Hongyan', 'College of Life Science, Hunan Normal University, Changsha, Hunan 410087, China and Department of Biostatistics and Epidemiology, Georgia Regents University, Augusta, GA 30912-4900, USA.|College of Life Science, Hunan Normal University, Changsha, Hunan 410087, China and Department of Biostatistics and Epidemiology, Georgia Regents University, Augusta, GA 30912-4900, USA.', 'China|China', 14, 'Algorithms|Arabidopsis|Data Interpretation, Statistical|Gene Expression Profiling|Humans|Leukemia|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btu124', '24632499', 'The omic data such as genomic data, transcriptomic data, proteomic data and single nucleotide polymorphism data have been rapidly growing. The omic data are large-scale and high-throughput data. Such data challenge traditional statistical methodologies and require multiple tests. Several multiple-testing procedures such as Bonferroni procedure, Benjamini-Hochberg (BH) procedure and Westfall-Young procedure have been developed, among which some control family-wise error rate and the others control false discovery rate (FDR). These procedures are valid in some cases and cannot be applied to all types of large-scale data. To address this statistically challenging problem in the analysis of the omic data, we propose a general method for generating a set of multiple-testing procedures. This method is based on the BH theorems. By choosing a C-value, one can realize a specific multiple-testing procedure. For example, by setting C = 1.22, our method produces the BH procedure. With C < 1.22, our method generates procedures of weakly controlling FDR, and with C > 1.22, the procedures strongly control FDR. Those with C = G (number of genes or tests) and C = 0 are, respectively, the Bonferroni procedure and the single-testing procedure. These are the two extreme procedures in this family. To let one choose an appropriate multiple-testing procedure in practice, we develop an algorithm by which FDR can be correctly and reliably estimated. Simulated results show that our method works well for an accurate estimation of FDR in various scenarios, and we illustrate the applications of our method with three real datasets.'),
(78305, 2014, 'bio', 'comTAR: a web tool for the prediction and characterization of conserved microRNA targets in plants', 'Chorostecki, Uciel|Palatnik, Javier F', 'IBR (Instituto de Biología Molecular y Celular de Rosario), CONICET and Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, 2000 Rosario, Argentina.|IBR (Instituto de Biología Molecular y Celular de Rosario), CONICET and Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, 2000 Rosario, Argentina.', 'Argentina|Argentina', 10, 'Animals|Base Sequence|Conserved Sequence|Internet|Magnoliopsida|MicroRNAs|RNA, Messenger|RNA, Plant|Software', 'Journal Article', '10.1093/bioinformatics/btu147', '24632500', 'MicroRNAs (miRNAs) are major regulators of gene expression in plants and animals. They recognize their target messenger RNAs (mRNAs) by sequence complementarity and guide them to cleavage or translational arrest. So far, the prediction of plant miRNA-target pairs generally relies on the use of empirical parameters deduced from known miRNA-target interactions.'),
(78306, 2014, 'bio', 'Optimal metabolic route search based on atom mappings', 'Latendresse, Mario|Krummenacker, Markus|Karp, Peter D', 'Bioinformatics Research Group/Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA.|Bioinformatics Research Group/Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA.|Bioinformatics Research Group/Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA.', 'United States|United States|United States', 28, 'Algorithms|Genome|Metabolic Engineering|Metabolic Networks and Pathways|Software', 'Journal Article', '10.1093/bioinformatics/btu150', '24642060', 'A key computational problem in metabolic engineering is finding efficient metabolic routes from a source to a target compound in genome-scale reaction networks, potentially considering the addition of new reactions. Efficiency can be based on many factors, such as route lengths, atoms conserved and the number of new reactions, and the new enzymes to catalyze them, added to the route. Fast algorithms are needed to systematically search these large genome-scale reaction networks.'),
(78307, 2014, 'bio', 'An R package to analyse LC/MS metabolomic data: MAIT (Metabolite Automatic Identification Toolkit)', 'Fernández-Albert, Francesc|Llorach, Rafael|Andrés-Lacueva, Cristina|Perera, Alexandre', 'B2SLab., Department dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, CIBER-BBN, Pau Gargallo, 5, 08028 Barcelona, Biomarkers & Nutrimetabolomic Lab., Department of Nutrition and Food Science-XaRTA, INSA, Faculty of Pharmacy, Food and Nutrition Torribera Campus, University of Barcelona, Av. Prat de la Riba 171, 08921, Sta Coloma de Gramenet, and INGENIO-CONSOLIDER Program, FUN-C-Food CSD2007-063, Av Joan XXIII s/n 08028, Barcelona, SpainB2SLab., Department dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, CIBER-BBN, Pau Gargallo, 5, 08028 Barcelona, Biomarkers & Nutrimetabolomic Lab., Department of Nutrition and Food Science-XaRTA, INSA, Faculty of Pharmacy, Food and Nutrition Torribera Campus, University of Barcelona, Av. Prat de la Riba 171, 08921, Sta Coloma de Gramenet, and INGENIO-CONSOLIDER Program, FUN-C-Food CSD2007-063, Av Joan XXIII s/n 08028, Barcelona, Spain.|B2SLab., Department dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, CIBER-BBN, Pau Gargallo, 5, 08028 Barcelona, Biomarkers & Nutrimetabolomic Lab., Department of Nutrition and Food Science-XaRTA, INSA, Faculty of Pharmacy, Food and Nutrition Torribera Campus, University of Barcelona, Av. Prat de la Riba 171, 08921, Sta Coloma de Gramenet, and INGENIO-CONSOLIDER Program, FUN-C-Food CSD2007-063, Av Joan XXIII s/n 08028, Barcelona, SpainB2SLab., Department dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, CIBER-BBN, Pau Gargallo, 5, 08028 Barcelona, Biomarkers & Nutrimetabolomic Lab., Department of Nutrition and Food Science-XaRTA, INSA, Faculty of Pharmacy, Food and Nutrition Torribera Campus, University of Barcelona, Av. Prat de la Riba 171, 08921, Sta Coloma de Gramenet, and INGENIO-CONSOLIDER Program, FUN-C-Food CSD2007-063, Av Joan XXIII s/n 08028, Barcelona, Spain.|B2SLab., Department dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, CIBER-BBN, Pau Gargallo, 5, 08028 Barcelona, Biomarkers & Nutrimetabolomic Lab., Department of Nutrition and Food Science-XaRTA, INSA, Faculty of Pharmacy, Food and Nutrition Torribera Campus, University of Barcelona, Av. Prat de la Riba 171, 08921, Sta Coloma de Gramenet, and INGENIO-CONSOLIDER Program, FUN-C-Food CSD2007-063, Av Joan XXIII s/n 08028, Barcelona, SpainB2SLab., Department dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, CIBER-BBN, Pau Gargallo, 5, 08028 Barcelona, Biomarkers & Nutrimetabolomic Lab., Department of Nutrition and Food Science-XaRTA, INSA, Faculty of Pharmacy, Food and Nutrition Torribera Campus, University of Barcelona, Av. Prat de la Riba 171, 08921, Sta Coloma de Gramenet, and INGENIO-CONSOLIDER Program, FUN-C-Food CSD2007-063, Av Joan XXIII s/n 08028, Barcelona, Spain.|B2SLab., Department dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, CIBER-BBN, Pau Gargallo, 5, 08028 Barcelona, Biomarkers & Nutrimetabolomic Lab., Department of Nutrition and Food Science-XaRTA, INSA, Faculty of Pharmacy, Food and Nutrition Torribera Campus, University of Barcelona, Av. Prat de la Riba 171, 08921, Sta Coloma de Gramenet, and INGENIO-CONSOLIDER Program, FUN-C-Food CSD2007-063, Av Joan XXIII s/n 08028, Barcelona, Spain.', 'Spain|Spain|Spain|Spain', 42, 'Automation, Laboratory|Chromatography, High Pressure Liquid|Mass Spectrometry|Metabolomics|Software Design', 'Journal Article', '10.1093/bioinformatics/btu136', '24642061', 'Current tools for liquid chromatography and mass spectrometry for metabolomic data cover a limited number of processing steps, whereas online tools are hard to use in a programmable fashion. This article introduces the Metabolite Automatic Identification Toolkit (MAIT) package, which makes it possible for users to perform metabolomic end-to-end liquid chromatography and mass spectrometry data analysis. MAIT is focused on improving the peak annotation stage and provides essential tools to validate statistical analysis results. MAIT generates output files with the statistical results, peak annotation and metabolite identification.'),
(78308, 2014, 'bio', 'Piecewise-constant and low-rank approximation for identification of recurrent copy number variations', 'Zhou, Xiaowei|Liu, Jiming|Wan, Xiang|Yu, Weichuan', 'Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon and Department of Computer Science and Institute of Theoretical and Computational Study, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China.|Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon and Department of Computer Science and Institute of Theoretical and Computational Study, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China.|Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon and Department of Computer Science and Institute of Theoretical and Computational Study, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China.|Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon and Department of Computer Science and Institute of Theoretical and Computational Study, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China.', 'China|China|China|China', 27, 'Algorithms|Breast Neoplasms|Comparative Genomic Hybridization|DNA Copy Number Variations|Female|Humans', 'Journal Article', '10.1093/bioinformatics/btu131', '24642062', 'The post-genome era sees urgent need for more novel approaches to extracting useful information from the huge amount of genetic data. The identification of recurrent copy number variations (CNVs) from array-based comparative genomic hybridization (aCGH) data can help understand complex diseases, such as cancer. Most of the previous computational methods focused on single-sample analysis or statistical testing based on the results of single-sample analysis. Finding recurrent CNVs from multi-sample data remains a challenging topic worth further study.'),
(78309, 2014, 'bio', 'Prokka: rapid prokaryotic genome annotation', 'Seemann, Torsten', 'Victorian Bioinformatics Consortium, Monash University, Clayton 3800 and Life Sciences Computation Centre, Victorian Life Sciences Computation Initiative, Carlton 3053, AustraliaVictorian Bioinformatics Consortium, Monash University, Clayton 3800 and Life Sciences Computation Centre, Victorian Life Sciences Computation Initiative, Carlton 3053, Australia.', 'Australia', 3511, 'Genome, Bacterial|Genomics|Molecular Sequence Annotation|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu153', '24642063', 'The multiplex capability and high yield of current day DNA-sequencing instruments has made bacterial whole genome sequencing a routine affair. The subsequent de novo assembly of reads into contigs has been well addressed. The final step of annotating all relevant genomic features on those contigs can be achieved slowly using existing web- and email-based systems, but these are not applicable for sensitive data or integrating into computational pipelines. Here we introduce Prokka, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer. It produces standards-compliant output files for further analysis or viewing in genome browsers.'),
(78310, 2014, 'bio', 'KAnalyze: a fast versatile pipelined k-mer toolkit', 'Audano, Peter|Vannberg, Fredrik', 'School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA.|School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA.', 'Georgia|Georgia', 31, 'Algorithms|Chromosomes, Human, Pair 1|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu152', '24642064', 'Converting nucleotide sequences into short overlapping fragments of uniform length, k-mers, is a common step in many bioinformatics applications. While existing software packages count k-mers, few are optimized for speed, offer an application programming interface (API), a graphical interface or contain features that make it extensible and maintainable. We designed KAnalyze to compete with the fastest k-mer counters, to produce reliable output and to support future development efforts through well-architected, documented and testable code. Currently, KAnalyze can output k-mer counts in a sorted tab-delimited file or stream k-mers as they are read. KAnalyze can process large datasets with 2 GB of memory. This project is implemented in Java 7, and the command line interface (CLI) is designed to integrate into pipelines written in any language.'),
(78311, 2014, 'bio', '15 years of Bioinformatics', '-', '-', '-', 0, 'Computational Biology|Peer Review, Research', 'Editorial', '10.1093/bioinformatics/btu076', '24642573', '-'),
(78312, 2014, 'bio', 'Basin Hopping Graph: a computational framework to characterize RNA folding landscapes', 'Kucharík, Marcel|Hofacker, Ivo L|Stadler, Peter F|Qin, Jing', 'Institute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, Denmark.|Institute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, DenmarkInstitute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, DenmarkInstitute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, Denmark.|Institute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, DenmarkInstitute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, DenmarkInstitute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, DenmarkInstitute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, Univer|Institute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, DenmarkInstitute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, Denmark.', 'Austria|Austria|Austria|Austria', 25, 'Algorithms|Computational Biology|Kinetics|RNA|RNA Folding', 'Journal Article', '10.1093/bioinformatics/btu156', '24648041', 'RNA folding is a complicated kinetic process. The minimum free energy structure provides only a static view of the most stable conformational state of the system. It is insufficient to give detailed insights into the dynamic behavior of RNAs. A sufficiently sophisticated analysis of the folding free energy landscape, however, can provide the relevant information.'),
(78313, 2014, 'bio', 'OncomiRDB: a database for the experimentally verified oncogenic and tumor-suppressive microRNAs', 'Wang, Dongfang|Gu, Jin|Wang, Ting|Ding, Zijian', 'MOE Key Laboratory of Bioinformatics, TNLIST Bioinformatics Division / Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics, TNLIST Bioinformatics Division / Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics, TNLIST Bioinformatics Division / Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics, TNLIST Bioinformatics Division / Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing 100084, China.', 'China|China|China|China', 81, 'Databases, Nucleic Acid|Gene Regulatory Networks|Humans|Internet|MicroRNAs|Neoplasms|Oncogenes|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu155', '24651967', 'MicroRNAs (miRNAs), a class of small regulatory RNAs, play important roles in cancer initiation, progression and therapy. MiRNAs are found to regulate diverse cancer-related processes by targeting a large set of oncogenic and tumor-suppressive genes. To establish a high-confidence reference resource for studying the miRNA-regulated target genes and cellular processes in cancer, we manually curated 2259 entries of cancer-related miRNA regulations with direct experimental evidence from xe2x88xbc9000 abstracts, covering more than 300 miRNAs and 829 target genes across 25 cancer tissues. A web-based portal named oncomiRDB, which provides both graphical and text-based interfaces, was developed for easily browsing and searching all the annotations. It should be a useful resource for both the computational analysis and experimental study on miRNA regulatory networks and functions in cancer.'),
(78314, 2014, 'bio', 'tqDist: a library for computing the quartet and triplet distances between binary or general trees', 'Sand, Andreas|Holt, Morten K|Johansen, Jens|Brodal, Gerth Stølting|Mailund, Thomas|Pedersen, Christian N S', 'Bioinformatics Research Centre, Department of Computer Science and MADALGO, Center for Massive Data Algorithms, a Center of the Danish National Research Foundation, Aarhus University, DK-8000 Aarhus C, DenmarkBioinformatics Research Centre, Department of Computer Science and MADALGO, Center for Massive Data Algorithms, a Center of the Danish National Research Foundation, Aarhus University, DK-8000 Aarhus C, Denmark.|Bioinformatics Research Centre, Department of Computer Science and MADALGO, Center for Massive Data Algorithms, a Center of the Danish National Research Foundation, Aarhus University, DK-8000 Aarhus C, Denmark.|Bioinformatics Research Centre, Department of Computer Science and MADALGO, Center for Massive Data Algorithms, a Center of the Danish National Research Foundation, Aarhus University, DK-8000 Aarhus C, Denmark.|Bioinformatics Research Centre, Department of Computer Science and MADALGO, Center for Massive Data Algorithms, a Center of the Danish National Research Foundation, Aarhus University, DK-8000 Aarhus C, DenmarkBioinformatics Research Centre, Department of Computer Science and MADALGO, Center for Massive Data Algorithms, a Center of the Danish National Research Foundation, Aarhus University, DK-8000 Aarhus C, Denmark.|Bioinformatics Research Centre, Department of Computer Science and MADALGO, Center for Massive Data Algorithms, a Center of the Danish National Research Foundation, Aarhus University, DK-8000 Aarhus C, Denmark.|Bioinformatics Research Centre, Department of Computer Science and MADALGO, Center for Massive Data Algorithms, a Center of the Danish National Research Foundation, Aarhus University, DK-8000 Aarhus C, DenmarkBioinformatics Research Centre, Department of Computer Science and MADALGO, Center for Massive Data Algorithms, a Center of the Danish National Research Foundation, Aarhus University, DK-8000 Aarhus C, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 14, 'Algorithms|Classification|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btu157', '24651968', 'tqDist is a software package for computing the triplet and quartet distances between general rooted or unrooted trees, respectively. The program is based on algorithms with running time [Formula: see text] for the triplet distance calculation and [Formula: see text] for the quartet distance calculation, where n is the number of leaves in the trees and d is the degree of the tree with minimum degree. These are currently the fastest algorithms both in theory and in practice.'),
(78315, 2014, 'bio', 'TroX: a new method to learn about the genesis of aneuploidy from trisomic products of conception', 'Kermany, Amir R|Segurel, Laure|Oliver, Tiffany R|Przeworski, Molly', 'Department of Human Genetics and Howard Hughes Medical Institute, University of Chicago, Chicago, IL 60637, USA and Department of Biology, Spelman College, Atlanta, GA 30314, USADepartment of Human Genetics and Howard Hughes Medical Institute, University of Chicago, Chicago, IL 60637, USA and Department of Biology, Spelman College, Atlanta, GA 30314, USA.|Department of Human Genetics and Howard Hughes Medical Institute, University of Chicago, Chicago, IL 60637, USA and Department of Biology, Spelman College, Atlanta, GA 30314, USADepartment of Human Genetics and Howard Hughes Medical Institute, University of Chicago, Chicago, IL 60637, USA and Department of Biology, Spelman College, Atlanta, GA 30314, USA.|Department of Human Genetics and Howard Hughes Medical Institute, University of Chicago, Chicago, IL 60637, USA and Department of Biology, Spelman College, Atlanta, GA 30314, USA.|Department of Human Genetics and Howard Hughes Medical Institute, University of Chicago, Chicago, IL 60637, USA and Department of Biology, Spelman College, Atlanta, GA 30314, USADepartment of Human Genetics and Howard Hughes Medical Institute, University of Chicago, Chicago, IL 60637, USA and Department of Biology, Spelman College, Atlanta, GA 30314, USA.', 'United States|United States|United States|United States', 0, 'Aneuploidy|Child|Down Syndrome|Genotyping Techniques|Humans|Markov Chains|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software|Trisomy', 'Journal Article', '10.1093/bioinformatics/btu159', '24659032', 'An estimated 10-30% of clinically recognized conceptions are aneuploid, leading to spontaneous miscarriages, in vitro fertilization failures and, when viable, severe developmental disabilities. With the ongoing reduction in the cost of genotyping and DNA sequencing, the use of high-density single nucleotide polymorphism (SNP) markers for clinical diagnosis of aneuploidy and biomedical research into its causes is becoming common practice. A reliable, flexible and computationally feasible method for inferring the sources of aneuploidy is thus crucial.'),
(78316, 2014, 'bio', 'GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology', 'Caniza, Horacio|Romero, Alfonso E|Heron, Samuel|Yang, Haixuan|Devoto, Alessandra|Frasca, Marco|Mesiti, Marco|Valentini, Giorgio|Paccanaro, Alberto', 'Department of Computer Science, Royal Holloway, University of London, Egham, TW200EX, UK, School of Mathematics, Statistics & Applied Mathematics, National University of Ireland, Galway, School of Biological Sciences, Royal Holloway, University of London, Egham, TW200EX, UK and Dipartimento di Informatica, Università degli Studi di Milano, via Comelico 39/41, 20135 Milano, Italy.|Department of Computer Science, Royal Holloway, University of London, Egham, TW200EX, UK, School of Mathematics, Statistics & Applied Mathematics, National University of Ireland, Galway, School of Biological Sciences, Royal Holloway, University of London, Egham, TW200EX, UK and Dipartimento di Informatica, Università degli Studi di Milano, via Comelico 39/41, 20135 Milano, Italy.|Department of Computer Science, Royal Holloway, University of London, Egham, TW200EX, UK, School of Mathematics, Statistics & Applied Mathematics, National University of Ireland, Galway, School of Biological Sciences, Royal Holloway, University of London, Egham, TW200EX, UK and Dipartimento di Informatica, Università degli Studi di Milano, via Comelico 39/41, 20135 Milano, Italy.|Department of Computer Science, Royal Holloway, University of London, Egham, TW200EX, UK, School of Mathematics, Statistics & Applied Mathematics, National University of Ireland, Galway, School of Biological Sciences, Royal Holloway, University of London, Egham, TW200EX, UK and Dipartimento di Informatica, Università degli Studi di Milano, via Comelico 39/41, 20135 Milano, Italy.|Department of Computer Science, Royal Holloway, University of London, Egham, TW200EX, UK, School of Mathematics, Statistics & Applied Mathematics, National University of Ireland, Galway, School of Biological Sciences, Royal Holloway, University of London, Egham, TW200EX, UK and Dipartimento di Informatica, Università degli Studi di Milano, via Comelico 39/41, 20135 Milano, Italy.|Department of Computer Science, Royal Holloway, University of London, Egham, TW200EX, UK, School of Mathematics, Statistics & Applied Mathematics, National University of Ireland, Galway, School of Biological Sciences, Royal Holloway, University of London, Egham, TW200EX, UK and Dipartimento di Informatica, Università degli Studi di Milano, via Comelico 39/41, 20135 Milano, Italy.|Department of Computer Science, Royal Holloway, University of London, Egham, TW200EX, UK, School of Mathematics, Statistics & Applied Mathematics, National University of Ireland, Galway, School of Biological Sciences, Royal Holloway, University of London, Egham, TW200EX, UK and Dipartimento di Informatica, Università degli Studi di Milano, via Comelico 39/41, 20135 Milano, Italy.|Department of Computer Science, Royal Holloway, University of London, Egham, TW200EX, UK, School of Mathematics, Statistics & Applied Mathematics, National University of Ireland, Galway, School of Biological Sciences, Royal Holloway, University of London, Egham, TW200EX, UK and Dipartimento di Informatica, Università degli Studi di Milano, via Comelico 39/41, 20135 Milano, Italy.|Department of Computer Science, Royal Holloway, University of London, Egham, TW200EX, UK, School of Mathematics, Statistics & Applied Mathematics, National University of Ireland, Galway, School of Biological Sciences, Royal Holloway, University of London, Egham, TW200EX, UK and Dipartimento di Informatica, Università degli Studi di Milano, via Comelico 39/41, 20135 Milano, Italy.', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland', 0, 'Data Mining|Gene Ontology|Internet|Proteins|Semantics|Software|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btu144', '24659104', 'We present GOssTo, the Gene Ontology semantic similarity Tool, a user-friendly software system for calculating semantic similarities between gene products according to the Gene Ontology. GOssTo is bundled with six semantic similarity measures, including both term- and graph-based measures, and has extension capabilities to allow the user to add new similarities. Importantly, for any measure, GOssTo can also calculate the Random Walk Contribution that has been shown to greatly improve the accuracy of similarity measures. GOssTo is very fast, easy to use, and it allows the calculation of similarities on a genomic scale in a few minutes on a regular desktop machine.');
