INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76612, 2012, 'bio', 'PathVar: analysis of gene and protein expression variance in cellular pathways using microarray data', 'Glaab, Enrico|Schneider, Reinhard', 'Structural and Computational Biology Unit, EMBL, Meyerhofstrasse 1, 69117, Heidelberg, Germany. enrico.glaab@uni.lu|Structural and Computational Biology Unit, EMBL, Meyerhofstrasse 1, 69117, Heidelberg, Germany. enrico.glaab@uni.lu', 'Germany|Germany', 10, 'Gene Expression Profiling|Humans|Internet|Male|Oligonucleotide Array Sequence Analysis|Prostatic Neoplasms|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btr656', '22123829', 'Finding significant differences between the expression levels of genes or proteins across diverse biological conditions is one of the primary goals in the analysis of functional genomics data. However, existing methods for identifying differentially expressed genes or sets of genes by comparing measures of the average expression across predefined sample groups do not detect differential variance in the expression levels across genes in cellular pathways. Since corresponding pathway deregulations occur frequently in microarray gene or protein expression data, we present a new dedicated web application, PathVar, to analyze these data sources. The software ranks pathway-representing gene/protein sets in terms of the differences of the variance in the within-pathway expression levels across different biological conditions. Apart from identifying new pathway deregulation patterns, the tool exploits these patterns by combining different machine learning methods to find clusters of similar samples and build sample classification models.'),
(76613, 2012, 'bio', 'An infrastructure for ontology-based information systems in biomedicine: RICORDO case study', 'Wimalaratne, Sarala M|Grenon, Pierre|Hoehndorf, Robert|Gkoutos, Georgios V|de Bono, Bernard', 'European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SD, UK. sarala@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SD, UK. sarala@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SD, UK. sarala@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SD, UK. sarala@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SD, UK. sarala@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 11, 'Databases, Factual|Heart|Humans|Information Storage and Retrieval|Knowledge Bases|Programming Languages|Semantics', 'Journal Article', '10.1093/bioinformatics/btr662', '22130590', 'The article presents an infrastructure for supporting the semantic interoperability of biomedical resources based on the management (storing and inference-based querying) of their ontology-based annotations. This infrastructure consists of: (i) a repository to store and query ontology-based annotations, (ii) a knowledge base server with an inference engine to support the storage of and reasoning over ontologies used in the annotation of resources, (iii) a set of applications and services allowing interaction with the integrated repository and knowledge base. The infrastructure is being prototyped and developed and evaluated by the RICORDO project in support of the knowledge management of biomedical resources, including physiology and pharmacology models and associated clinical data.'),
(76614, 2012, 'bio', 'SCPC: a method to structurally compare protein complexes', 'Koike, Ryotaro|Ota, Motonori', 'Department of Complex Systems Science, Graduate School of Information Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan. rkoike@is.nagoya-u.ac.jp|Department of Complex Systems Science, Graduate School of Information Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan. rkoike@is.nagoya-u.ac.jp', 'Japan|Japan', 7, 'Algorithms|Databases, Protein|Hemoglobins|Models, Chemical|Multiprotein Complexes|Protein Structure, Quaternary|Protein Structure, Secondary|Software', 'Journal Article', '10.1093/bioinformatics/btr654', '22130591', 'Protein-protein interactions play vital functional roles in various biological phenomena. Physical contacts between proteins have been revealed using experimental approaches that have solved the structures of protein complexes at atomic resolution. To examine the huge number of protein complexes available in the Protein Data Bank, an efficient automated method that compares protein complexes is required.'),
(76615, 2012, 'bio', 'Gaussian process modelling for bicoid mRNA regulation in spatio-temporal Bicoid profile', 'Liu, Wei|Niranjan, Mahesan', 'School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK.|School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK.', 'United Kingdom|United Kingdom', 9, 'Animals|Diffusion|Drosophila|Embryo, Nonmammalian|Embryonic Development|Female|Homeodomain Proteins|Models, Genetic|RNA Stability|RNA, Messenger|Trans-Activators', 'Journal Article', '10.1093/bioinformatics/btr658', '22130592', 'Bicoid protein molecules, translated from maternally provided bicoid mRNA, establish a concentration gradient in Drosophila early embryonic development. There is experimental evidence that the synthesis and subsequent destruction of this protein is regulated at source by precise control of the stability of the maternal mRNA. Can we infer the driving function at the source from noisy observations of the spatio-temporal protein profile? We use non-parametric Gaussian process regression for modelling the propagation of Bicoid in the embryo and infer aspects of source regulation as a posterior function.'),
(76616, 2012, 'bio', 'NRPSsp: non-ribosomal peptide synthase substrate predictor', 'Prieto, Carlos|García-Estrada, Carlos|Lorenzana, Diego|Martín, Juan Francisco', 'Institute of Biotechnology of Leon, INBIOTEC, Parque Científico de León, 24006 León, Spain. carlos.prieto@unileon.es|Institute of Biotechnology of Leon, INBIOTEC, Parque Científico de León, 24006 León, Spain. carlos.prieto@unileon.es|Institute of Biotechnology of Leon, INBIOTEC, Parque Científico de León, 24006 León, Spain. carlos.prieto@unileon.es|Institute of Biotechnology of Leon, INBIOTEC, Parque Científico de León, 24006 León, Spain. carlos.prieto@unileon.es', 'Spain|Spain|Spain|Spain', 53, 'Bacteria|Fungi|Markov Chains|Peptide Synthases|Substrate Specificity', 'Journal Article', '10.1093/bioinformatics/btr659', '22130593', 'Non-ribosomal peptide synthetases (NRPSs) are multi-modular enzymes, which biosynthesize many important peptide compounds produced by bacteria and fungi. Some studies have revealed that an individual domain within the NRPSs shows significant substrate selectivity. The discovery and characterization of non-ribosomal peptides are of great interest for the biotechnological industries. We have applied computational mining methods in order to build a database of NRPSs modules that bind to specific substrates. We have used this database to build a hidden Markov model predictor of substrates that bind to a given NRPS.'),
(76617, 2012, 'bio', 'PGAP: pan-genomes analysis pipeline', 'Zhao, Yongbing|Wu, Jiayan|Yang, Junhui|Sun, Shixiang|Xiao, Jingfa|Yu, Jun', 'CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, Peoples Republic of China.|CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, Peoples Republic of China.|CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, Peoples Republic of China.|CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, Peoples Republic of China.|CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, Peoples Republic of China.|CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, Peoples Republic of China.', 'China|China|China|China|China|China', 0, 'Algorithms|Genome, Bacterial|Software|Streptococcus pyogenes', 'Journal Article', '10.1093/bioinformatics/btr655', '22130594', 'With the rapid development of DNA sequencing technology, increasing bacteria genome data enable the biologists to dig the evolutionary and genetic information of prokaryotic species from pan-genome sight. Therefore, the high-efficiency pipelines for pan-genome analysis are mostly needed. We have developed a new pan-genome analysis pipeline (PGAP), which can perform five analytic functions with only one command, including cluster analysis of functional genes, pan-genome profile analysis, genetic variation analysis of functional genes, species evolution analysis and function enrichment analysis of gene clusters. PGAPs performance has been evaluated on 11 Streptococcus pyogenes strains.'),
(76618, 2012, 'bio', 'Prediction and analysis of nucleotide-binding residues using sequence and sequence-derived structural descriptors', 'Chen, Ke|Mizianty, Marcin J|Kurgan, Lukasz', 'School of Computer Science and Software Engineering, Tianjin Polytechnic University, Hedong District, Tianjin 300160, PR of China.|School of Computer Science and Software Engineering, Tianjin Polytechnic University, Hedong District, Tianjin 300160, PR of China.|School of Computer Science and Software Engineering, Tianjin Polytechnic University, Hedong District, Tianjin 300160, PR of China.', 'China|China|China', 0, 'Binding Sites|Nucleotides|Protein Structure, Secondary|Proteins|Sequence Alignment|Software|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/btr657', '22130595', 'Nucleotides are multifunctional molecules that are essential for numerous biological processes. They serve as sources for chemical energy, participate in the cellular signaling and they are involved in the enzymatic reactions. The knowledge of the nucleotide-protein interactions helps with annotation of protein functions and finds applications in drug design.'),
(76619, 2012, 'bio', 'Which species is it? Species-driven gene name disambiguation using random walks over a mixture of adjacency matrices', 'Harmston, Nathan|Filsell, Wendy|Stumpf, Michael P H', 'Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London SW7 2AZ, UK.|Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London SW7 2AZ, UK.|Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London SW7 2AZ, UK.', 'United Kingdom|United Kingdom|United Kingdom', 5, 'Animals|Data Mining|Genes|Humans|MEDLINE|Software|Species Specificity|Support Vector Machine|Terminology as Topic|United States', 'Journal Article', '10.1093/bioinformatics/btr640', '22135416', 'The scientific literature contains a wealth of information about biological systems. Manual curation lacks the scalability to extract this information due to the ever-increasing numbers of papers being published. The development and application of text mining technologies has been proposed as a way of dealing with this problem. However, the inter-species ambiguity of the genomic nomenclature makes mapping of gene mentions identified in text to their corresponding Entrez gene identifiers an extremely difficult task. We propose a novel method, which transforms a MEDLINE record into a mixture of adjacency matrices, by performing a random walkover the resulting graph, we can perform multi-class supervised classification allowing the assignment of taxonomy identifiers to individual gene mentions. The ability to achieve good performance at this task has a direct impact on the performance of normalizing gene mentions to Entrez gene identifiers. Such graph mixtures add flexibility and allow us to generate probabilistic classification schemes that naturally reflect the uncertainties inherent, even in literature-derived data.'),
(76620, 2012, 'bio', 'SNPxGE(2): a database for human SNP-coexpression associations', 'Wang, Yupeng|Joseph, Sandeep J|Liu, Xinyu|Kelley, Michael|Rekaya, Romdhane', 'Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA. wyp1125@uga.edu|Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA. wyp1125@uga.edu|Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA. wyp1125@uga.edu|Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA. wyp1125@uga.edu|Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA. wyp1125@uga.edu', 'Georgia|Georgia|Georgia|Georgia|Georgia', 7, 'Databases, Genetic|Disease|Gene Expression Profiling|Genetics, Medical|HapMap Project|Humans|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btr663', '22135417', 'Recently, gene-coexpression relationships have been found to be often conditional and dynamic. Many studies have suggested that single nucleotide polymorphisms (SNPs) have impacts on gene expression variations in human populations.'),
(76621, 2012, 'bio', 'Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data', 'Karnovsky, Alla|Weymouth, Terry|Hull, Tim|Tarcea, V Glenn|Scardoni, Giovanni|Laudanna, Carlo|Sartor, Maureen A|Stringer, Kathleen A|Jagadish, H V|Burant, Charles|Athey, Brian|Omenn, Gilbert S', 'Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA. akarnovs@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA. akarnovs@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA. akarnovs@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA. akarnovs@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA. akarnovs@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA. akarnovs@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA. akarnovs@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA. akarnovs@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA. akarnovs@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA. akarnovs@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA. akarnovs@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, USA. akarnovs@umich.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 204, 'Adenocarcinoma|Animals|Gene Expression Profiling|Humans|Inflammation|Metabolic Networks and Pathways|Metabolomics|Mice|Pancreatic Neoplasms|Proteomics|Sepsis|Software', 'Journal Article', '10.1093/bioinformatics/btr661', '22135418', 'Metabolomics is a rapidly evolving field that holds promise to provide insights into genotype-phenotype relationships in cancers, diabetes and other complex diseases. One of the major informatics challenges is providing tools that link metabolite data with other types of high-throughput molecular data (e.g. transcriptomics, proteomics), and incorporate prior knowledge of pathways and molecular interactions.'),
(76622, 2012, 'bio', 'DMAN: a Java tool for analysis of multi-well differential scanning fluorimetry experiments', 'Wang, Conan K|Weeratunga, Saroja K|Pacheco, Chris M|Hofmann, Andreas', 'Structural Chemistry Program, Eskitis Institute for Cell and Molecular Therapies, Griffith University, Brisbane, Queensland 4111, Australia. conan.wang@griffith.edu.au|Structural Chemistry Program, Eskitis Institute for Cell and Molecular Therapies, Griffith University, Brisbane, Queensland 4111, Australia. conan.wang@griffith.edu.au|Structural Chemistry Program, Eskitis Institute for Cell and Molecular Therapies, Griffith University, Brisbane, Queensland 4111, Australia. conan.wang@griffith.edu.au|Structural Chemistry Program, Eskitis Institute for Cell and Molecular Therapies, Griffith University, Brisbane, Queensland 4111, Australia. conan.wang@griffith.edu.au', 'Australia|Australia|Australia|Australia', 0, 'Fluorometry|Real-Time Polymerase Chain Reaction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr664', '22135419', 'Differential scanning fluorimetry (DSF) is a rapid technique that can be used in structural biology to study protein-ligand interactions. We have developed DMAN, a novel tool to analyse multi-well plate data obtained in DSF experiments. DMAN is easy to install and provides a user-friendly interface. Multi-well plate layouts can be designed by the user and experimental data can be annotated and analysed by DMAN according to the specified plate layout. Statistical tests for significance are performed automatically, and graphical tools are also provided to assist in data analysis. The modular concept of this software will allow easy development of other multi-well plate analysis applications in the future.'),
(76623, 2012, 'bio', 'Integrated annotation and analysis of genetic variants from next-generation sequencing studies with variant tools', 'San Lucas, F Anthony|Wang, Gao|Scheet, Paul|Peng, Bo', 'Department of Epidemiology, University of Texas, MD Anderson Cancer Center, Houston, TX, USA.|Department of Epidemiology, University of Texas, MD Anderson Cancer Center, Houston, TX, USA.|Department of Epidemiology, University of Texas, MD Anderson Cancer Center, Houston, TX, USA.|Department of Epidemiology, University of Texas, MD Anderson Cancer Center, Houston, TX, USA.', 'United States|United States|United States|United States', 87, 'Genetic Variation|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Metabolic Networks and Pathways|Molecular Sequence Annotation|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr667', '22138362', 'Storing, annotating and analyzing variants from next-generation sequencing projects can be difficult due to the availability of a wide array of data formats, tools and annotation sources, as well as the sheer size of the data files. Useful tools, including the GATK, ANNOVAR and BEDTools can be integrated into custom pipelines for annotating and analyzing sequence variants. However, building flexible pipelines that support the tracking of variants alongside their samples, while enabling updated annotation and reanalyses, is not a simple task.'),
(76624, 2012, 'bio', 'Computing graphlet signatures of network nodes and motifs in Cytoscape with GraphletCounter', 'Whelan, Christopher|Sönmez, Kemal', 'Biomedical Engineering, Oregon Health and Science University, 20000 NW Walker Road, Beaverton, OR 97006, USA. whelanch@ohsu.edu|Biomedical Engineering, Oregon Health and Science University, 20000 NW Walker Road, Beaverton, OR 97006, USA. whelanch@ohsu.edu', 'United States|United States', 7, 'Humans|Software|Systems Biology|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr637', '22155862', 'Biological network analysis can be enhanced by examining the connections between nodes and the rest of the network. For this purpose we have developed GraphletCounter, an open-source software tool for computing graphlet degree signatures that can operate on its own or as a plug-in to the network analysis environment Cytoscape. A unique characteristic of GraphletCounter is its ability to compute the graphlet signatures of network motifs, which can be specified by files generated by the motif-finding tool mfinder. GraphletCounter displays graphlet signatures for visual inspection within Cytoscape, and can output graphlet data for integration with larger workflows.'),
(76625, 2012, 'bio', 'BPDA2d--a 2D global optimization-based Bayesian peptide detection algorithm for liquid chromatograph-mass spectrometry', 'Sun, Youting|Zhang, Jianqiu|Braga-Neto, Ulisses|Dougherty, Edward R', 'Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.', 'United States|United States|United States|United States', 7, 'Algorithms|Bayes Theorem|Chromatography, Liquid|Mass Spectrometry|Peptides|Probability|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btr675', '22155863', 'Peptide detection is a crucial step in mass spectrometry (MS) based proteomics. Most existing algorithms are based upon greedy isotope template matching and thus may be prone to error propagation and ineffective to detect overlapping peptides. In addition, existing algorithms usually work at different charge states separately, isolating useful information that can be drawn from other charge states, which may lead to poor detection of low abundance peptides.'),
(76626, 2012, 'bio', 'A simple statistical test to infer the causality of target/phenotype correlation from small molecule phenotypic screens', 'Wei, Xin|Hoffman, Ann F|Hamilton, Shannon M|Xiang, Qing|He, Yang|So, W Venus|So, Sung-Sau|Mark, David', 'Pharmaceutical Research and Early Development Informatics/Statistics, F. Hoffmann-La Roche, Nutley, NJ 07110, USA. xin.wei@roche.com|Pharmaceutical Research and Early Development Informatics/Statistics, F. Hoffmann-La Roche, Nutley, NJ 07110, USA. xin.wei@roche.com|Pharmaceutical Research and Early Development Informatics/Statistics, F. Hoffmann-La Roche, Nutley, NJ 07110, USA. xin.wei@roche.com|Pharmaceutical Research and Early Development Informatics/Statistics, F. Hoffmann-La Roche, Nutley, NJ 07110, USA. xin.wei@roche.com|Pharmaceutical Research and Early Development Informatics/Statistics, F. Hoffmann-La Roche, Nutley, NJ 07110, USA. xin.wei@roche.com|Pharmaceutical Research and Early Development Informatics/Statistics, F. Hoffmann-La Roche, Nutley, NJ 07110, USA. xin.wei@roche.com|Pharmaceutical Research and Early Development Informatics/Statistics, F. Hoffmann-La Roche, Nutley, NJ 07110, USA. xin.wei@roche.com|Pharmaceutical Research and Early Development Informatics/Statistics, F. Hoffmann-La Roche, Nutley, NJ 07110, USA. xin.wei@roche.com', 'United States|United States|United States|United States|United States|United States|United States|United States', 4, 'Cell Survival|Cell-Free System|Drug Discovery|HeLa Cells|High-Throughput Screening Assays|Humans|Protein Kinase Inhibitors', 'Journal Article', '10.1093/bioinformatics/btr676', '22155864', 'Cell-based phenotypic screens using small molecule inhibitors is an important technology for early drug discovery if the relationship between the disease-related cellular phenotype and inhibitors biological targets can be determined. However, chemical inhibitors are rightfully believed to be less specific than perturbation by biological agents, such as antibody and small inference RNA. Therefore, it is often a challenge in small molecule phenotypic screening to infer the causality between a particular cellular phenotype and the inactivation of the responsible protein due to the off-target effect of the inhibitors.'),
(76627, 2012, 'bio', 'B-SOLANA: an approach for the analysis of two-base encoding bisulfite sequencing data', 'Kreck, Benjamin|Marnellos, George|Richter, Julia|Krueger, Felix|Siebert, Reiner|Franke, Andre', 'Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany. b.kreck@ikmb.uni-kiel.de|Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany. b.kreck@ikmb.uni-kiel.de|Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany. b.kreck@ikmb.uni-kiel.de|Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany. b.kreck@ikmb.uni-kiel.de|Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany. b.kreck@ikmb.uni-kiel.de|Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany. b.kreck@ikmb.uni-kiel.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 18, 'DNA Methylation|Genome, Human|Genome-Wide Association Study|Humans|Sequence Alignment|Sequence Analysis, DNA|Software|Sulfites', 'Journal Article', '10.1093/bioinformatics/btr660', '22155865', 'Bisulfite sequencing, a combination of bisulfite treatment and high-throughput sequencing, has proved to be a valuable method for measuring DNA methylation at single base resolution. Here, we present B-SOLANA, an approach for the analysis of two-base encoding (colorspace) bisulfite sequencing data on the SOLiD platform of Life Technologies. It includes the alignment of bisulfite sequences and the determination of methylation levels in CpG as well as non-CpG sequence contexts. B-SOLANA enables a fast and accurate analysis of large raw sequence datasets.'),
(76628, 2012, 'bio', 'InFiRe -- a novel computational method for the identification of insertion sites in transposon mutagenized bacterial genomes', 'Shevchuk, Olga|Roselius, Louisa|Günther, Gabriele|Klein, Johannes|Jahn, Dieter|Steinert, Michael|Münch, Richard', 'Institute of Microbiology, Technische Universität Braunschweig, Spielmannstrasse 7, 38106 Braunschweig, Germany.|Institute of Microbiology, Technische Universität Braunschweig, Spielmannstrasse 7, 38106 Braunschweig, Germany.|Institute of Microbiology, Technische Universität Braunschweig, Spielmannstrasse 7, 38106 Braunschweig, Germany.|Institute of Microbiology, Technische Universität Braunschweig, Spielmannstrasse 7, 38106 Braunschweig, Germany.|Institute of Microbiology, Technische Universität Braunschweig, Spielmannstrasse 7, 38106 Braunschweig, Germany.|Institute of Microbiology, Technische Universität Braunschweig, Spielmannstrasse 7, 38106 Braunschweig, Germany.|Institute of Microbiology, Technische Universität Braunschweig, Spielmannstrasse 7, 38106 Braunschweig, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 2, 'Algorithms|DNA Transposable Elements|DNA, Bacterial|Genome, Bacterial|Internet|Legionella pneumophila|Mutagenesis, Insertional|Software', 'Journal Article', '10.1093/bioinformatics/btr672', '22155866', 'InFiRe, Insertion Finder via Restriction digest, is a novel software tool that allows for the computational identification of transposon insertion sites in known bacterial genome sequences after transposon mutagenesis experiments. The approach is based on the fact that restriction endonuclease digestions of bacterial DNA yield a unique pattern of DNA fragments with defined sizes. Transposon insertion changes the size of the hosting DNA fragment by a known number of base pairs. The exact size of this fragment can be determined by Southern blot hybridization. Subsequently, the position of insertion can be identified with computational analysis. The outlined method provides a solid basis for the establishment of a new high-throughput technology.'),
(76629, 2012, 'bio', 'Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort', 'Wang, Hua|Nie, Feiping|Huang, Heng|Kim, Sungeun|Nho, Kwangsik|Risacher, Shannon L|Saykin, Andrew J|Shen, Li|Alzheimers Disease Neuroimaging Initiative', 'Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 97, 'Algorithms|Alzheimer Disease|Brain|Cognitive Dysfunction|Cohort Studies|Genotype|Humans|Neuroimaging|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Regression Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btr649', '22155867', 'Recent advances in high-throughput genotyping and brain imaging techniques enable new approaches to study the influence of genetic variation on brain structures and functions. Traditional association studies typically employ independent and pairwise univariate analysis, which treats single nucleotide polymorphisms (SNPs) and quantitative traits (QTs) as isolated units and ignores important underlying interacting relationships between the units. New methods are proposed here to overcome this limitation.'),
(76630, 2012, 'bio', 'GenomeRunner: automating genome exploration', 'Dozmorov, Mikhail G|Cara, Lukas R|Giles, Cory B|Wren, Jonathan D', 'Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104-5005, USA. mikhail-dozmorov@omrf.org|Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104-5005, USA. mikhail-dozmorov@omrf.org|Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104-5005, USA. mikhail-dozmorov@omrf.org|Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104-5005, USA. mikhail-dozmorov@omrf.org', 'United States|United States|United States|United States', 20, 'Automation|Databases, Genetic|Genomics|Molecular Sequence Annotation|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btr666', '22155868', 'One of the challenges in interpreting high-throughput genomic studies such as a genome-wide associations, microarray or ChIP-seq is their open-ended nature-once a set of experimentally identified regions is identified as statistically significant, at least two questions arise: (i) besides P-value, do any of these significant regions stand out in terms of biological implications? (ii) Does the set of significant regions, as a whole, have anything in common genome wide? These issues are difficult to address because of the growing number of annotated genomic features (e.g. single nucleotide polymorphisms, transcription factor binding sites, methylation peaks, etc.), and it is difficult to know a priori which features would be most fruitful to analyze. Our goal is to provide partial automation of this process to begin examining associations between experimental features and annotated genomic regions in a hypothesis-free, data-driven manner.'),
(76631, 2012, 'bio', 'Identification and removal of ribosomal RNA sequences from metatranscriptomes', 'Schmieder, Robert|Lim, Yan Wei|Edwards, Robert', 'Department of Computer Science, San Diego State University, San Diego, CA 92182, USA. rschmied@sciences.sdsu.edu|Department of Computer Science, San Diego State University, San Diego, CA 92182, USA. rschmied@sciences.sdsu.edu|Department of Computer Science, San Diego State University, San Diego, CA 92182, USA. rschmied@sciences.sdsu.edu', 'United States|United States|United States', 114, 'Humans|Internet|Metagenome|Programming Languages|RNA, Ribosomal|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btr669', '22155869', 'Here, we present riboPicker, a robust framework for the rapid, automated identification and removal of ribosomal RNA sequences from metatranscriptomic datasets. The results can be exported for subsequent analysis, and the databases used for the web-based version are updated on a regular basis. riboPicker categorizes rRNA-like sequences and provides graphical visualizations and tabular outputs of ribosomal coverage, alignment results and taxonomic classifications.'),
(76632, 2012, 'bio', 'Control-FREEC: a tool for assessing copy number and allelic content using next-generation sequencing data', 'Boeva, Valentina|Popova, Tatiana|Bleakley, Kevin|Chiche, Pierre|Cappo, Julie|Schleiermacher, Gudrun|Janoueix-Lerosey, Isabelle|Delattre, Olivier|Barillot, Emmanuel', 'Institut Curie, Paris 75248, France. freec@curie.fr|Institut Curie, Paris 75248, France. freec@curie.fr|Institut Curie, Paris 75248, France. freec@curie.fr|Institut Curie, Paris 75248, France. freec@curie.fr|Institut Curie, Paris 75248, France. freec@curie.fr|Institut Curie, Paris 75248, France. freec@curie.fr|Institut Curie, Paris 75248, France. freec@curie.fr|Institut Curie, Paris 75248, France. freec@curie.fr|Institut Curie, Paris 75248, France. freec@curie.fr', 'France|France|France|France|France|France|France|France|France', 370, 'Alleles|DNA Copy Number Variations|Humans|Loss of Heterozygosity|Neoplasms|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btr670', '22155870', 'More and more cancer studies use next-generation sequencing (NGS) data to detect various types of genomic variation. However, even when researchers have such data at hand, single-nucleotide polymorphism arrays have been considered necessary to assess copy number alterations and especially loss of heterozygosity (LOH). Here, we present the tool Control-FREEC that enables automatic calculation of copy number and allelic content profiles from NGS data, and consequently predicts regions of genomic alteration such as gains, losses and LOH. Taking as input aligned reads, Control-FREEC constructs copy number and B-allele frequency profiles. The profiles are then normalized, segmented and analyzed in order to assign genotype status (copy number and allelic content) to each genomic region. When a matched normal sample is provided, Control-FREEC discriminates somatic from germline events. Control-FREEC is able to analyze overdiploid tumor samples and samples contaminated by normal cells. Low mappability regions can be excluded from the analysis using provided mappability tracks.'),
(76633, 2012, 'bio', 'RRBSMAP: a fast, accurate and user-friendly alignment tool for reduced representation bisulfite sequencing', 'Xi, Yuanxin|Bock, Christoph|Müller, Fabian|Sun, Deqiang|Meissner, Alexander|Li, Wei', 'Division of Biostatistics, Dan L Duncan Cancer Center and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA.|Division of Biostatistics, Dan L Duncan Cancer Center and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA.|Division of Biostatistics, Dan L Duncan Cancer Center and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA.|Division of Biostatistics, Dan L Duncan Cancer Center and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA.|Division of Biostatistics, Dan L Duncan Cancer Center and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA.|Division of Biostatistics, Dan L Duncan Cancer Center and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA.', 'United States|United States|United States|United States|United States|United States', 59, 'DNA Methylation|Embryonic Stem Cells|Genomics|Humans|Sequence Alignment|Sequence Analysis, DNA|Software|Sulfites|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btr668', '22155871', 'Reduced representation bisulfite sequencing (RRBS) is a powerful yet cost-efficient method for studying DNA methylation on a genomic scale. RRBS involves restriction-enzyme digestion, bisulfite conversion and size selection, resulting in DNA sequencing data that require special bioinformatic handling. Here, we describe RRBSMAP, a short-read alignment tool that is designed for handling RRBS data in a user-friendly and scalable way. RRBSMAP uses wildcard alignment, and avoids the need for any preprocessing or post-processing steps. We benchmarked RRBSMAP against a well-validated MAQ-based pipeline for RRBS read alignment and observed similar accuracy but much improved runtime performance, easier handling and better scaling to large sample sets. In summary, RRBSMAP removes bioinformatic hurdles and reduces the computational burden of large-scale epigenome association studies performed with RRBS.'),
(76634, 2012, 'bio', 'SomaticSniper: identification of somatic point mutations in whole genome sequencing data', 'Larson, David E|Harris, Christopher C|Chen, Ken|Koboldt, Daniel C|Abbott, Travis E|Dooling, David J|Ley, Timothy J|Mardis, Elaine R|Wilson, Richard K|Ding, Li', 'The Genome Institute, Washington University, St Louis, MO 63108, USA. delarson@wustl.edu|The Genome Institute, Washington University, St Louis, MO 63108, USA. delarson@wustl.edu|The Genome Institute, Washington University, St Louis, MO 63108, USA. delarson@wustl.edu|The Genome Institute, Washington University, St Louis, MO 63108, USA. delarson@wustl.edu|The Genome Institute, Washington University, St Louis, MO 63108, USA. delarson@wustl.edu|The Genome Institute, Washington University, St Louis, MO 63108, USA. delarson@wustl.edu|The Genome Institute, Washington University, St Louis, MO 63108, USA. delarson@wustl.edu|The Genome Institute, Washington University, St Louis, MO 63108, USA. delarson@wustl.edu|The Genome Institute, Washington University, St Louis, MO 63108, USA. delarson@wustl.edu|The Genome Institute, Washington University, St Louis, MO 63108, USA. delarson@wustl.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 305, 'Genome, Human|Humans|Neoplasms|Point Mutation|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btr665', '22155872', 'The sequencing of tumors and their matched normals is frequently used to study the genetic composition of cancer. Despite this fact, there remains a dearth of available software tools designed to compare sequences in pairs of samples and identify sites that are likely to be unique to one sample.'),
(76635, 2012, 'bio', 'GWAtoolbox: an R package for fast quality control and handling of genome-wide association studies meta-analysis data', 'Fuchsberger, Christian|Taliun, Daniel|Pramstaller, Peter P|Pattaro, Cristian|CKDGen consortium', 'Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA. cfuchsb@umich.edu|Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA. cfuchsb@umich.edu|Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA. cfuchsb@umich.edu|Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA. cfuchsb@umich.edu|Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA. cfuchsb@umich.edu', 'United States|United States|United States|United States|United States', 23, 'Genome-Wide Association Study|HapMap Project|Humans|Meta-Analysis as Topic|Quality Control|Software', 'Journal Article', '10.1093/bioinformatics/btr679', '22155946', 'The GWAtoolbox is an R package that standardizes and accelerates the handling of data from genome-wide association studies (GWAS), particularly in the context of large-scale GWAS meta-analyses. A key feature of GWAtoolbox is its ability to perform quality control (QC) of any number of files in a matter of minutes. The implemented workflow has been structured to check three particular data quality aspects: (i) data formatting, (ii) quality of the GWAS results and (iii) data consistency across studies. Output consists of an extensive list of quality statistics and plots which allow inspection of individual files and between-study comparison to identify systematic bias.'),
(76636, 2012, 'bio', 'M(3): an improved SNP calling algorithm for Illumina BeadArray data', 'Li, Gengxin|Gelernter, Joel|Kranzler, Henry R|Zhao, Hongyu', 'Biostatistics Division, Department of Epidemiology and Public Health, Yale University, New Haven, CT 06520, USA.|Biostatistics Division, Department of Epidemiology and Public Health, Yale University, New Haven, CT 06520, USA.|Biostatistics Division, Department of Epidemiology and Public Health, Yale University, New Haven, CT 06520, USA.|Biostatistics Division, Department of Epidemiology and Public Health, Yale University, New Haven, CT 06520, USA.', 'United States|United States|United States|United States', 18, 'Algorithms|Case-Control Studies|Cluster Analysis|Computational Biology|Genotype|HapMap Project|Humans|Models, Genetic|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btr673', '22155947', 'Genotype calling from high-throughput platforms such as Illumina and Affymetrix is a critical step in data processing, so that accurate information on genetic variants can be obtained for phenotype-genotype association studies. A number of algorithms have been developed to infer genotypes from data generated through the Illumina BeadStation platform, including GenCall, GenoSNP, Illuminus and CRLMM. Most of these algorithms are built on population-based statistical models to genotype every SNP in turn, such as GenCall with the GenTrain clustering algorithm, and require a large reference population to perform well. These approaches may not work well for rare variants where only a small proportion of the individuals carry the variant. A fundamentally different approach, implemented in GenoSNP, adopts a single nucleotide polymorphism (SNP)-based model to infer genotypes of all the SNPs in one individual, making it an appealing alternative to call rare variants. However, compared to the population-based strategies, more SNPs in GenoSNP may fail the Hardy-Weinberg Equilibrium test. To take advantage of both strategies, we propose a two-stage SNP calling procedure, named the modified mixture model (M(3)), to improve call accuracy for both common and rare variants. The effectiveness of our approach is demonstrated through applications to genotype calling on a set of HapMap samples used for quality control purpose in a large case-control study of cocaine dependence. The increase in power with M(3) is greater for rare variants than for common variants depending on the model.'),
(76637, 2011, 'bio', 'Optimized application of penalized regression methods to diverse genomic data', 'Waldron, Levi|Pintilie, Melania|Tsao, Ming-Sound|Shepherd, Frances A|Huttenhower, Curtis|Jurisica, Igor', 'Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA.', 'United States|United States|United States|United States|United States|United States', 45, 'Bacteria|Computational Biology|Computer Simulation|Feces|Gene Expression Profiling|Humans|Metagenomics|Neoplasms|Obesity|Regression Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btr591', '22156367', 'Penalized regression methods have been adopted widely for high-dimensional feature selection and prediction in many bioinformatic and biostatistical contexts. While their theoretical properties are well-understood, specific methodology for their optimal application to genomic data has not been determined.'),
(76638, 2012, 'bio', 'seeQTL: a searchable database for human eQTLs', 'Xia, Kai|Shabalin, Andrey A|Huang, Shunping|Madar, Vered|Zhou, Yi-Hui|Wang, Wei|Zou, Fei|Sun, Wei|Sullivan, Patrick F|Wright, Fred A', 'Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. kxia@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. kxia@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. kxia@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. kxia@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. kxia@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. kxia@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. kxia@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. kxia@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. kxia@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. kxia@bios.unc.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 84, 'Databases, Genetic|Genome-Wide Association Study|HapMap Project|Humans|Quantitative Trait Loci|Software', 'Journal Article', '10.1093/bioinformatics/btr678', '22171328', 'seeQTL is a comprehensive and versatile eQTL database, including various eQTL studies and a meta-analysis of HapMap eQTL information. The database presents eQTL association results in a convenient browser, using both segmented local-association plots and genome-wide Manhattan plots.'),
(76639, 2012, 'bio', 'Transformations for the compression of FASTQ quality scores of next-generation sequencing data', 'Wan, Raymond|Anh, Vo Ngoc|Asai, Kiyoshi', 'Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Chiba-ken 277-8561, Tokyo 135-0064, Japan. rwan@cuhk.edu.hk|Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Chiba-ken 277-8561, Tokyo 135-0064, Japan. rwan@cuhk.edu.hk|Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Chiba-ken 277-8561, Tokyo 135-0064, Japan. rwan@cuhk.edu.hk', 'Japan|Japan|Japan', 39, 'Data Compression|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr689', '22171329', 'The growth of next-generation sequencing means that more effective and efficient archiving methods are needed to store the generated data for public dissemination and in anticipation of more mature analytical methods later. This article examines methods for compressing the quality score component of the data to partly address this problem.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76640, 2012, 'bio', 'SitePainter: a tool for exploring biogeographical patterns', 'Gonzalez, Antonio|Stombaugh, Jesse|Lauber, Christian L|Fierer, Noah|Knight, Rob', 'Department of Computer Science, University of Colorado at Boulder and Howard Hughes Medical Institute, Boulder, CO 80309, USA. antoniog@colorado.edu|Department of Computer Science, University of Colorado at Boulder and Howard Hughes Medical Institute, Boulder, CO 80309, USA. antoniog@colorado.edu|Department of Computer Science, University of Colorado at Boulder and Howard Hughes Medical Institute, Boulder, CO 80309, USA. antoniog@colorado.edu|Department of Computer Science, University of Colorado at Boulder and Howard Hughes Medical Institute, Boulder, CO 80309, USA. antoniog@colorado.edu|Department of Computer Science, University of Colorado at Boulder and Howard Hughes Medical Institute, Boulder, CO 80309, USA. antoniog@colorado.edu', 'United States|United States|United States|United States|United States', 17, 'Bacteria|Hand|Humans|Metagenome|Metagenomics|Software', 'Journal Article', '10.1093/bioinformatics/btr685', '22171330', 'As microbial ecologists take advantage of high-throughput analytical techniques to describe microbial communities across ever-increasing numbers of samples, the need for new analysis tools that reveal the intrinsic spatial patterns and structures of these populations is crucial. Here we present SitePainter, an interactive graphical tool that allows investigators to create or upload pictures of their study site, load diversity analyses data and display both diversity and taxonomy results in a spatial context. Features of SitePainter include: visualizing xcexb1 -diversity, using taxonomic summaries, visualizing xcexb2 -diversity, using results from multidimensional scaling methods, and animating relationships among microbial taxa or pathways overtime. SitePainter thus increases the visual power and ability to explore spatially explicit studies.'),
(76641, 2012, 'bio', 'Identifying small interfering RNA loci from high-throughput sequencing data', 'Hardcastle, Thomas J|Kelly, Krystyna A|Baulcombe, David C', 'Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, UK. tjh48@cam.ac.uk|Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, UK. tjh48@cam.ac.uk|Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, UK. tjh48@cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 17, 'Arabidopsis|Computer Simulation|Genome, Plant|High-Throughput Nucleotide Sequencing|RNA, Plant|RNA, Small Interfering|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btr687', '22171331', 'Small interfering RNAs (siRNAs) are produced from much longer sequences of double-stranded RNA precursors through cleavage by Dicer or a Dicer-like protein. These small RNAs play a key role in genetic and epigenetic regulation, however, a full understanding of the mechanisms by which they operate depends on the characterization of the precursors from which they are derived.'),
(76642, 2012, 'bio', 'HydroPaCe: understanding and predicting cross-inhibition in serine proteases through hydrophobic patch centroids', 'Gonçalves-Almeida, V M|Pires, D E V|de Melo-Minardi, R C|da Silveira, C H|Meira, W|Santoro, M M', 'Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil. valdetemg@ufmg.br|Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil. valdetemg@ufmg.br|Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil. valdetemg@ufmg.br|Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil. valdetemg@ufmg.br|Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil. valdetemg@ufmg.br|Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil. valdetemg@ufmg.br', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 13, 'Animals|Hydrophobic and Hydrophilic Interactions|Models, Biological|Ovomucin|Proteins|Serine Proteases|Software|Turkeys', 'Journal Article', '10.1093/bioinformatics/btr680', '22171332', 'Protein-protein interfaces contain important information about molecular recognition. The discovery of conserved patterns is essential for understanding how substrates and inhibitors are bound and for predicting molecular binding. When an inhibitor binds to different enzymes (e.g. dissimilar sequences, structures or mechanisms what we call cross-inhibition), identification of invariants is a difficult task for which traditional methods may fail.'),
(76643, 2012, 'bio', 'JDet: interactive calculation and visualization of function-related conservation patterns in multiple sequence alignments and structures', 'Muth, Thilo|García-Martín, Juan A|Rausell, Antonio|Juan, David|Valencia, Alfonso|Pazos, Florencio', 'Computational Systems Biology Group, National Center for Biotechnology (CNB-CSIC), 28049 Madrid, Spain.|Computational Systems Biology Group, National Center for Biotechnology (CNB-CSIC), 28049 Madrid, Spain.|Computational Systems Biology Group, National Center for Biotechnology (CNB-CSIC), 28049 Madrid, Spain.|Computational Systems Biology Group, National Center for Biotechnology (CNB-CSIC), 28049 Madrid, Spain.|Computational Systems Biology Group, National Center for Biotechnology (CNB-CSIC), 28049 Madrid, Spain.|Computational Systems Biology Group, National Center for Biotechnology (CNB-CSIC), 28049 Madrid, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain', 12, 'Amino Acid Sequence|Models, Molecular|Molecular Sequence Data|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btr688', '22171333', 'We have implemented in a single package all the features required for extracting, visualizing and manipulating fully conserved positions as well as those with a family-dependent conservation pattern in multiple sequence alignments. The program allows, among other things, to run different methods for extracting these positions, combine the results and visualize them in protein 3D structures and sequence spaces.'),
(76644, 2012, 'bio', 'Detection of microRNAs in color space', 'Marco, Antonio|Griffiths-Jones, Sam', 'University of Manchester, M13 9PT Manchester, UK. antonio.marco@manchester.ac.uk|University of Manchester, M13 9PT Manchester, UK. antonio.marco@manchester.ac.uk', 'United Kingdom|United Kingdom', 15, 'Algorithms|Animals|Bees|Color|High-Throughput Nucleotide Sequencing|MicroRNAs|Sequence Analysis, DNA|Sequence Analysis, RNA|Tribolium', 'Journal Article', '10.1093/bioinformatics/btr686', '22171334', 'Deep sequencing provides inexpensive opportunities to characterize the transcriptional diversity of known genomes. The AB SOLiD technology generates millions of short sequencing reads in color-space, that is, the raw data is a sequence of colors, where each color represents 2 nt and each nucleotide is represented by two consecutive colors. This strategy is purported to have several advantages, including increased ability to distinguish sequencing errors from polymorphisms. Several programs have been developed to map short reads to genomes in color space. However, a number of previously unexplored technical issues arise when using SOLiD technology to characterize microRNAs.'),
(76645, 2012, 'bio', 'Improved mean estimation and its application to diagonal discriminant analysis', 'Tong, Tiejun|Chen, Liang|Zhao, Hongyu', 'Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong. tongt@hkbu.edu.hk|Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong. tongt@hkbu.edu.hk|Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong. tongt@hkbu.edu.hk', 'Hong Kong|Hong Kong|Hong Kong', 0, 'Discriminant Analysis|Gene Expression Profiling|Humans|Leukemia|Oligonucleotide Array Sequence Analysis|Regression Analysis|Sample Size', 'Journal Article', '10.1093/bioinformatics/btr690', '22171335', 'High-dimensional data such as microarrays have created new challenges to traditional statistical methods. One such example is on class prediction with high-dimension, low-sample size data. Due to the small sample size, the sample mean estimates are usually unreliable. As a consequence, the performance of the class prediction methods using the sample mean may also be unsatisfactory. To obtain more accurate estimation of parameters some statistical methods, such as regularizations through shrinkage, are often desired.'),
(76646, 2012, 'bio', 'MTBindingSim: simulate protein binding to microtubules', 'Philip, Julia T|Pence, Charles H|Goodson, Holly V', 'Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA. jphilip@nd.edu|Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA. jphilip@nd.edu|Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA. jphilip@nd.edu', 'United States|United States|United States', 0, 'Computational Biology|Kinetics|Microtubules|Models, Biological|Programming Languages|Protein Binding|Software', 'Journal Article', '10.1093/bioinformatics/btr684', '22171336', 'Many protein-protein interactions are more complex than can be accounted for by 1:1 binding models. However, biochemists have few tools available to help them recognize and predict the behaviors of these more complicated systems, making it difficult to design experiments that distinguish between possible binding models. MTBindingSim provides researchers with an environment in which they can rapidly compare different models of binding for a given scenario. It is written specifically with microtubule polymers in mind, but many of its models apply equally well to any polymer or any protein-protein interaction. MTBindingSim can thus both help in training intuition about binding models and with experimental design.'),
(76647, 2012, 'bio', 'Novel search method for the discovery of functional relationships', 'Ramírez, Fidel|Lawyer, Glenn|Albrecht, Mario', 'Max Planck Institute for Informatics, Campus E1.4, 66123 Saarbrücken, Germany.|Max Planck Institute for Informatics, Campus E1.4, 66123 Saarbrücken, Germany.|Max Planck Institute for Informatics, Campus E1.4, 66123 Saarbrücken, Germany.', 'Germany|Germany|Germany', 0, 'Algorithms|Computational Biology|Databases, Genetic|Genes|Humans|Internet|Molecular Sequence Annotation|Proteins|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btr631', '22180409', 'Numerous annotations are available that functionally characterize genes and proteins with regard to molecular process, cellular localization, tissue expression, protein domain composition, protein interaction, disease association and other properties. Searching this steadily growing amount of information can lead to the discovery of new biological relationships between genes and proteins. To facilitate the searches, methods are required that measure the annotation similarity of genes and proteins. However, most current similarity methods are focused only on annotations from the Gene Ontology (GO) and do not take other annotation sources into account.'),
(76648, 2012, 'bio', 'PopDrowser: the Population Drosophila Browser', 'Ràmia, Miquel|Librado, Pablo|Casillas, Sònia|Rozas, Julio|Barbadilla, Antonio', 'Institut de Biotecnologia i de Biomedicina and Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain.|Institut de Biotecnologia i de Biomedicina and Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain.|Institut de Biotecnologia i de Biomedicina and Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain.|Institut de Biotecnologia i de Biomedicina and Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain.|Institut de Biotecnologia i de Biomedicina and Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain', 13, 'Animals|Biological Evolution|Drosophila|Drosophila Proteins|Drosophila melanogaster|Genetic Variation|Genetics, Population|Internet|Linkage Disequilibrium|Polymorphism, Genetic', 'Journal Article', '10.1093/bioinformatics/btr691', '22180410', 'The completion of 168 genome sequences from a single population of Drosophila melanogaster provides a global view of genomic variation and an understanding of the evolutionary forces shaping the patterns of DNA polymorphism and divergence along the genome.'),
(76649, 2012, 'bio', 'The Virtual Fly Brain browser and query interface', 'Milyaev, Nestor|Osumi-Sutherland, David|Reeve, Simon|Burton, Nicholas|Baldock, Richard A|Armstrong, J Douglas', 'School of Informatics, University of Edinburgh, Edinburgh, UK.|School of Informatics, University of Edinburgh, Edinburgh, UK.|School of Informatics, University of Edinburgh, Edinburgh, UK.|School of Informatics, University of Edinburgh, Edinburgh, UK.|School of Informatics, University of Edinburgh, Edinburgh, UK.|School of Informatics, University of Edinburgh, Edinburgh, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 57, 'Animals|Brain|Brain Mapping|Databases, Factual|Drosophila|Internet|Neurosciences|Software', 'Journal Article', '10.1093/bioinformatics/btr677', '22180411', 'Sources of neuroscience data in Drosophila are diverse and disparate making integrated search and retrieval difficult. A major obstacle to this is the lack of a comprehensive and logically structured anatomical framework and an intuitive interface.'),
(76650, 2012, 'bio', 'The role of miRNAs in complex formation and control', 'Goh, Wilson Wen Bin|Oikawa, Hirotaka|Sng, Judy Chia Ghee|Sergot, Marek|Wong, Limsoon', 'Department of Computing, Imperial College London, London, UK.|Department of Computing, Imperial College London, London, UK.|Department of Computing, Imperial College London, London, UK.|Department of Computing, Imperial College London, London, UK.|Department of Computing, Imperial College London, London, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Brain|Epigenomics|Gene Expression Regulation|Humans|Mice|MicroRNAs|Multiprotein Complexes|Myocardium|Organ Specificity|Valproic Acid', 'Journal Article', '10.1093/bioinformatics/btr693', '22180412', 'microRibonucleic acid (miRNAs) are small regulatory molecules that act by mRNA degradation or via translational repression. Although many miRNAs are ubiquitously expressed, a small subset have differential expression patterns that may give rise to tissue-specific complexes.'),
(76651, 2012, 'bio', 'Minimal cut sets in a metabolic network are elementary modes in a dual network', 'Ballerstein, Kathrin|von Kamp, Axel|Klamt, Steffen|Haus, Utz-Uwe', 'Institute for Operations Research, Department of Mathematics, ETH Zürich, Rämistrasse 101, 8092 Zürich, Switzerland.|Institute for Operations Research, Department of Mathematics, ETH Zürich, Rämistrasse 101, 8092 Zürich, Switzerland.|Institute for Operations Research, Department of Mathematics, ETH Zürich, Rämistrasse 101, 8092 Zürich, Switzerland.|Institute for Operations Research, Department of Mathematics, ETH Zürich, Rämistrasse 101, 8092 Zürich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 38, 'Algorithms|Computational Biology|Escherichia coli|Metabolic Networks and Pathways', 'Journal Article', '10.1093/bioinformatics/btr674', '22190691', 'Elementary modes (EMs) and minimal cut sets (MCSs) provide important techniques for metabolic network modeling. Whereas EMs describe minimal subnetworks that can function in steady state, MCSs are sets of reactions whose removal will disable certain network functions. Effective algorithms were developed for EM computation while calculation of MCSs is typically addressed by indirect methods requiring the computation of EMs as initial step.'),
(76652, 2012, 'bio', 'ESpritz: accurate and fast prediction of protein disorder', 'Walsh, Ian|Martin, Alberto J M|Di Domenico, Tomàs|Tosatto, Silvio C E', 'Department of Biology, University of Padua, Viale G. Colombo 3, I-35131 Padova, Italy.|Department of Biology, University of Padua, Viale G. Colombo 3, I-35131 Padova, Italy.|Department of Biology, University of Padua, Viale G. Colombo 3, I-35131 Padova, Italy.|Department of Biology, University of Padua, Viale G. Colombo 3, I-35131 Padova, Italy.', 'Italy|Italy|Italy|Italy', 225, 'Algorithms|Animals|Humans|Neural Networks (Computer)|Protein Conformation|Protein Folding|Proteins', 'Journal Article', '10.1093/bioinformatics/btr682', '22190692', 'Intrinsically disordered regions are key for the function of numerous proteins, and the scant available experimental annotations suggest the existence of different disorder flavors. While efficient predictions are required to annotate entire genomes, most existing methods require sequence profiles for disorder prediction, making them cumbersome for high-throughput applications.'),
(76653, 2012, 'bio', 'htSeqTools: high-throughput sequencing quality control, processing and visualization in R', 'Planet, Evarist|Attolini, Camille Stephan-Otto|Reina, Oscar|Flores, Oscar|Rossell, David', 'Biostatistics and Bioinformatics Unit, Institute for Research in Biomedicine of Barcelona, Barcelona, Spain.|Biostatistics and Bioinformatics Unit, Institute for Research in Biomedicine of Barcelona, Barcelona, Spain.|Biostatistics and Bioinformatics Unit, Institute for Research in Biomedicine of Barcelona, Barcelona, Spain.|Biostatistics and Bioinformatics Unit, Institute for Research in Biomedicine of Barcelona, Barcelona, Spain.|Biostatistics and Bioinformatics Unit, Institute for Research in Biomedicine of Barcelona, Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain', 31, 'Genomics|High-Throughput Nucleotide Sequencing|Humans|Internet|Oligonucleotide Array Sequence Analysis|Quality Control|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1093/bioinformatics/btr700', '22199381', 'We provide a Bioconductor package with quality assessment, processing and visualization tools for high-throughput sequencing data, with emphasis in ChIP-seq and RNA-seq studies. It includes detection of outliers and biases, inefficient immuno-precipitation and overamplification artifacts, de novo identification of read-rich genomic regions and visualization of the location and coverage of genomic region lists.'),
(76654, 2012, 'bio', 'Modeling mechanistic biological networks: an advanced Boolean approach', 'Handorf, T|Klipp, E', 'Department of Theoretical Biophysics, Humboldt-Universität zu Berlin, Invalidenstr. 42, 10115 Berlin, Germany. handorf@physik.hu-berlin.de|Department of Theoretical Biophysics, Humboldt-Universität zu Berlin, Invalidenstr. 42, 10115 Berlin, Germany. handorf@physik.hu-berlin.de', 'Germany|Germany', 18, 'Computer Simulation|Databases, Factual|Gene Regulatory Networks|Humans|Kinetics|Models, Biological|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btr697', '22199382', 'The understanding of the molecular sources for diseases like cancer can be significantly improved by computational models. Recently, Boolean networks have become very popular for modeling signaling and regulatory networks. However, such models rely on a set of Boolean functions that are in general not known. Unfortunately, while detailed information on the molecular interactions becomes available in large scale through electronic databases, the information on the Boolean functions does not become available simultaneously and has to be included manually into the models, if at all known.'),
(76655, 2012, 'bio', 'Fast large-scale clustering of protein structures using Gauss integrals', 'Harder, Tim|Borg, Mikael|Boomsma, Wouter|Røgen, Peter|Hamelryck, Thomas', 'The Bioinformatics Section, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|The Bioinformatics Section, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|The Bioinformatics Section, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|The Bioinformatics Section, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|The Bioinformatics Section, Department of Biology, University of Copenhagen, Copenhagen, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark', 21, 'Adenylate Kinase|Candida|Cluster Analysis|Computational Biology|Escherichia coli|Fungal Proteins|Molecular Dynamics Simulation|Proteins', 'Journal Article', '10.1093/bioinformatics/btr692', '22199383', 'Clustering protein structures is an important task in structural bioinformatics. De novo structure prediction, for example, often involves a clustering step for finding the best prediction. Other applications include assigning proteins to fold families and analyzing molecular dynamics trajectories.'),
(76656, 2012, 'bio', 'MeQA: a pipeline for MeDIP-seq data quality assessment and analysis', 'Huang, J|Renault, V|Sengenès, J|Touleimat, N|Michel, S|Lathrop, M|Tost, J', 'School of life science, Tongji University, 200092 Shanghai, China. jhuang@cephb.fr|School of life science, Tongji University, 200092 Shanghai, China. jhuang@cephb.fr|School of life science, Tongji University, 200092 Shanghai, China. jhuang@cephb.fr|School of life science, Tongji University, 200092 Shanghai, China. jhuang@cephb.fr|School of life science, Tongji University, 200092 Shanghai, China. jhuang@cephb.fr|School of life science, Tongji University, 200092 Shanghai, China. jhuang@cephb.fr|School of life science, Tongji University, 200092 Shanghai, China. jhuang@cephb.fr', 'China|China|China|China|China|China|China', 20, 'DNA Methylation|Humans|Immunoprecipitation|Research Design|Software', 'Journal Article', '10.1093/bioinformatics/btr699', '22199384', 'We present a pipeline for the pre-processing, quality assessment, read distribution and methylation estimation for methylated DNA immunoprecipitation (MeDIP)-sequence datasets. This is the first MeDIP-seq-specific analytic pipeline that starts at the output of the sequencers. This pipeline will reduce the data analysis load on staff and allows the easy and straightforward analysis of sequencing data for DNA methylation. The pipeline integrates customized scripting and several existing tools, which can deal with both paired and single end data.'),
(76657, 2012, 'bio', 'LaTcOm: a web server for visualizing rare codon clusters in coding sequences', 'Theodosiou, Athina|Promponas, Vasilis J', 'Bioinformatics Research Laboratory, Department of Biological Sciences, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus.|Bioinformatics Research Laboratory, Department of Biological Sciences, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus.', 'Cyprus|Cyprus', 7, 'Algorithms|Cluster Analysis|Codon|Escherichia coli|Internet|RNA, Transfer|Software', 'Journal Article', '10.1093/bioinformatics/btr706', '22199385', 'We present LaTcOm, a new web tool, which offers several alternative methods for rare codon cluster (RCC) identification from a single and simple graphical user interface. In the current version, three RCC detection schemes are implemented: the recently described %MinMax algorithm and a simplified sliding window approach, along with a novel modification of a linear-time algorithm for the detection of maximally scoring subsequences tailored to the RCC detection problem. Among a number of user tunable parameters, several codon-based scales relevant for RCC detection are available, including tRNA abundance values from Escherichia coli and several codon usage tables from a selection of genomes. Furthermore, useful scale transformations may be performed upon user request (e.g. linear, sigmoid). Users may choose to visualize RCC positions within the submitted sequences either with graphical representations or in textual form for further processing.'),
(76658, 2012, 'bio', 'Optimal structural inference of signaling pathways from unordered and overlapping gene sets', 'Acharya, Lipi R|Judeh, Thair|Wang, Guangdi|Zhu, Dongxiao', 'Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA.|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA.|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA.|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA.', 'United States|United States|United States|United States', 8, 'Algorithms|Bayes Theorem|Breast Neoplasms|Cell Communication|Computational Biology|Escherichia coli|Female|Humans|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btr696', '22199386', 'A plethora of bioinformatics analysis has led to the discovery of numerous gene sets, which can be interpreted as discrete measurements emitted from latent signaling pathways. Their potential to infer signaling pathway structures, however, has not been sufficiently exploited. Existing methods accommodating discrete data do not explicitly consider signal cascading mechanisms that characterize a signaling pathway. Novel computational methods are thus needed to fully utilize gene sets and broaden the scope from focusing only on pairwise interactions to the more general cascading events in the inference of signaling pathway structures.'),
(76659, 2012, 'bio', 'CLARE: Cracking the LAnguage of Regulatory Elements', 'Taher, Leila|Narlikar, Leelavati|Ovcharenko, Ivan', 'Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MA 20894, USA. taherl@ncbi.nlm.nih.gov|Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MA 20894, USA. taherl@ncbi.nlm.nih.gov|Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MA 20894, USA. taherl@ncbi.nlm.nih.gov', 'United States|United States|United States', 10, 'Animals|Enhancer Elements, Genetic|Gene Expression Regulation|Genomics|Humans|Mice|Organ Specificity|Prosencephalon|Regulatory Sequences, Nucleic Acid|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr704', '22199387', 'CLARE is a computational method designed to reveal sequence encryption of tissue-specific regulatory elements. Starting with a set of regulatory elements known to be active in a particular tissue/process, it learns the sequence code of the input set and builds a predictive model from features specific to those elements. The resulting model can then be applied to user-supplied genomic regions to identify novel candidate regulatory elements. CLAREs model also provides a detailed analysis of transcription factors that most likely bind to the elements, making it an invaluable tool for understanding mechanisms of tissue-specific gene regulation.'),
(76660, 2012, 'bio', 'Artemis: an integrated platform for visualization and analysis of high-throughput sequence-based experimental data', 'Carver, Tim|Harris, Simon R|Berriman, Matthew|Parkhill, Julian|McQuillan, Jacqueline A', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. artemis@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. artemis@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. artemis@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. artemis@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. artemis@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 447, 'Genome|High-Throughput Nucleotide Sequencing|Molecular Sequence Annotation|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btr703', '22199388', 'High-throughput sequencing (HTS) technologies have made low-cost sequencing of large numbers of samples commonplace. An explosion in the type, not just number, of sequencing experiments has also taken place including genome re-sequencing, population-scale variation detection, whole transcriptome sequencing and genome-wide analysis of protein-bound nucleic acids.'),
(76661, 2012, 'bio', 'PathVisio-Validator: a rule-based validation plugin for graphical pathway notations', 'Chandan, Kumar|van Iersel, Martijn P|Aladjem, Mirit I|Kohn, Kurt W|Luna, Augustin', 'Keshav Memorial Institute of Technology, Hyderabad, Andhra Pradesh, India. chandankmit@gmail.com|Keshav Memorial Institute of Technology, Hyderabad, Andhra Pradesh, India. chandankmit@gmail.com|Keshav Memorial Institute of Technology, Hyderabad, Andhra Pradesh, India. chandankmit@gmail.com|Keshav Memorial Institute of Technology, Hyderabad, Andhra Pradesh, India. chandankmit@gmail.com|Keshav Memorial Institute of Technology, Hyderabad, Andhra Pradesh, India. chandankmit@gmail.com', 'India|India|India|India|India', 5, 'Computer Graphics|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btr694', '22199389', 'The PathVisio-Validator plugin aims to simplify the task of producing biological pathway diagrams that follow graphical standardized notations, such as Molecular Interaction Maps or the Systems Biology Graphical Notation. This plugin assists in the creation of pathway diagrams by ensuring correct usage of a notation, and thereby reducing ambiguity when diagrams are shared among biologists. Rulesets, needed in the validation process, can be generated for any graphical notation that a developer desires, using either Schematron or Groovy. The plugin also provides support for filtering validation results, validating on a subset of rules, and distinguishing errors and warnings.'),
(76662, 2012, 'bio', 'PIE the search: searching PubMed literature for protein interaction information', 'Kim, Sun|Kwon, Dongseop|Shin, Soo-Yong|Wilbur, W John', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. sun.kim@nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. sun.kim@nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. sun.kim@nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. sun.kim@nih.gov', 'United States|United States|United States|United States', 25, 'Artificial Intelligence|Protein Interaction Mapping|Proteins|PubMed', 'Journal Article', '10.1093/bioinformatics/btr702', '22199390', 'Finding protein-protein interaction (PPI) information from literature is challenging but an important issue. However, keyword search in PubMed(®) is often time consuming because it requires a series of actions that refine keywords and browse search results until it reaches a goal. Due to the rapid growth of biomedical literature, it has become more difficult for biologists and curators to locate PPI information quickly. Therefore, a tool for prioritizing PPI informative articles can be a useful assistant for finding this PPI-relevant information.'),
(76663, 2012, 'bio', 'Measuring the distance between multiple sequence alignments', 'Blackburne, Benjamin P|Whelan, Simon', 'Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester M13 9PT, UK.|Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester M13 9PT, UK.', 'United Kingdom|United Kingdom', 33, 'Computers|INDEL Mutation|Phylogeny|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btr701', '22199391', 'Multiple sequence alignment (MSA) is a core method in bioinformatics. The accuracy of such alignments may influence the success of downstream analyses such as phylogenetic inference, protein structure prediction, and functional prediction. The importance of MSA has lead to the proliferation of MSA methods, with different objective functions and heuristics to search for the optimal MSA. Different methods of inferring MSAs produce different results in all but the most trivial cases. By measuring the differences between inferred alignments, we may be able to develop an understanding of how these differences (i) relate to the objective functions and heuristics used in MSA methods, and (ii) affect downstream analyses.'),
(76664, 2012, 'bio', 'ART: a next-generation sequencing read simulator', 'Huang, Weichun|Li, Leping|Myers, Jason R|Marth, Gabor T', 'Biostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA. weichun.huang@nih.gov|Biostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA. weichun.huang@nih.gov|Biostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA. weichun.huang@nih.gov|Biostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA. weichun.huang@nih.gov', 'United States|United States|United States|United States', 515, 'Chromosomes, Human, Pair 17|Genetic Variation|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btr708', '22199392', 'ART is a set of simulation tools that generate synthetic next-generation sequencing reads. This functionality is essential for testing and benchmarking tools for next-generation sequencing data analysis including read alignment, de novo assembly and genetic variation discovery. ART generates simulated sequencing reads by emulating the sequencing process with built-in, technology-specific read error models and base quality value profiles parameterized empirically in large sequencing datasets. We currently support all three major commercial next-generation sequencing platforms: Roches 454, Illuminas Solexa and Applied Biosystems SOLiD. ART also allows the flexibility to use customized read error model parameters and quality profiles.'),
(76665, 2012, 'bio', 'Read count approach for DNA copy number variants detection', 'Magi, Alberto|Tattini, Lorenzo|Pippucci, Tommaso|Torricelli, Francesca|Benelli, Matteo', 'Faculty of Medicine, University of Florence, Florence 50019, Italy. albertomagi@gmail.com|Faculty of Medicine, University of Florence, Florence 50019, Italy. albertomagi@gmail.com|Faculty of Medicine, University of Florence, Florence 50019, Italy. albertomagi@gmail.com|Faculty of Medicine, University of Florence, Florence 50019, Italy. albertomagi@gmail.com|Faculty of Medicine, University of Florence, Florence 50019, Italy. albertomagi@gmail.com', 'Italy|Italy|Italy|Italy|Italy', 56, 'Algorithms|DNA Copy Number Variations|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btr707', '22199393', 'The advent of high-throughput sequencing technologies is revolutionizing our ability in discovering and genotyping DNA copy number variants (CNVs). Read count-based approaches are able to detect CNV regions with an unprecedented resolution. Although this computational strategy has been recently introduced in literature, much work has been already done for the preparation, normalization and analysis of this kind of data.'),
(76666, 2012, 'bio', 'Modeling community-wide molecular networks of multicellular systems', 'Komurov, Kakajan', 'Divisions of Experimental Hematology and Cancer Biology, Human Genetics and Biomedical Informatics, Cincinnati Childrens Hospital Medical Center, Cincinnati, OH, USA. kakajan.komurov@cchmc.org', 'United States', 12, 'Animals|Cell Communication|Genome-Wide Association Study|Humans|Lung Neoplasms|Mice|Models, Biological|Neoplasm Transplantation|Transplantation, Heterologous|Tumor Microenvironment', 'Journal Article', '10.1093/bioinformatics/btr718', '22210865', 'Multicellular systems, such as tissues, are composed of different cell types that form a heterogeneous community. Behavior of these systems is determined by complex regulatory networks within (intracellular networks) and between (intercellular networks) cells. Increasingly more studies are applying genome-wide experimental approaches to delineate the contributions of individual cell types (e.g. stromal, epithelial, vascular cells) to collective behavior of heterogeneous cell communities (e.g. tumors). Although many computational methods have been developed for analyses of intracellular networks based on genome-scale data, these efforts have not been extended toward analyzing genomic data from heterogeneous cell communities.'),
(76667, 2012, 'bio', 'influx_s: increasing numerical stability and precision for metabolic flux analysis in isotope labelling experiments', 'Sokol, Serguei|Millard, Pierre|Portais, Jean-Charles', 'INSA, UPS, INP, LISBP, Université de Toulouse, 135 Avenue de Rangueil, F-31077 Toulouse, France.|INSA, UPS, INP, LISBP, Université de Toulouse, 135 Avenue de Rangueil, F-31077 Toulouse, France.|INSA, UPS, INP, LISBP, Université de Toulouse, 135 Avenue de Rangueil, F-31077 Toulouse, France.', 'France|France|France', 37, 'Algorithms|Carbon Radioisotopes|Escherichia coli|Isotope Labeling|Metabolic Networks and Pathways|Models, Biological|Software', 'Journal Article', '10.1093/bioinformatics/btr716', '22210866', 'The problem of stationary metabolic flux analysis based on isotope labelling experiments first appeared in the early 1950s and was basically solved in early 2000s. Several algorithms and software packages are available for this problem. However, the generic stochastic algorithms (simulated annealing or evolution algorithms) currently used in these software require a lot of time to achieve acceptable precision. For deterministic algorithms, a common drawback is the lack of convergence stability for ill-conditioned systems or when started from a random point.'),
(76668, 2012, 'bio', 'CytoSEED: a Cytoscape plugin for viewing, manipulating and analyzing metabolic models created by the Model SEED', 'DeJongh, Matthew|Bockstege, Benjamin|Frybarger, Paul|Hazekamp, Nicholas|Kammeraad, Joshua|McGeehan, Travis', 'Computer Science Department, Hope College, Holland, MI 49423, USA. dejongh@hope.edu|Computer Science Department, Hope College, Holland, MI 49423, USA. dejongh@hope.edu|Computer Science Department, Hope College, Holland, MI 49423, USA. dejongh@hope.edu|Computer Science Department, Hope College, Holland, MI 49423, USA. dejongh@hope.edu|Computer Science Department, Hope College, Holland, MI 49423, USA. dejongh@hope.edu|Computer Science Department, Hope College, Holland, MI 49423, USA. dejongh@hope.edu', 'United States|United States|United States|United States|United States|United States', 11, 'Metabolic Networks and Pathways|Models, Biological|Mycoplasma|Prokaryotic Cells|Software', 'Journal Article', '10.1093/bioinformatics/btr719', '22210867', 'CytoSEED is a Cytoscape plugin for viewing, manipulating and analyzing metabolic models created using the Model SEED. The CytoSEED plugin enables users of the Model SEED to create informative visualizations of the reaction networks generated for their organisms of interest. These visualizations are useful for understanding organism-specific biochemistry and for highlighting the results of flux variability analysis experiments.'),
(76669, 2012, 'bio', 'VarSifter: visualizing and analyzing exome-scale sequence variation data on a desktop computer', 'Teer, Jamie K|Green, Eric D|Mullikin, James C|Biesecker, Leslie G', 'National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.|National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.|National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.|National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.', 'United States|United States|United States|United States', 104, 'Computational Biology|Exome|High-Throughput Nucleotide Sequencing|Software', 'Journal Article', '10.1093/bioinformatics/btr711', '22210868', 'VarSifter is a graphical software tool for desktop computers that allows investigators of varying computational skills to easily and quickly sort, filter, and sift through sequence variation data. A variety of filters and a custom query framework allow filtering based on any combination of sample and annotation information. By simplifying visualization and analyses of exome-scale sequence variation data, this program will help bring the power and promise of massively-parallel DNA sequencing to a broader group of researchers.'),
(76670, 2012, 'bio', 'Small-molecule inhibitor starting points learned from protein-protein interaction inhibitor structure', 'Koes, David Ryan|Camacho, Carlos J', 'Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA. dkoes@pitt.edu|Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA. dkoes@pitt.edu', 'United States|United States', 0, 'Databases, Protein|Humans|Ligands|Protein Interaction Maps|Proteins|Small Molecule Libraries|Software|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btr717', '22210869', 'Protein-protein interactions (PPIs) are a promising, but challenging target for pharmaceutical intervention. One approach for addressing these difficult targets is the rational design of small-molecule inhibitors that mimic the chemical and physical properties of small clusters of key residues at the protein-protein interface. The identification of appropriate clusters of interface residues provides starting points for inhibitor design and supports an overall assessment of the susceptibility of PPIs to small-molecule inhibition.'),
(76671, 2012, 'bio', 'Approximating the set of local minima in partial RNA folding landscapes', 'Sahoo, S|Albrecht, A A', 'Centre for Cancer Research and Cell Biology, Queens University Belfast, Belfast BT9 7BL, UK.|Centre for Cancer Research and Cell Biology, Queens University Belfast, Belfast BT9 7BL, UK.', 'United Kingdom|United Kingdom', 0, '3 Untranslated Regions|Algorithms|Humans|Nucleic Acid Conformation|RNA|RNA Folding|Riboswitch', 'Journal Article', '10.1093/bioinformatics/btr715', '22210870', 'We study a stochastic method for approximating the set of local minima in partial RNA folding landscapes associated with a bounded-distance neighbourhood of folding conformations. The conformations are limited to RNA secondary structures without pseudoknots. The method aims at exploring partial energy landscapes pL induced by folding simulations and their underlying neighbourhood relations. It combines an approximation of the number of local optima devised by Garnier and Kallel (2002) with a run-time estimation for identifying sets of local optima established by Reeves and Eremeev (2004).'),
(76672, 2012, 'bio', 'SNPdbe: constructing an nsSNP functional impacts database', 'Schaefer, Christian|Meier, Alice|Rost, Burkhard|Bromberg, Yana', 'Technische Universitaet Muenchen, Bioinformatics - I12, Informatik, Boltzmannstrasse 3, Muenchen, Germany. schaefer@rostlab.org|Technische Universitaet Muenchen, Bioinformatics - I12, Informatik, Boltzmannstrasse 3, Muenchen, Germany. schaefer@rostlab.org|Technische Universitaet Muenchen, Bioinformatics - I12, Informatik, Boltzmannstrasse 3, Muenchen, Germany. schaefer@rostlab.org|Technische Universitaet Muenchen, Bioinformatics - I12, Informatik, Boltzmannstrasse 3, Muenchen, Germany. schaefer@rostlab.org', 'Germany|Germany|Germany|Germany', 34, 'Algorithms|Amino Acid Substitution|Databases, Genetic|Humans|Internet|Polymorphism, Single Nucleotide|Proteins', 'Journal Article', '10.1093/bioinformatics/btr705', '22210871', 'Many existing databases annotate experimentally characterized single nucleotide polymorphisms (SNPs). Each non-synonymous SNP (nsSNP) changes one amino acid in the gene product (single amino acid substitution,SAAS). This change can either affect protein function or be neutral in that respect. Most polymorphisms lack experimental annotation of their functional impact. Here, we introduce SNPdbe-SNP database of effects, with predictions of computationally annotated functional impacts of SNPs. Database entries represent nsSNPs in dbSNP and 1000 Genomes collection, as well as variants from UniProt and PMD. SAASs come from >2600 organisms, human being the most prevalent. The impact of each SAAS on protein function is predicted using the SNAP and SIFT algorithms and augmented with experimentally derived function/structure information and disease associations from PMD, OMIM and UniProt. SNPdbe is consistently updated and easily augmented with new sources of information. The database is available as an MySQL dump and via a web front end that allows searches with any combination of organism names, sequences and mutation IDs.'),
(76673, 2012, 'bio', 'Evaluating bacterial gene-finding HMM structures as probabilistic logic programs', 'Mørk, Søren|Holmes, Ian', 'Department of Science, Systems and Models, Roskilde University, 4000 Roskilde, Denmark. soer@ruc.dk|Department of Science, Systems and Models, Roskilde University, 4000 Roskilde, Denmark. soer@ruc.dk', 'Denmark|Denmark', 0, 'Algorithms|Artificial Intelligence|Bacillus subtilis|Escherichia coli|Genes, Bacterial|Markov Chains|Models, Genetic|Models, Statistical|Programming Languages|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btr698', '22215819', 'Probabilistic logic programming offers a powerful way to describe and evaluate structured statistical models. To investigate the practicality of probabilistic logic programming for structure learning in bioinformatics, we undertook a simplified bacterial gene-finding benchmark in PRISM, a probabilistic dialect of Prolog.'),
(76674, 2012, 'bio', 'PASSion: a pattern growth algorithm-based pipeline for splice junction detection in paired-end RNA-Seq data', 'Zhang, Yanju|Lameijer, Eric-Wubbo|	 Hoen, Peter A C|Ning, Zemin|Slagboom, P Eline|Ye, Kai', 'Department of Molecular Epidemiology, Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands. y.zhang@lumc.nl|Department of Molecular Epidemiology, Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands. y.zhang@lumc.nl|Department of Molecular Epidemiology, Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands. y.zhang@lumc.nl|Department of Molecular Epidemiology, Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands. y.zhang@lumc.nl|Department of Molecular Epidemiology, Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands. y.zhang@lumc.nl|Department of Molecular Epidemiology, Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands. y.zhang@lumc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Chromosomes, Human, Pair 17|Exons|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|RNA|RNA Splice Sites|RNA Splicing|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btr712', '22219203', 'RNA-seq is a powerful technology for the study of transcriptome profiles that uses deep-sequencing technologies. Moreover, it may be used for cellular phenotyping and help establishing the etiology of diseases characterized by abnormal splicing patterns. In RNA-Seq, the exact nature of splicing events is buried in the reads that span exon-exon boundaries. The accurate and efficient mapping of these reads to the reference genome is a major challenge.'),
(76675, 2012, 'bio', 'NetSeed: a network-based reverse-ecology tool for calculating the metabolic interface of an organism with its environment', 'Carr, Rogan|Borenstein, Elhanan', 'Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.', 'United States|United States', 23, 'Algorithms|Bacteria|Ecology|Environment|Internet|Metabolic Networks and Pathways|Microbial Interactions|Software', 'Journal Article', '10.1093/bioinformatics/btr721', '22219204', 'NetSeed is a web tool and Perl module for analyzing the topology of metabolic networks and calculating the set of exogenously acquired compounds. NetSeed is based on the seed detection algorithm, developed and validated in previous studies.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76676, 2012, 'bio', 'Automatic selection of reference taxa for protein-protein interaction prediction with phylogenetic profiling', 'Simonsen, Martin|Maetschke, Stefan R|Ragan, Mark A', 'Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.|Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.', 'Denmark|Denmark|Denmark', 9, 'Archaea|Artificial Intelligence|Bacteria|Eukaryota|Phylogeny|Protein Interaction Maps|Proteins', 'Journal Article', '10.1093/bioinformatics/btr720', '22219205', 'Phylogenetic profiling methods can achieve good accuracy in predicting protein-protein interactions, especially in prokaryotes. Recent studies have shown that the choice of reference taxa (RT) is critical for accurate prediction, but with more than 2500 fully sequenced taxa publicly available, identifying the most-informative RT is becoming increasingly difficult. Previous studies on the selection of RT have provided guidelines for manual taxon selection, and for eliminating closely related taxa. However, no general strategy for automatic selection of RT is currently available.'),
(76677, 2012, 'bio', 'Quantifying the white blood cell transcriptome as an accessible window to the multiorgan transcriptome', 'Kohane, Isaac S|Valtchinov, Vladimir I', 'National Center for Biomedical Computing Informatics for Integrating Biology and the Bedside (i2b2), Boston, MA 02115, USA.|National Center for Biomedical Computing Informatics for Integrating Biology and the Bedside (i2b2), Boston, MA 02115, USA.', 'United States|United States', 0, 'Databases, Genetic|Gene Expression Profiling|Gene Regulatory Networks|Humans|Leukocytes|Neoplasms|Transcription Factors|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btr713', '22219206', 'We investigate and quantify the generalizability of the white blood cell (WBC) transcriptome to the general, multiorgan transcriptome. We use data from the NCBIs Gene Expression Omnibus (GEO) public repository to define two datasets for comparison, WBC and OO (Other Organ) sets.'),
(76678, 2012, 'bio', 'A method to infer positive selection from marker dynamics in an asexual population', 'Illingworth, Christopher J R|Mustonen, Ville', 'Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK.|Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK.', 'United Kingdom|United Kingdom', 15, 'Biological Evolution|Escherichia coli|Likelihood Functions|Models, Genetic|Mutation', 'Journal Article', '10.1093/bioinformatics/btr722', '22223745', 'The observation of positive selection acting on a mutant indicates that the corresponding mutation has some form of functional relevance. Determining the fitness effects of mutations thus has relevance to many interesting biological questions. One means of identifying beneficial mutations in an asexual population is to observe changes in the frequency of marked subsets of the population. We here describe a method to estimate the establishment times and fitnesses of beneficial mutations from neutral marker frequency data.'),
(76679, 2012, 'bio', 'CHROMATRA: a Galaxy tool for visualizing genome-wide chromatin signatures', 'Hentrich, Thomas|Schulze, Julia M|Emberly, Eldon|Kobor, Michael S', 'Department of Computing Science, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.|Department of Computing Science, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.|Department of Computing Science, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.|Department of Computing Science, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.', 'Canada|Canada|Canada|Canada', 11, 'Animals|Chromatin|Chromatin Immunoprecipitation|DNA-Binding Proteins|Genome|Genomics|Humans|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/bts007', '22238257', 'CHROMATRA (CHROmatin Mapping Across TRAnscripts) is a visualization tool available as plug-in for the Galaxy platform. It allows detailed yet concise presentations of data derived from ChIP-chip or ChIP-seq experiments by visualizing enrichment scores across genes or other genomic features while accounting for their length and additional characteristics such as gene expression. It integrates into typical analysis workflows and enables rapid graphical assessment and comparison of genome-wide data at a glance.'),
(76680, 2012, 'bio', 'IMID: integrated molecular interaction database', 'Balaji, Sentil|Mcclendon, Charles|Chowdhary, Rajesh|Liu, Jun S|Zhang, Jinfeng', 'Department of Statistics, Florida State University, Tallahassee, FL 32306, USA.|Department of Statistics, Florida State University, Tallahassee, FL 32306, USA.|Department of Statistics, Florida State University, Tallahassee, FL 32306, USA.|Department of Statistics, Florida State University, Tallahassee, FL 32306, USA.|Department of Statistics, Florida State University, Tallahassee, FL 32306, USA.', 'United States|United States|United States|United States|United States', 6, 'Databases, Protein|Humans|Internet|Protein Binding|Protein Interaction Maps|Proteins|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts010', '22238258', 'Molecular interaction information, such as protein-protein interactions and protein-small molecule interactions, is indispensable for understanding the mechanism of biological processes and discovering treatments for diseases. Many databases have been built by manual annotation of literature to organize such information into structured form. However, most databases focus on only one type of interactions, which are often not well annotated and integrated with related functional information.'),
(76681, 2012, 'bio', 'RIBER/DIBER: a software suite for crystal content analysis in the studies of protein-nucleic acid complexes', 'Chojnowski, Grzegorz|Bujnicki, Janusz M|Bochtler, Matthias', 'International Institute of Molecular and Cell Biology, Warsaw, Poland. gchojnowski@genesilico.pl|International Institute of Molecular and Cell Biology, Warsaw, Poland. gchojnowski@genesilico.pl|International Institute of Molecular and Cell Biology, Warsaw, Poland. gchojnowski@genesilico.pl', 'Poland|Poland|Poland', 4, 'Artificial Intelligence|Crystallography, X-Ray|DNA|DNA-Binding Proteins|Databases, Protein|RNA|RNA-Binding Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts003', '22238259', 'Co-crystallization experiments of proteins with nucleic acids do not guarantee that both components are present in the crystal. We have previously developed DIBER to predict crystal content when protein and DNA are present in the crystallization mix. Here, we present RIBER, which should be used when protein and RNA are in the crystallization drop. The combined RIBER/DIBER suite builds on machine learning techniques to make reliable, quantitative predictions of crystal content for non-expert users and high-throughput crystallography.'),
(76682, 2012, 'bio', 'PHACTS, a computational approach to classifying the lifestyle of phages', 'McNair, Katelyn|Bailey, Barbara A|Edwards, Robert A', 'Computational Science Research Center, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA. katelyn@rohan.sdsu.edu|Computational Science Research Center, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA. katelyn@rohan.sdsu.edu|Computational Science Research Center, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA. katelyn@rohan.sdsu.edu', 'United States|United States|United States', 80, 'Algorithms|Bacteria|Bacteriophages|Genomics|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/bts014', '22238260', 'Bacteriophages have two distinct lifestyles: virulent and temperate. The virulent lifestyle has many implications for phage therapy, genomics and microbiology. Determining which lifestyle a newly sequenced phage falls into is currently determined using standard culturing techniques. Such laboratory work is not only costly and time consuming, but also cannot be used on phage genomes constructed from environmental sequencing. Therefore, a computational method that utilizes the sequence data of phage genomes is needed.'),
(76683, 2012, 'bio', 'SSuMMo: rapid analysis, comparison and visualization of microbial communities', 'Leach, Alex L B|Chong, James P J|Redeker, Kelly R', 'Department of Biology, University of York, York YO10 5DD, UK. albl500@york.ac.uk|Department of Biology, University of York, York YO10 5DD, UK. albl500@york.ac.uk|Department of Biology, University of York, York YO10 5DD, UK. albl500@york.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 5, 'Archaea|Bacteria|Markov Chains|Metagenomics|Ribotyping|Software', 'Journal Article', '10.1093/bioinformatics/bts017', '22238261', 'Next-generation sequencing methods are generating increasingly massive datasets, yet still do not fully capture genetic diversity in the richest environments. To understand such complicated and elusive systems, effective tools are needed to assist with delineating the differences found in and between community datasets.'),
(76684, 2012, 'bio', 'The evolution of nitrogen fixation in cyanobacteria', 'Latysheva, Natasha|Junker, Vivien L|Palmer, William J|Codd, Geoffrey A|Barker, Daniel', 'Centre for Evolution, Genes and Genomics, School of Biology, University of St Andrews, St Andrews, Fife, KY16 9TH, UK.|Centre for Evolution, Genes and Genomics, School of Biology, University of St Andrews, St Andrews, Fife, KY16 9TH, UK.|Centre for Evolution, Genes and Genomics, School of Biology, University of St Andrews, St Andrews, Fife, KY16 9TH, UK.|Centre for Evolution, Genes and Genomics, School of Biology, University of St Andrews, St Andrews, Fife, KY16 9TH, UK.|Centre for Evolution, Genes and Genomics, School of Biology, University of St Andrews, St Andrews, Fife, KY16 9TH, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 48, 'Bacterial Proteins|Biological Evolution|Cyanobacteria|Gene Transfer, Horizontal|Nitrogen Fixation|Nitrogenase|Phylogeny', 'Journal Article', '10.1093/bioinformatics/bts008', '22238262', 'Fixed nitrogen is an essential requirement for the biosynthesis of cellular nitrogenous compounds. Some cyanobacteria can fix nitrogen, contributing significantly to the nitrogen cycle, agriculture and biogeochemical history of Earth. The rate and position on the species phylogeny of gains and losses of this ability, as well as of the underlying nif genes, are controversial.'),
(76685, 2012, 'bio', 'MetExtract: a new software tool for the automated comprehensive extraction of metabolite-derived LC/MS signals in metabolomics research', 'Bueschl, Christoph|Kluger, Bernhard|Berthiller, Franz|Lirk, Gerald|Winkler, Stephan|Krska, Rudolf|Schuhmacher, Rainer', 'Center for Analytical Chemistry, Department for Agrobiotechnology (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, Konrad Lorenz Strasse 20, 3430 Tulln, Austria.|Center for Analytical Chemistry, Department for Agrobiotechnology (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, Konrad Lorenz Strasse 20, 3430 Tulln, Austria.|Center for Analytical Chemistry, Department for Agrobiotechnology (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, Konrad Lorenz Strasse 20, 3430 Tulln, Austria.|Center for Analytical Chemistry, Department for Agrobiotechnology (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, Konrad Lorenz Strasse 20, 3430 Tulln, Austria.|Center for Analytical Chemistry, Department for Agrobiotechnology (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, Konrad Lorenz Strasse 20, 3430 Tulln, Austria.|Center for Analytical Chemistry, Department for Agrobiotechnology (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, Konrad Lorenz Strasse 20, 3430 Tulln, Austria.|Center for Analytical Chemistry, Department for Agrobiotechnology (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, Konrad Lorenz Strasse 20, 3430 Tulln, Austria.', 'Austria|Austria|Austria|Austria|Austria|Austria|Austria', 54, 'Algorithms|Carbon Radioisotopes|Chromatography, Liquid|Fusarium|Mass Spectrometry|Metabolomics|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/bts012', '22238263', 'Liquid chromatography-mass spectrometry (LC/MS) is a key technique in metabolomics. Since the efficient assignment of MS signals to true biological metabolites becomes feasible in combination with in vivo stable isotopic labelling, our aim was to provide a new software tool for this purpose.'),
(76686, 2012, 'bio', 'Interactome-transcriptome integration for predicting distant metastasis in breast cancer', 'Garcia, Maxime|Millat-Carus, Raphaelle|Bertucci, François|Finetti, Pascal|Birnbaum, Daniel|Bidaut, Ghislain', 'Aix-Marseille Univ, F-13284 Marseille, France. maxime.garcia@inserm.fr|Aix-Marseille Univ, F-13284 Marseille, France. maxime.garcia@inserm.fr|Aix-Marseille Univ, F-13284 Marseille, France. maxime.garcia@inserm.fr|Aix-Marseille Univ, F-13284 Marseille, France. maxime.garcia@inserm.fr|Aix-Marseille Univ, F-13284 Marseille, France. maxime.garcia@inserm.fr|Aix-Marseille Univ, F-13284 Marseille, France. maxime.garcia@inserm.fr', 'France|France|France|France|France|France', 15, 'Algorithms|Breast Neoplasms|Female|Gene Expression Profiling|Humans|Neoplasm Metastasis|Protein Interaction Maps|Receptors, Estrogen|Transcriptome', 'Journal Article', '10.1093/bioinformatics/bts025', '22238264', 'High-throughput gene expression profiling yields genomic signatures that allow the prediction of clinical conditions including patient outcome. However, these signatures have limitations, such as dependency on the training set, and worse, lack of generalization.'),
(76687, 2012, 'bio', 'Estimating abundances of retroviral insertion sites from DNA fragment length data', 'Berry, Charles C|Gillet, Nicolas A|Melamed, Anat|Gormley, Niall|Bangham, Charles R M|Bushman, Frederic D', 'Department of Family and Preventive Medicine, University of California, La Jolla, CA, USA. ccberry@ucsd.edu|Department of Family and Preventive Medicine, University of California, La Jolla, CA, USA. ccberry@ucsd.edu|Department of Family and Preventive Medicine, University of California, La Jolla, CA, USA. ccberry@ucsd.edu|Department of Family and Preventive Medicine, University of California, La Jolla, CA, USA. ccberry@ucsd.edu|Department of Family and Preventive Medicine, University of California, La Jolla, CA, USA. ccberry@ucsd.edu|Department of Family and Preventive Medicine, University of California, La Jolla, CA, USA. ccberry@ucsd.edu', 'United States|United States|United States|United States|United States|United States', 60, 'Algorithms|HTLV-I Infections|Human T-lymphotropic virus 1|Humans|Virus Integration', 'Journal Article', '10.1093/bioinformatics/bts004', '22238265', 'The relative abundance of retroviral insertions in a host genome is important in understanding the persistence and pathogenesis of both natural retroviral infections and retroviral gene therapy vectors. It could be estimated from a sample of cells if only the host genomic sites of retroviral insertions could be directly counted. When host genomic DNA is randomly broken via sonication and then amplified, amplicons of varying lengths are produced. The number of unique lengths of amplicons of an insertion site tends to increase according to its abundance, providing a basis for estimating relative abundance. However, as abundance increases amplicons of the same length arise by chance leading to a non-linear relation between the number of unique lengths and relative abundance. The difficulty in calibrating this relation is compounded by sample-specific variations in the relative frequencies of clones of each length.'),
(76688, 2012, 'bio', 'Detecting genomic indel variants with exact breakpoints in single- and paired-end sequencing data using SplazerS', 'Emde, Anne-Katrin|Schulz, Marcel H|Weese, David|Sun, Ruping|Vingron, Martin|Kalscheuer, Vera M|Haas, Stefan A|Reinert, Knut', 'Department of Computer Science, Freie Universität Berlin, Takustrasse 9, Max-Planck-Institute for Molecular Genetics, Berlin, Germany. emde@inf.fu-berlin.de|Department of Computer Science, Freie Universität Berlin, Takustrasse 9, Max-Planck-Institute for Molecular Genetics, Berlin, Germany. emde@inf.fu-berlin.de|Department of Computer Science, Freie Universität Berlin, Takustrasse 9, Max-Planck-Institute for Molecular Genetics, Berlin, Germany. emde@inf.fu-berlin.de|Department of Computer Science, Freie Universität Berlin, Takustrasse 9, Max-Planck-Institute for Molecular Genetics, Berlin, Germany. emde@inf.fu-berlin.de|Department of Computer Science, Freie Universität Berlin, Takustrasse 9, Max-Planck-Institute for Molecular Genetics, Berlin, Germany. emde@inf.fu-berlin.de|Department of Computer Science, Freie Universität Berlin, Takustrasse 9, Max-Planck-Institute for Molecular Genetics, Berlin, Germany. emde@inf.fu-berlin.de|Department of Computer Science, Freie Universität Berlin, Takustrasse 9, Max-Planck-Institute for Molecular Genetics, Berlin, Germany. emde@inf.fu-berlin.de|Department of Computer Science, Freie Universität Berlin, Takustrasse 9, Max-Planck-Institute for Molecular Genetics, Berlin, Germany. emde@inf.fu-berlin.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 47, 'Algorithms|Genomics|Humans|INDEL Mutation|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts019', '22238266', 'The reliable detection of genomic variation in resequencing data is still a major challenge, especially for variants larger than a few base pairs. Sequencing reads crossing boundaries of structural variation carry the potential for their identification, but are difficult to map.'),
(76689, 2012, 'bio', 'De novo motif discovery facilitates identification of interactions between transcription factors in Saccharomyces cerevisiae', 'Chen, Mei-Ju May|Chou, Lih-Ching|Hsieh, Tsung-Ting|Lee, Ding-Dar|Liu, Kai-Wei|Yu, Chi-Yuan|Oyang, Yen-Jen|Tsai, Huai-Kuang|Chen, Chien-Yu', 'Department of Computer Science and Information Engineering, National Taiwan University and Institute of Information Science, Academia Sinica, Taipei, Taiwan.|Department of Computer Science and Information Engineering, National Taiwan University and Institute of Information Science, Academia Sinica, Taipei, Taiwan.|Department of Computer Science and Information Engineering, National Taiwan University and Institute of Information Science, Academia Sinica, Taipei, Taiwan.|Department of Computer Science and Information Engineering, National Taiwan University and Institute of Information Science, Academia Sinica, Taipei, Taiwan.|Department of Computer Science and Information Engineering, National Taiwan University and Institute of Information Science, Academia Sinica, Taipei, Taiwan.|Department of Computer Science and Information Engineering, National Taiwan University and Institute of Information Science, Academia Sinica, Taipei, Taiwan.|Department of Computer Science and Information Engineering, National Taiwan University and Institute of Information Science, Academia Sinica, Taipei, Taiwan.|Department of Computer Science and Information Engineering, National Taiwan University and Institute of Information Science, Academia Sinica, Taipei, Taiwan.|Department of Computer Science and Information Engineering, National Taiwan University and Institute of Information Science, Academia Sinica, Taipei, Taiwan.', '-|-|-|-|-|-|-|-|-', 9, 'Chromatin Immunoprecipitation|Gene Expression Regulation, Fungal|Gene Regulatory Networks|Oligonucleotide Array Sequence Analysis|Protein Binding|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bts002', '22238267', 'Gene regulation involves complicated mechanisms such as cooperativity between a set of transcription factors (TFs). Previous studies have used target genes shared by two TFs as a clue to infer TF-TF interactions. However, this task remains challenging because the target genes with low binding affinity are frequently omitted by experimental data, especially when a single strict threshold is employed. This article aims at improving the accuracy of inferring TF-TF interactions by incorporating motif discovery as a fundamental step when detecting overlapping targets of TFs based on ChIP-chip data.'),
(76690, 2012, 'bio', 'Predicting folding free energy changes upon single point mutations', 'Zhang, Zhe|Wang, Lin|Gao, Yang|Zhang, Jie|Zhenirovskyy, Maxim|Alexov, Emil', 'Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA.|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA.|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA.|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA.|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA.|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA.', 'United States|United States|United States|United States|United States|United States', 42, 'Humans|Mutation, Missense|Point Mutation|Protein Folding|Protein Stability|Proteins|Software|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/bts005', '22238268', 'The folding free energy is an important characteristic of proteins stability and is directly related to proteins wild-type function. The changes of proteins stability due to naturally occurring mutations, missense mutations, are typically causing diseases. Single point mutations made in vitro are frequently used to assess the contribution of given amino acid to the stability of the protein. In both cases, it is desirable to predict the change of the folding free energy upon single point mutations in order to either provide insights of the molecular mechanism of the change or to design new experimental studies.'),
(76691, 2012, 'bio', 'GROMACS molecule & liquid database', 'van der Spoel, David|van Maaren, Paul J|Caleman, Carl', 'Department of Cell and Molecular Biology, Uppsala University, Husargatan 3, Box 596, SE-75124 Uppsala, Sweden. spoel@xray.bmc.uu.se|Department of Cell and Molecular Biology, Uppsala University, Husargatan 3, Box 596, SE-75124 Uppsala, Sweden. spoel@xray.bmc.uu.se|Department of Cell and Molecular Biology, Uppsala University, Husargatan 3, Box 596, SE-75124 Uppsala, Sweden. spoel@xray.bmc.uu.se', 'Sweden|Sweden|Sweden', 116, 'Databases, Factual|Models, Molecular|Molecular Dynamics Simulation|Proteins|Software|Surface Tension|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/bts020', '22238269', 'The molecular dynamics simulation package GROMACS is a widely used tool used in a broad range of different applications within physics, chemistry and biology. It is freely available, user friendly and extremely efficient. The GROMACS software is force field agnostic, and compatible with many molecular dynamics force fields, coarse-grained, unified atom, all atom as well as polarizable models based on the charge on a spring concept. To validate simulations, it is necessary to compare results from the simulations to experimental data. To ease the process of setting up topologies and structures for simulations, as well as providing pre-calculated physical properties along with experimental values for the same we provide a web-based database, containing 145 organic molecules at present.'),
(76692, 2012, 'bio', 'BESC knowledgebase public portal', 'Syed, Mustafa H|Karpinets, Tatiana V|Parang, Morey|Leuze, Michael R|Park, Byung H|Hyatt, Doug|Brown, Steven D|Moulton, Steve|Galloway, Michael D|Uberbacher, Edward C', 'BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA. syedmh@ornl.gov|BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA. syedmh@ornl.gov|BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA. syedmh@ornl.gov|BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA. syedmh@ornl.gov|BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA. syedmh@ornl.gov|BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA. syedmh@ornl.gov|BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA. syedmh@ornl.gov|BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA. syedmh@ornl.gov|BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA. syedmh@ornl.gov|BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA. syedmh@ornl.gov', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 5, 'Bacteria|Biofuels|Eukaryota|Genomics|Knowledge Bases|Plants', 'Journal Article', '10.1093/bioinformatics/bts016', '22238270', 'The BioEnergy Science Center (BESC) is undertaking large experimental campaigns to understand the biosynthesis and biodegradation of biomass and to develop biofuel solutions. BESC is generating large volumes of diverse data, including genome sequences, omics data and assay results. The purpose of the BESC Knowledgebase is to serve as a centralized repository for experimentally generated data and to provide an integrated, interactive and user-friendly analysis framework. The Portal makes available tools for visualization, integration and analysis of data either produced by BESC or obtained from external resources.'),
(76693, 2012, 'bio', 'Surrogate variable analysis using partial least squares (SVA-PLS) in gene expression studies', 'Chakraborty, Sutirtha|Datta, Somnath|Datta, Susmita', 'Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA.|Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA.|Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA.', 'United States|United States|United States', 32, 'Analysis of Variance|Computer Simulation|Gene Expression Profiling|Humans|Least-Squares Analysis|Leukemia, Megakaryoblastic, Acute|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/bts022', '22238271', 'In a typical gene expression profiling study, our prime objective is to identify the genes that are differentially expressed between the samples from two different tissue types. Commonly, standard analysis of variance (ANOVA)/regression is implemented to identify the relative effects of these genes over the two types of samples from their respective arrays of expression levels. But, this technique becomes fundamentally flawed when there are unaccounted sources of variability in these arrays (latent variables attributable to different biological, environmental or other factors relevant in the context). These factors distort the true picture of differential gene expression between the two tissue types and introduce spurious signals of expression heterogeneity. As a result, many genes which are actually differentially expressed are not detected, whereas many others are falsely identified as positives. Moreover, these distortions can be different for different genes. Thus, it is also not possible to get rid of these variations by simple array normalizations. This both-way error can lead to a serious loss in sensitivity and specificity, thereby causing a severe inefficiency in the underlying multiple testing problem. In this work, we attempt to identify the hidden effects of the underlying latent factors in a gene expression profiling study by partial least squares (PLS) and apply ANCOVA technique with the PLS-identified signatures of these hidden effects as covariates, in order to identify the genes that are truly differentially expressed between the two concerned tissue types.'),
(76694, 2012, 'bio', 'A scalable and portable framework for massively parallel variable selection in genetic association studies', 'Chen, Gary K', 'Division of Biostatistics, Department of Preventive Medicine, Los Angeles, CA 90089, USA. gary.k.chen@usc.edu', 'United States', 7, 'Algorithms|Genome-Wide Association Study|Humans|Male|Polymorphism, Single Nucleotide|Programming Languages|Prostatic Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/bts015', '22238272', 'The deluge of data emerging from high-throughput sequencing technologies poses large analytical challenges when testing for association to disease. We introduce a scalable framework for variable selection, implemented in C++ and OpenCL, that fits regularized regression across multiple Graphics Processing Units. Open source code and documentation can be found at a Google Code repository under the URL http://bioinformatics.oxfordjournals.org/content/early/2012/01/10/bioinformatics.bts015.abstract.'),
(76695, 2012, 'bio', 'Roundup 20: enabling comparative genomics for over 1800 genomes', 'DeLuca, Todd F|Cui, Jike|Jung, Jae-Yoon|St Gabriel, Kristian Che|Wall, Dennis P', 'The Center for Biomedical Informatics, Harvard Medical School and Department of Pathology, Beth Israel Deaconess Medical Center, Boston MA 02115, USA. todd_deluca@hms.harvard.edu|The Center for Biomedical Informatics, Harvard Medical School and Department of Pathology, Beth Israel Deaconess Medical Center, Boston MA 02115, USA. todd_deluca@hms.harvard.edu|The Center for Biomedical Informatics, Harvard Medical School and Department of Pathology, Beth Israel Deaconess Medical Center, Boston MA 02115, USA. todd_deluca@hms.harvard.edu|The Center for Biomedical Informatics, Harvard Medical School and Department of Pathology, Beth Israel Deaconess Medical Center, Boston MA 02115, USA. todd_deluca@hms.harvard.edu|The Center for Biomedical Informatics, Harvard Medical School and Department of Pathology, Beth Israel Deaconess Medical Center, Boston MA 02115, USA. todd_deluca@hms.harvard.edu', 'Israel|Israel|Israel|Israel|Israel', 29, 'Algorithms|Animals|Archaea|Bacteria|Cluster Analysis|Evolution, Molecular|Genome|Genomics|Humans|Phylogeny|Viruses', 'Journal Article', '10.1093/bioinformatics/bts006', '22247275', 'Roundup is an online database of gene orthologs for over 1800 genomes, including 226 Eukaryota, 1447 Bacteria, 113 Archaea and 21 Viruses. Orthologs are inferred using the Reciprocal Smallest Distance algorithm. Users may query Roundup for single-linkage clusters of orthologous genes based on any group of genomes. Annotated query results may be viewed in a variety of ways including as clusters of orthologs and as phylogenetic profiles. Genomic results may be downloaded in formats suitable for functional as well as phylogenetic analysis, including the recent OrthoXML standard. In addition, gene IDs can be retrieved using FASTA sequence search. All source code and orthologs are freely available.'),
(76696, 2012, 'bio', 'BOCTOPUS: improved topology prediction of transmembrane xcexb2 barrel proteins', 'Hayat, Sikander|Elofsson, Arne', 'Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm Bioinformatics Center, SciLifeLab, Swedish E-science Research Center, Stockholm University, SE-10691 Stockholm, Sweden.|Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm Bioinformatics Center, SciLifeLab, Swedish E-science Research Center, Stockholm University, SE-10691 Stockholm, Sweden.', 'Sweden|Sweden', 47, 'Bacterial Proteins|Computational Biology|Markov Chains|Membrane Proteins|Protein Conformation|Protein Structure, Secondary|Software|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btr710', '22247276', 'Transmembrane xcexb2 barrel proteins (TMBs) are found in the outer membrane of Gram-negative bacteria, chloroplast and mitochondria. They play a major role in the translocation machinery, pore formation, membrane anchoring and ion exchange. TMBs are also promising targets for antimicrobial drugs and vaccines. Given the difficulty in membrane protein structure determination, computational methods to identify TMBs and predict the topology of TMBs are important.'),
(76697, 2012, 'bio', 'Mining and evaluation of molecular relationships in literature', 'Senger, Christian|Grüning, Björn A|Erxleben, Anika|Döring, Kersten|Patel, Hitesh|Flemming, Stephan|Merfort, Irmgard|Günther, Stefan', 'Pharmaceutical Bioinformatics, Institute of Pharmaceutical Sciences, Albert-Ludwigs-University, Hermann-Herder-Str. 9, D-79104 Freiburg, Germany.|Pharmaceutical Bioinformatics, Institute of Pharmaceutical Sciences, Albert-Ludwigs-University, Hermann-Herder-Str. 9, D-79104 Freiburg, Germany.|Pharmaceutical Bioinformatics, Institute of Pharmaceutical Sciences, Albert-Ludwigs-University, Hermann-Herder-Str. 9, D-79104 Freiburg, Germany.|Pharmaceutical Bioinformatics, Institute of Pharmaceutical Sciences, Albert-Ludwigs-University, Hermann-Herder-Str. 9, D-79104 Freiburg, Germany.|Pharmaceutical Bioinformatics, Institute of Pharmaceutical Sciences, Albert-Ludwigs-University, Hermann-Herder-Str. 9, D-79104 Freiburg, Germany.|Pharmaceutical Bioinformatics, Institute of Pharmaceutical Sciences, Albert-Ludwigs-University, Hermann-Herder-Str. 9, D-79104 Freiburg, Germany.|Pharmaceutical Bioinformatics, Institute of Pharmaceutical Sciences, Albert-Ludwigs-University, Hermann-Herder-Str. 9, D-79104 Freiburg, Germany.|Pharmaceutical Bioinformatics, Institute of Pharmaceutical Sciences, Albert-Ludwigs-University, Hermann-Herder-Str. 9, D-79104 Freiburg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 7, 'Data Mining|Databases, Protein|Drug Discovery|Internet|Proteins|PubMed', 'Journal Article', '10.1093/bioinformatics/bts026', '22247277', 'Specific information on newly discovered proteins is often difficult to find in literature. Particularly if only sequences and no common names of proteins or genes are available, preceding sequence similarity searches can be crucial for the process of information collection. In drug research, it is important to know whether a small molecule targets only one specific protein or whether similar or homologous proteins are also influenced that may account for possible side effects.'),
(76698, 2012, 'bio', 'nEASE: a method for gene ontology subclassification of high-throughput gene expression data', 'Chittenden, Thomas W|Howe, Eleanor A|Taylor, Jennifer M|Mar, Jessica C|Aryee, Martin J|Gómez, Harold|Sultana, Razvan|Braisted, John|Nair, Sarita J|Quackenbush, John|Holmes, Chris', 'Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Gene Expression Profiling|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Software|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts011', '22247278', 'High-throughput technologies can identify genes whose expression profiles correlate with specific phenotypes, however, placing these genes into a biological context remains challenging. To help address this issue, we developed nested Expression Analysis Systematic Explorer (nEASE). nEASE complements traditional gene ontology enrichment approaches by determining statistically enriched gene ontology subterms within a list of genes based on co-annotation. Here, we overview an open-source software version of the nEASE algorithm. nEASE can be used either stand-alone or as part of a pathway discovery pipeline.'),
(76699, 2012, 'bio', 'Robust rank aggregation for gene list integration and meta-analysis', 'Kolde, Raivo|Laur, Sven|Adler, Priit|Vilo, Jaak', 'Institute of Computer Science, University of Tartu, Liivi 2- 314, 50409 Tartu, Estonia.|Institute of Computer Science, University of Tartu, Liivi 2- 314, 50409 Tartu, Estonia.|Institute of Computer Science, University of Tartu, Liivi 2- 314, 50409 Tartu, Estonia.|Institute of Computer Science, University of Tartu, Liivi 2- 314, 50409 Tartu, Estonia.', 'Estonia|Estonia|Estonia|Estonia', 279, 'Algorithms|Animals|Computational Biology|Gene Expression Profiling|Gene Knockout Techniques|Genomics|Humans|Meta-Analysis as Topic|Mice|Stem Cells|Yeasts', 'Journal Article', '10.1093/bioinformatics/btr709', '22247279', 'The continued progress in developing technological platforms, availability of many published experimental datasets, as well as different statistical methods to analyze those data have allowed approaching the same research question using various methods simultaneously. To get the best out of all these alternatives, we need to integrate their results in an unbiased manner. Prioritized gene lists are a common result presentation method in genomic data analysis applications. Thus, the rank aggregation methods can become a useful and general solution for the integration task.'),
(76700, 2012, 'bio', 'Estimation of pairwise sequence similarity of mammalian enhancers with word neighbourhood counts', 'Göke, Jonathan|Schulz, Marcel H|Lasserre, Julia|Vingron, Martin', 'Department for Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. goeke@molgen.mpg.de|Department for Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. goeke@molgen.mpg.de|Department for Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. goeke@molgen.mpg.de|Department for Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. goeke@molgen.mpg.de', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Animals|Cluster Analysis|Enhancer Elements, Genetic|Genome-Wide Association Study|Mice|Organ Specificity|Software', 'Journal Article', '10.1093/bioinformatics/bts028', '22247280', 'The identity of cells and tissues is to a large degree governed by transcriptional regulation. A major part is accomplished by the combinatorial binding of transcription factors at regulatory sequences, such as enhancers. Even though binding of transcription factors is sequence-specific, estimating the sequence similarity of two functionally similar enhancers is very difficult. However, a similarity measure for regulatory sequences is crucial to detect and understand functional similarities between two enhancers and will facilitate large-scale analyses like clustering, prediction and classification of genome-wide datasets.'),
(76701, 2012, 'bio', 'Application of canonical correlation analysis for identifying viral integration preferences', 'Gumus, Ergun|Kursun, Olcay|Sertbas, Ahmet|Ustek, Duran', 'Department of Computer Engineering, Istanbul University, Istanbul 34320, Turkey. egumus@istanbul.edu.tr|Department of Computer Engineering, Istanbul University, Istanbul 34320, Turkey. egumus@istanbul.edu.tr|Department of Computer Engineering, Istanbul University, Istanbul 34320, Turkey. egumus@istanbul.edu.tr|Department of Computer Engineering, Istanbul University, Istanbul 34320, Turkey. egumus@istanbul.edu.tr', 'Turkey|Turkey|Turkey|Turkey', 16, 'HIV Infections|HIV-1|Humans|Multivariate Analysis|Software|Virus Integration', 'Journal Article', '10.1093/bioinformatics/bts027', '22247281', 'Gene therapy aims at using viral vectors for attaching helpful genetic code to target genes. Therefore, it is of great importance to develop methods that can discover significant patterns around viral integration sites. Canonical correlation analysis is an unsupervised statistical tool that is used to describe the relations between two related views of the same semantic object, which fits well for identifying such salient patterns.'),
(76702, 2012, 'bio', 'IMA: an R package for high-throughput analysis of Illuminas 450K Infinium methylation data', 'Wang, Dan|Yan, Li|Hu, Qiang|Sucheston, Lara E|Higgins, Michael J|Ambrosone, Christine B|Johnson, Candace S|Smiraglia, Dominic J|Liu, Song', 'Department of Biostatistics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA.|Department of Biostatistics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA.|Department of Biostatistics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA.|Department of Biostatistics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA.|Department of Biostatistics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA.|Department of Biostatistics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA.|Department of Biostatistics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA.|Department of Biostatistics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA.|Department of Biostatistics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'CpG Islands|DNA Methylation|Genome, Human|Humans|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/bts013', '22253290', 'The Illumina Infinium HumanMethylation450 BeadChip is a newly designed high-density microarray for quantifying the methylation level of over 450 000 CpG sites within human genome. Illumina Methylation Analyzer (IMA) is a computational package designed to automate the pipeline for exploratory analysis and summarization of site-level and region-level methylation changes in epigenetic studies utilizing the 450K DNA methylation microarray. The pipeline loads the data from Illumina platform and provides user-customized functions commonly required to perform exploratory methylation analysis for individual sites as well as annotated regions.'),
(76703, 2012, 'bio', 'ReLA, a local alignment search tool for the identification of distal and proximal gene regulatory regions and their conserved transcription factor binding sites', 'González, Santi|Montserrat-Sentís, Bàrbara|Sánchez, Friman|Puiggròs, Montserrat|Blanco, Enrique|Ramirez, Alex|Torrents, David', 'Joint IRB-BSC program on Computational Biology, BSC c/ Jordi Girona 29, Catalonia.|Joint IRB-BSC program on Computational Biology, BSC c/ Jordi Girona 29, Catalonia.|Joint IRB-BSC program on Computational Biology, BSC c/ Jordi Girona 29, Catalonia.|Joint IRB-BSC program on Computational Biology, BSC c/ Jordi Girona 29, Catalonia.|Joint IRB-BSC program on Computational Biology, BSC c/ Jordi Girona 29, Catalonia.|Joint IRB-BSC program on Computational Biology, BSC c/ Jordi Girona 29, Catalonia.|Joint IRB-BSC program on Computational Biology, BSC c/ Jordi Girona 29, Catalonia.', '-|-|-|-|-|-|-', 0, 'Algorithms|Animals|Humans|Protein Binding|Regulatory Sequences, Nucleic Acid|Search Engine|Sequence Alignment|Transcription Factors|Transcription Initiation Site', 'Journal Article', '10.1093/bioinformatics/bts024', '22253291', 'The prediction and annotation of the genomic regions involved in gene expression has been largely explored. Most of the energy has been devoted to the development of approaches that detect transcription start sites, leaving the identification of regulatory regions and their functional transcription factor binding sites (TFBSs) largely unexplored and with important quantitative and qualitative methodological gaps.'),
(76704, 2012, 'bio', 'CODEX: exploration of semantic changes between ontology versions', 'Hartung, Michael|Gross, Anika|Rahm, Erhard', 'Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany. hartung@izbi.uni-leipzig.de|Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany. hartung@izbi.uni-leipzig.de|Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany. hartung@izbi.uni-leipzig.de', 'Germany|Germany|Germany', 14, 'Genes|Knowledge Bases|Semantics|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts029', '22253292', 'Life science ontologies substantially change over time to meet the requirements of their users and to include the newest domain knowledge. Thus, an important task is to know what has been modified between two versions of an ontology (diff). This diff should contain all performed changes as compact and understandable as possible. We present CODEX (Complex Ontology Diff Explorer), a tool that allows determining semantic changes between two versions of an ontology, which users can interactively analyze in multiple ways.'),
(76705, 2012, 'bio', 'SNP calling using genotype model selection on high-throughput sequencing data', 'You, Na|Murillo, Gabriel|Su, Xiaoquan|Zeng, Xiaowei|Xu, Jian|Ning, Kang|Zhang, Shoudong|Zhu, Jiankang|Cui, Xinping', 'Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China.|Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China.|Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China.|Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China.|Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China.|Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China.|Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China.|Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China.|Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China.', 'China|China|China|China|China|China|China|China|China', 0, 'Algorithms|Genomics|High-Throughput Nucleotide Sequencing|Models, Genetic|Polymorphism, Single Nucleotide|Predictive Value of Tests|Software|Thermoanaerobacter', 'Journal Article', '10.1093/bioinformatics/bts001', '22253293', 'A review of the available single nucleotide polymorphism (SNP) calling procedures for Illumina high-throughput sequencing (HTS) platform data reveals that most rely mainly on base-calling and mapping qualities as sources of error when calling SNPs. Thus, errors not involved in base-calling or alignment, such as those in genomic sample preparation, are not accounted for.'),
(76706, 2012, 'bio', 'Exact coalescent simulation of new haplotype data from existing reference haplotypes', 'Kang, Chul Joo|Marjoram, Paul', 'Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA. chulkang@usc.edu|Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA. chulkang@usc.edu', 'United States|United States', 0, 'Algorithms|Computer Simulation|Genome, Human|Genome-Wide Association Study|Haplotypes|Humans|Models, Genetic|Population Groups|Probability', 'Journal Article', '10.1093/bioinformatics/bts033', '22257666', 'We introduce a coalescent-based method (RECOAL) for the simulation of new haplotype data from a reference population of haplotypes. A coalescent genealogy for the reference haplotype data is sampled from the appropriate posterior probability distribution, then a coalescent genealogy is simulated which extends the sampled genealogy to include new haplotype data. The new haplotype data will, therefore, contain both some of the existing polymorphic sites and new polymorphisms added based on the structure of the simulated coalescent genealogy. This allows exact coalescent simulation of new haplotype data, compared with other methods which are more approximate in nature.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76707, 2012, 'bio', 'FX: an RNA-Seq analysis tool on the cloud', 'Hong, Dongwan|Rhie, Arang|Park, Sung-Soo|Lee, Jongkeun|Ju, Young Seok|Kim, Sujung|Yu, Saet-Byeol|Bleazard, Thomas|Park, Hyun-Seok|Rhee, Hwanseok|Chong, Hyonyong|Yang, Kap-Seok|Lee, Yeon-Su|Kim, In-Hoo|Lee, Jin Soo|Kim, Jong-Il|Seo, Jeong-Sun', 'Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.|Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul.', '-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-', 0, 'Gene Expression Profiling|Genome|Genome, Human|Humans|RNA Splice Sites|RNA Splicing|RNA, Messenger|Sequence Analysis, RNA|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts023', '22257667', 'FX is an RNA-Seq analysis tool, which runs in parallel on cloud computing infrastructure, for the estimation of gene expression levels and genomic variant calling. In the mapping of short RNA-Seq reads, FX uses a transcriptome-based reference primarily, generated from ~160 000 mRNA sequences from RefSeq, UCSC and Ensembl databases. This approach reduces the misalignment of reads originating from splicing junctions. Unmapped reads not aligned on known transcripts are then mapped on the human genome reference. FX allows analysis of RNA-Seq data on cloud computing infrastructures, supporting access through a user-friendly web interface.'),
(76708, 2012, 'bio', 'COPICAT: a software system for predicting interactions between proteins and chemical compounds', 'Sakakibara, Yasubumi|Hachiya, Tsuyoshi|Uchida, Miho|Nagamine, Nobuyoshi|Sugawara, Yohei|Yokota, Masahiro|Nakamura, Masaomi|Popendorf, Kris|Komori, Takashi|Sato, Kengo', 'Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan. yasu@bio.keio.ac.jp|Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan. yasu@bio.keio.ac.jp|Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan. yasu@bio.keio.ac.jp|Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan. yasu@bio.keio.ac.jp|Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan. yasu@bio.keio.ac.jp|Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan. yasu@bio.keio.ac.jp|Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan. yasu@bio.keio.ac.jp|Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan. yasu@bio.keio.ac.jp|Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan. yasu@bio.keio.ac.jp|Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan. yasu@bio.keio.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 13, 'Databases, Factual|Ligands|Protein Binding|Proteins|Software|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/bts031', '22257668', 'Since tens of millions of chemical compounds have been accumulated in public chemical databases, fast comprehensive computational methods to predict interactions between chemical compounds and proteins are needed for virtual screening of lead compounds. Previously, we proposed a novel method for predicting protein-chemical interactions using two-layer Support Vector Machine classifiers that require only readily available biochemical data, i.e. amino acid sequences of proteins and structure formulas of chemical compounds. In this article, the method has been implemented as the COPICAT web service, with an easy-to-use front-end interface. Users can simply submit a protein-chemical interaction prediction job using a pre-trained classifier, or can even train their own classification model by uploading training data. COPICATs fast and accurate computational prediction has enhanced lead compound discovery against a database of tens of millions of chemical compounds, implying that the search space for drug discovery is extended by >1000 times compared with currently well-used high-throughput screening methodologies.'),
(76709, 2012, 'bio', 'The sva package for removing batch effects and other unwanted variation in high-throughput experiments', 'Leek, Jeffrey T|Johnson, W Evan|Parker, Hilary S|Jaffe, Andrew E|Storey, John D', 'Department of Biostatistics, JHU Bloomberg School of Public Health, Baltimore, MD, USA. jleek@jhsph.edu|Department of Biostatistics, JHU Bloomberg School of Public Health, Baltimore, MD, USA. jleek@jhsph.edu|Department of Biostatistics, JHU Bloomberg School of Public Health, Baltimore, MD, USA. jleek@jhsph.edu|Department of Biostatistics, JHU Bloomberg School of Public Health, Baltimore, MD, USA. jleek@jhsph.edu|Department of Biostatistics, JHU Bloomberg School of Public Health, Baltimore, MD, USA. jleek@jhsph.edu', 'United States|United States|United States|United States|United States', 988, 'Gene Expression Profiling|Genomics|High-Throughput Nucleotide Sequencing|Humans|Regression Analysis|Software|Urinary Bladder Neoplasms', 'Journal Article', '10.1093/bioinformatics/bts034', '22257669', 'Heterogeneity and latent variables are now widely recognized as major sources of bias and variability in high-throughput experiments. The most well-known source of latent variation in genomic experiments are batch effects-when samples are processed on different days, in different groups or by different people. However, there are also a large number of other variables that may have a major impact on high-throughput measurements. Here we describe the sva package for identifying, estimating and removing unwanted sources of variation in high-throughput experiments. The sva package supports surrogate variable estimation with the sva function, direct adjustment for known batch effects with the ComBat function and adjustment for batch and latent variables in prediction problems with the fsva function.'),
(76710, 2012, 'bio', 'AnnTools: a comprehensive and versatile annotation toolkit for genomic variants', 'Makarov, Vladimir|OGrady, Tina|Cai, Guiqing|Lihm, Jayon|Buxbaum, Joseph D|Yoon, Seungtai', 'The Seaver Autism Center for Research and Treatment, Department of Psychiatry, Levy Library, Mount Sinai School of Medicine, New York, NY 10029, USA. vladimir.makarov@mssm.edu|The Seaver Autism Center for Research and Treatment, Department of Psychiatry, Levy Library, Mount Sinai School of Medicine, New York, NY 10029, USA. vladimir.makarov@mssm.edu|The Seaver Autism Center for Research and Treatment, Department of Psychiatry, Levy Library, Mount Sinai School of Medicine, New York, NY 10029, USA. vladimir.makarov@mssm.edu|The Seaver Autism Center for Research and Treatment, Department of Psychiatry, Levy Library, Mount Sinai School of Medicine, New York, NY 10029, USA. vladimir.makarov@mssm.edu|The Seaver Autism Center for Research and Treatment, Department of Psychiatry, Levy Library, Mount Sinai School of Medicine, New York, NY 10029, USA. vladimir.makarov@mssm.edu|The Seaver Autism Center for Research and Treatment, Department of Psychiatry, Levy Library, Mount Sinai School of Medicine, New York, NY 10029, USA. vladimir.makarov@mssm.edu', 'United States|United States|United States|United States|United States|United States', 32, 'DNA Copy Number Variations|Genetic Variation|Genome, Human|Humans|Molecular Sequence Annotation|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/bts032', '22257670', 'AnnTools is a versatile bioinformatics application designed for comprehensive annotation of a full spectrum of human genome variation: novel and known single-nucleotide substitutions (SNP/SNV), short insertions/deletions (INDEL) and structural variants/copy number variation (SV/CNV). The variants are interpreted by interrogating data compiled from 15 constantly updated sources. In addition to detailed functional characterization of the coding variants, AnnTools searches for overlaps with regulatory elements, disease/trait associated loci, known segmental duplications and artifact prone regions, thereby offering an integrated and comprehensive analysis of genomic data. The tool conveniently accepts user-provided tracks for custom annotation and offers flexibility in input data formats. The output is generated in the universal Variant Call Format. High annotation speed makes AnnTools suitable for high-throughput sequencing facilities, while a low-memory footprint and modest CPU requirements allow it to operate on a personal computer. The application is freely available for public use, the package includes installation scripts and a set of helper tools.'),
(76711, 2012, 'bio', 'Construction and completion of flux balance models from pathway databases', 'Latendresse, Mario|Krummenacker, Markus|Trupp, Miles|Karp, Peter D', 'Bioinformatics Research Group/Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA. mario.latendresse@sri.com|Bioinformatics Research Group/Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA. mario.latendresse@sri.com|Bioinformatics Research Group/Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA. mario.latendresse@sri.com|Bioinformatics Research Group/Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA. mario.latendresse@sri.com', 'United States|United States|United States|United States', 0, 'Databases, Protein|Escherichia coli|Humans|Metabolic Networks and Pathways|Models, Biological|Proteome|Software', 'Journal Article', '10.1093/bioinformatics/btr681', '22262672', 'Flux balance analysis (FBA) is a well-known technique for genome-scale modeling of metabolic flux. Typically, an FBA formulation requires the accurate specification of four sets: biochemical reactions, biomass metabolites, nutrients and secreted metabolites. The development of FBA models can be time consuming and tedious because of the difficulty in assembling completely accurate descriptions of these sets, and in identifying errors in the composition of these sets. For example, the presence of a single non-producible metabolite in the biomass will make the entire model infeasible. Other difficulties in FBA modeling are that model distributions, and predicted fluxes, can be cryptic and difficult to understand.'),
(76712, 2012, 'bio', 'medpie: an information extraction package for medical message board posts', 'Benton, A|Holmes, J H|Hill, S|Chung, A|Ungar, L', 'University of Pennsylvania School of Medicine, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, PA 19104, USA.|University of Pennsylvania School of Medicine, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, PA 19104, USA.|University of Pennsylvania School of Medicine, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, PA 19104, USA.|University of Pennsylvania School of Medicine, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, PA 19104, USA.|University of Pennsylvania School of Medicine, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, PA 19104, USA.', 'United States|United States|United States|United States|United States', 0, 'Adverse Drug Reaction Reporting Systems|Diet|Humans|Internet|Medical Informatics|Software', 'Journal Article', '10.1093/bioinformatics/bts030', '22262673', 'We have developed medpie, a software package for preparing medical message board corpora and extracting patient mentions and statistics for drugs, herbs and adverse effects experienced from them. The package is divided into web-crawling, HTML-cleaning, de-identification and information extraction modules. It also includes a sample controlled vocabulary of drugs, herbs and adverse effect terms.'),
(76713, 2012, 'bio', 'An effective statistical evaluation of ChIPseq dataset similarity', 'Chikina, Maria D|Troyanskaya, Olga G', 'Department of Neurology, Mount Sinai School of Medicine, New York, NY 10029, USA.|Department of Neurology, Mount Sinai School of Medicine, New York, NY 10029, USA.', 'United States|United States', 37, 'Algorithms|Chromatin Immunoprecipitation|Genomics|Programming Languages|Sequence Analysis, DNA|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/bts009', '22262674', 'ChIPseq is rapidly becoming a common technique for investigating protein-DNA interactions. However, results from individual experiments provide a limited understanding of chromatin structure, as various chromatin factors cooperate in complex ways to orchestrate transcription. In order to quantify chromtain interactions, it is thus necessary to devise a robust similarity metric applicable to ChIPseq data. Unfortunately, moving past simple overlap calculations to give statistically rigorous comparisons of ChIPseq datasets often involves arbitrary choices of distance metrics, with significance being estimated by computationally intensive permutation tests whose statistical power may be sensitive to non-biological experimental and post-processing variation.'),
(76714, 2012, 'bio', 'A Boolean network model of the FA/BRCA pathway', 'Rodríguez, Alfredo|Sosa, David|Torres, Leda|Molina, Bertha|Frías, Sara|Mendoza, Luis', 'Departamento de Investigación en Genética Humana, Instituto Nacional de Pediatría, Posgrado en Ciencias Biológicas, México.|Departamento de Investigación en Genética Humana, Instituto Nacional de Pediatría, Posgrado en Ciencias Biológicas, México.|Departamento de Investigación en Genética Humana, Instituto Nacional de Pediatría, Posgrado en Ciencias Biológicas, México.|Departamento de Investigación en Genética Humana, Instituto Nacional de Pediatría, Posgrado en Ciencias Biológicas, México.|Departamento de Investigación en Genética Humana, Instituto Nacional de Pediatría, Posgrado en Ciencias Biológicas, México.|Departamento de Investigación en Genética Humana, Instituto Nacional de Pediatría, Posgrado en Ciencias Biológicas, México.', '-|-|-|-|-|-', 0, 'BRCA1 Protein|Breast Neoplasms|Cell Cycle|Cells, Cultured|DNA Damage|DNA Repair|Fanconi Anemia|Fanconi Anemia Complementation Group Proteins|Genomic Instability|Humans|Models, Biological', 'Journal Article', '10.1093/bioinformatics/bts036', '22267503', 'Fanconi anemia (FA) is a chromosomal instability syndrome originated by inherited mutations that impair the Fanconi Anemia/Breast Cancer (FA/BRCA) pathway, which is committed to the repair of DNA interstrand cross-links (ICLs). The disease displays increased spontaneous chromosomal aberrations and hypersensitivity to agents that create DNA interstrand cross-links. In spite of DNA damage, FA/BRCA-deficient cells are able to progress throughout the cell cycle, probably due to the activity of alternative DNA repair pathways, or due to defects in the checkpoints that monitor DNA integrity.'),
(76715, 2012, 'bio', 'Mining and integration of pathway diagrams from imaging data', 'Kozhenkov, Sergey|Baitaluk, Michael', 'San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA.|San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA.', 'United States|United States', 8, 'Cells|Data Mining|Humans|Internet|Medical Illustration|Organelles|Proteins|PubMed|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/bts018', '22267504', 'Pathway diagrams from PubMed and World Wide Web (WWW) contain valuable highly curated information difficult to reach without tools specifically designed and customized for the biological semantics and high-content density of the images. There is currently no search engine or tool that can analyze pathway images, extract their pathway components (molecules, genes, proteins, organelles, cells, organs, etc.) and indicate their relationships.'),
(76716, 2012, 'bio', 'Using biologically interrelated experiments to identify pathway genes in Arabidopsis', 'Kim, Kyungpil|Jiang, Keni|Teng, Siew Leng|Feldman, Lewis J|Huang, Haiyan', 'Division of Biostatistics, University of California, Berkeley, CA, USA.|Division of Biostatistics, University of California, Berkeley, CA, USA.|Division of Biostatistics, University of California, Berkeley, CA, USA.|Division of Biostatistics, University of California, Berkeley, CA, USA.|Division of Biostatistics, University of California, Berkeley, CA, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Arabidopsis|Genes, Plant|Metabolic Networks and Pathways|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/bts038', '22271267', 'Pathway genes are considered as a group of genes that work cooperatively in the same pathway constituting a fundamental functional grouping in a biological process. Identifying pathway genes has been one of the major tasks in understanding biological processes. However, due to the difficulty in characterizing/inferring different types of biological gene relationships, as well as several computational issues arising from dealing with high-dimensional biological data, deducing genes in pathways remain challenging.'),
(76717, 2012, 'bio', 'Assumption weighting for incorporating heterogeneity into meta-analysis of genomic data', 'Li, Yihan|Ghosh, Debashis', 'Department of Statistics, Penn State University, University Park, PA 16802, USA.|Department of Statistics, Penn State University, University Park, PA 16802, USA.', 'United States|United States', 0, 'Databases, Genetic|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Stem Cells', 'Journal Article', '10.1093/bioinformatics/bts037', '22285559', 'There is now a large literature on statistical methods for the meta-analysis of genomic data from multiple studies. However, a crucial assumption for performing many of these analyses is that the data exhibit small between-study variation or that this heterogeneity can be sufficiently modelled probabilistically.'),
(76718, 2012, 'bio', 'vHOG, a multispecies vertebrate ontology of homologous organs groups', 'Niknejad, Anne|Comte, Aurélie|Parmentier, Gilles|Roux, Julien|Bastian, Frederic B|Robinson-Rechavi, Marc', 'Department of Ecology and Evolution, Biophore, University of Lausanne, Lausanne, Switzerland.|Department of Ecology and Evolution, Biophore, University of Lausanne, Lausanne, Switzerland.|Department of Ecology and Evolution, Biophore, University of Lausanne, Lausanne, Switzerland.|Department of Ecology and Evolution, Biophore, University of Lausanne, Lausanne, Switzerland.|Department of Ecology and Evolution, Biophore, University of Lausanne, Lausanne, Switzerland.|Department of Ecology and Evolution, Biophore, University of Lausanne, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 16, 'Animals|Biological Evolution|Computational Biology|Databases, Factual|Gene Expression|Terminology as Topic|Vertebrates|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts048', '22285560', 'Most anatomical ontologies are species-specific, whereas a framework for comparative studies is needed. We describe the vertebrate Homologous Organs Groups ontology, vHOG, used to compare expression patterns between species.'),
(76719, 2012, 'bio', 'Literature mining of host-pathogen interactions: comparing feature-based supervised learning and language-based approaches', 'Thieu, Thanh|Joshi, Sneha|Warren, Samantha|Korkin, Dmitry', 'Department of Computer Science, University of Missouri, Columbia, MO 65211, USA.|Department of Computer Science, University of Missouri, Columbia, MO 65211, USA.|Department of Computer Science, University of Missouri, Columbia, MO 65211, USA.|Department of Computer Science, University of Missouri, Columbia, MO 65211, USA.', 'United States|United States|United States|United States', 0, 'Animals|Data Mining|Host-Pathogen Interactions|Humans|Infection|Natural Language Processing|Proteins|PubMed|Software|Support Vector Machine', 'Comparative Study', '10.1093/bioinformatics/bts042', '22285561', 'In an infectious disease, the pathogens strategy to enter the host organism and breach its immune defenses often involves interactions between the host and pathogen proteins. Currently, the experimental data on host-pathogen interactions (HPIs) are scattered across multiple databases, which are often specialized to target a specific disease or host organism. An accurate and efficient method for the automated extraction of HPIs from biomedical literature is crucial for creating a unified repository of HPI data.'),
(76720, 2012, 'bio', 'JointSNVMix: a probabilistic model for accurate detection of somatic mutations in normal/tumour paired next-generation sequencing data', 'Roth, Andrew|Ding, Jiarui|Morin, Ryan|Crisan, Anamaria|Ha, Gavin|Giuliany, Ryan|Bashashati, Ali|Hirst, Martin|Turashvili, Gulisa|Oloumi, Arusha|Marra, Marco A|Aparicio, Samuel|Shah, Sohrab P', 'Department of Molecular Oncology, BC Cancer Agency, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, BC, Canada.|Department of Molecular Oncology, BC Cancer Agency, BC, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 116, 'Computational Biology|DNA Mutational Analysis|DNA, Neoplasm|Humans|Models, Statistical|Mutation|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/bts053', '22285562', 'Identification of somatic single nucleotide variants (SNVs) in tumour genomes is a necessary step in defining the mutational landscapes of cancers. Experimental designs for genome-wide ascertainment of somatic mutations now routinely include next-generation sequencing (NGS) of tumour DNA and matched constitutional DNA from the same individual. This allows investigators to control for germline polymorphisms and distinguish somatic mutations that are unique to the tumour, thus reducing the burden of labour-intensive and expensive downstream experiments needed to verify initial predictions. In order to make full use of such paired datasets, computational tools for simultaneous analysis of tumour-normal paired sequence data are required, but are currently under-developed and under-represented in the bioinformatics literature.'),
(76721, 2012, 'bio', 'Functional microRNA targets in protein coding sequences', 'Reczko, Martin|Maragkakis, Manolis|Alexiou, Panagiotis|Grosse, Ivo|Hatzigeorgiou, Artemis G', 'Institute of Molecular Oncology, Biomedical Sciences Research Center, Vari, Greece. reczko@fleming.gr|Institute of Molecular Oncology, Biomedical Sciences Research Center, Vari, Greece. reczko@fleming.gr|Institute of Molecular Oncology, Biomedical Sciences Research Center, Vari, Greece. reczko@fleming.gr|Institute of Molecular Oncology, Biomedical Sciences Research Center, Vari, Greece. reczko@fleming.gr|Institute of Molecular Oncology, Biomedical Sciences Research Center, Vari, Greece. reczko@fleming.gr', 'Greece|Greece|Greece|Greece|Greece', 272, '3 Untranslated Regions|Algorithms|Animals|Humans|MicroRNAs|Open Reading Frames|Regulatory Sequences, Ribonucleic Acid', 'Journal Article', '10.1093/bioinformatics/bts043', '22285563', 'Experimental evidence has accumulated showing that microRNA (miRNA) binding sites within protein coding sequences (CDSs) are functional in controlling gene expression.'),
(76722, 2012, 'bio', 'SynaptomeDB: an ontology-based knowledgebase for synaptic genes', 'Pirooznia, Mehdi|Wang, Tao|Avramopoulos, Dimitrios|Valle, David|Thomas, Gareth|Huganir, Richard L|Goes, Fernando S|Potash, James B|Zandi, Peter P', 'Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, MD, USA. mpirooz1@jhmi.edu|Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, MD, USA. mpirooz1@jhmi.edu|Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, MD, USA. mpirooz1@jhmi.edu|Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, MD, USA. mpirooz1@jhmi.edu|Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, MD, USA. mpirooz1@jhmi.edu|Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, MD, USA. mpirooz1@jhmi.edu|Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, MD, USA. mpirooz1@jhmi.edu|Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, MD, USA. mpirooz1@jhmi.edu|Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, MD, USA. mpirooz1@jhmi.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Databases, Genetic|Genomics|Humans|Internet|Knowledge Bases|Proteins|Synapses', 'Journal Article', '10.1093/bioinformatics/bts040', '22285564', 'The synapse is integral to the function of the brain and may be an important source of dysfunction underlying many neuropsychiatric disorders. Consequently, it is an excellent candidate for large-scale genomic and proteomic study. However, while the tools and databases available for the annotation of high-throughput DNA and protein are generally robust, a comprehensive resource dedicated to the integration of information about the synapse is lacking.'),
(76723, 2012, 'bio', 'Genotype calling from next-generation sequencing data using haplotype information of reads', 'Zhi, Degui|Wu, Jihua|Liu, Nianjun|Zhang, Kui', 'Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA. dzhi@ms.soph.uab.edu|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA. dzhi@ms.soph.uab.edu|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA. dzhi@ms.soph.uab.edu|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA. dzhi@ms.soph.uab.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Computational Biology|Computer Simulation|Genome-Wide Association Study|Genotype|HapMap Project|Haplotypes|Humans|Linkage Disequilibrium|Markov Chains|Models, Statistical|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts047', '22285565', 'Low coverage sequencing provides an economic strategy for whole genome sequencing. When sequencing a set of individuals, genotype calling can be challenging due to low sequencing coverage. Linkage disequilibrium (LD) based refinement of genotyping calling is essential to improve the accuracy. Current LD-based methods use read counts or genotype likelihoods at individual potential polymorphic sites (PPSs). Reads that span multiple PPSs (jumping reads) can provide additional haplotype information overlooked by current methods.'),
(76724, 2012, 'bio', 'TurboKnot: rapid prediction of conserved RNA secondary structures including pseudoknots', 'Seetin, Matthew G|Mathews, David H', 'Department of Biochemistry and Biophysics, University of Rochester Medical Center, Rochester, NY 14642, USA.|Department of Biochemistry and Biophysics, University of Rochester Medical Center, Rochester, NY 14642, USA.', 'United States|United States', 0, 'Algorithms|Mycobacterium tuberculosis|Nucleic Acid Conformation|RNA, Bacterial|RNA, Untranslated|Ribonuclease P|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/bts044', '22285566', 'Many RNA molecules function without being translated into proteins, and function depends on structure. Pseudoknots are motifs in RNA secondary structures that are difficult to predict but are also often functionally important.'),
(76725, 2012, 'bio', 'The Transcriptome Analysis and Comparison Explorer--T-ACE: a platform-independent, graphical tool to process large RNAseq datasets of non-model organisms', 'Philipp, E E R|Kraemer, L|Mountfort, D|Schilhabel, M|Schreiber, S|Rosenstiel, P', 'Department of Cell Biology, Christian-Albrechts-University Kiel, Schittenhelmstrasse 12, Kiel, Germany. e.philipp@ikmb.uni-kiel.de|Department of Cell Biology, Christian-Albrechts-University Kiel, Schittenhelmstrasse 12, Kiel, Germany. e.philipp@ikmb.uni-kiel.de|Department of Cell Biology, Christian-Albrechts-University Kiel, Schittenhelmstrasse 12, Kiel, Germany. e.philipp@ikmb.uni-kiel.de|Department of Cell Biology, Christian-Albrechts-University Kiel, Schittenhelmstrasse 12, Kiel, Germany. e.philipp@ikmb.uni-kiel.de|Department of Cell Biology, Christian-Albrechts-University Kiel, Schittenhelmstrasse 12, Kiel, Germany. e.philipp@ikmb.uni-kiel.de|Department of Cell Biology, Christian-Albrechts-University Kiel, Schittenhelmstrasse 12, Kiel, Germany. e.philipp@ikmb.uni-kiel.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Animals|Gene Expression Profiling|Mollusca|Polychaeta|Programming Languages|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts056', '22285826', 'Next generation sequencing (NGS) technologies allow a rapid and cost-effective compilation of large RNA sequence datasets in model and non-model organisms. However, the storage and analysis of transcriptome information from different NGS platforms is still a significant bottleneck, leading to a delay in data dissemination and subsequent biological understanding. Especially database interfaces with transcriptome analysis modules going beyond mere read counts are missing. Here, we present the Transcriptome Analysis and Comparison Explorer (T-ACE), a tool designed for the organization and analysis of large sequence datasets, and especially suited for transcriptome projects of non-model organisms with little or no a priori sequence information. T-ACE offers a TCL-based interface, which accesses a PostgreSQL database via a php-script. Within T-ACE, information belonging to single sequences or contigs, such as annotation or read coverage, is linked to the respective sequence and immediately accessible. Sequences and assigned information can be searched via keyword- or BLAST-search. Additionally, T-ACE provides within and between transcriptome analysis modules on the level of expression, GO terms, KEGG pathways and protein domains. Results are visualized and can be easily exported for external analysis. We developed T-ACE for laboratory environments, which have only a limited amount of bioinformatics support, and for collaborative projects in which different partners work on the same dataset from different locations or platforms (Windows/Linux/MacOS). For laboratories with some experience in bioinformatics and programming, the low complexity of the database structure and open-source code provides a framework that can be customized according to the different needs of the user and transcriptome project.'),
(76726, 2012, 'bio', 'Chado controller: advanced annotation management with a community annotation system', 'Guignon, Valentin|Droc, Gaëtan|Alaux, Michael|Baurens, Franc-Christophe|Garsmeur, Olivier|Poiron, Claire|Carver, Tim|Rouard, Mathieu|Bocs, Stéphanie', 'CIRAD, UMR AGAP, F-34398 Montpellier, France. valentin.guignon@cirad.fr|CIRAD, UMR AGAP, F-34398 Montpellier, France. valentin.guignon@cirad.fr|CIRAD, UMR AGAP, F-34398 Montpellier, France. valentin.guignon@cirad.fr|CIRAD, UMR AGAP, F-34398 Montpellier, France. valentin.guignon@cirad.fr|CIRAD, UMR AGAP, F-34398 Montpellier, France. valentin.guignon@cirad.fr|CIRAD, UMR AGAP, F-34398 Montpellier, France. valentin.guignon@cirad.fr|CIRAD, UMR AGAP, F-34398 Montpellier, France. valentin.guignon@cirad.fr|CIRAD, UMR AGAP, F-34398 Montpellier, France. valentin.guignon@cirad.fr|CIRAD, UMR AGAP, F-34398 Montpellier, France. valentin.guignon@cirad.fr', 'France|France|France|France|France|France|France|France|France', 7, 'Computational Biology|Database Management Systems|Genomics|Molecular Sequence Annotation|Software|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts046', '22285827', 'We developed a controller that is compliant with the Chado database schema, GBrowse and genome annotation-editing tools such as Artemis and Apollo. It enables the management of public and private data, monitors manual annotation (with controlled vocabularies, structural and functional annotation controls) and stores versions of annotation for all modified features. The Chado controller uses PostgreSQL and Perl.'),
(76727, 2012, 'bio', 'HandAlign: Bayesian multiple sequence alignment, phylogeny and ancestral reconstruction', 'Westesson, Oscar|Barquist, Lars|Holmes, Ian', 'Department of Bioengineering, University of California Berkeley, CA 94720, USA.|Department of Bioengineering, University of California Berkeley, CA 94720, USA.|Department of Bioengineering, University of California Berkeley, CA 94720, USA.', 'United States|United States|United States', 11, 'Bayes Theorem|HIV|HIV Envelope Protein gp120|INDEL Mutation|Markov Chains|Membrane Glycoproteins|Monte Carlo Method|Phylogeny|Sequence Alignment|Simian Immunodeficiency Virus|Software|Viral Envelope Proteins', 'Journal Article', '10.1093/bioinformatics/bts058', '22285828', 'We describe handalign, a software package for Bayesian reconstruction of phylogenetic history. The underlying model of sequence evolution describes indels and substitutions. Alignments, trees and model parameters are all treated as jointly dependent random variables and sampled via Metropolis-Hastings Markov chain Monte Carlo (MCMC), enabling systematic statistical parameter inference and hypothesis testing. handalign implements several different MCMC proposal kernels, allows sampling from arbitrary target distributions via Hastings ratios, and uses standard file formats for trees, alignments and models.'),
(76728, 2012, 'bio', 'Measurement of genome-wide RNA synthesis and decay rates with Dynamic Transcriptome Analysis (DTA)', 'Schwalb, Björn|Schulz, Daniel|Sun, Mai|Zacher, Benedikt|Dümcke, Sebastian|Martin, Dietmar E|Cramer, Patrick|Tresch, Achim', 'Department of Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany. schwalb@lmb.uni-muenchen.de|Department of Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany. schwalb@lmb.uni-muenchen.de|Department of Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany. schwalb@lmb.uni-muenchen.de|Department of Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany. schwalb@lmb.uni-muenchen.de|Department of Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany. schwalb@lmb.uni-muenchen.de|Department of Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany. schwalb@lmb.uni-muenchen.de|Department of Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany. schwalb@lmb.uni-muenchen.de|Department of Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany. schwalb@lmb.uni-muenchen.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Cell Cycle|Gene Expression Profiling|Genome-Wide Association Study|Oligonucleotide Array Sequence Analysis|RNA Stability|Saccharomyces cerevisiae|Schizosaccharomyces|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/bts052', '22285829', 'Standard transcriptomics measures total cellular RNA levels. Our understanding of gene regulation would be greatly improved if we could measure RNA synthesis and decay rates on a genome-wide level. To that end, the Dynamic Transcriptome Analysis (DTA) method has been developed. DTA combines metabolic RNA labeling with standard transcriptomics to measure RNA synthesis and decay rates in a precise and non-perturbing manner. Here, we present the open source R/Bioconductor software package DTA. It implements all required bioinformatics steps that allow the accurate absolute quantification and comparison of RNA turnover.'),
(76729, 2012, 'bio', 'A co-module approach for elucidating drug-disease associations and revealing their molecular basis', 'Zhao, Shiwen|Li, Shao', 'MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing, China.|MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing, China.', 'China|China', 0, 'Algorithms|Bayes Theorem|Computational Biology|Disease Susceptibility|Drug Therapy|Gene Regulatory Networks|Humans|Markov Chains|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/bts057', '22285830', 'Understanding how drugs and diseases are associated in the molecular level is of critical importance to unveil disease mechanisms and treatments. Until recently, few studies attempt end to discover important gene modules shared by both drugs and diseases.'),
(76730, 2012, 'bio', 'A new approach to bias correction in RNA-Seq', 'Jones, Daniel C|Ruzzo, Walter L|Peng, Xinxia|Katze, Michael G', 'Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195-2350, USA. dcjones@cs.washington.edu|Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195-2350, USA. dcjones@cs.washington.edu|Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195-2350, USA. dcjones@cs.washington.edu|Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195-2350, USA. dcjones@cs.washington.edu', 'United States|United States|United States|United States', 16, 'Bayes Theorem|Computational Biology|Humans|Models, Statistical|Molecular Sequence Annotation|RNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts055', '22285831', 'Quantification of sequence abundance in RNA-Seq experiments is often conflated by protocol-specific sequence bias. The exact sources of the bias are unknown, but may be influenced by polymerase chain reaction amplification, or differing primer affinities and mixtures, for example. The result is decreased accuracy in many applications, such as de novo gene annotation and transcript quantification.'),
(76731, 2012, 'bio', 'SOAP3: ultra-fast GPU-based parallel alignment tool for short reads', 'Liu, Chi-Man|Wong, Thomas|Wu, Edward|Luo, Ruibang|Yiu, Siu-Ming|Li, Yingrui|Wang, Bingqiang|Yu, Chang|Chu, Xiaowen|Zhao, Kaiyong|Li, Ruiqiang|Lam, Tak-Wah', 'Department of Computer Science, The University of Hong Kong, Hong Kong, China.|Department of Computer Science, The University of Hong Kong, Hong Kong, China.|Department of Computer Science, The University of Hong Kong, Hong Kong, China.|Department of Computer Science, The University of Hong Kong, Hong Kong, China.|Department of Computer Science, The University of Hong Kong, Hong Kong, China.|Department of Computer Science, The University of Hong Kong, Hong Kong, China.|Department of Computer Science, The University of Hong Kong, Hong Kong, China.|Department of Computer Science, The University of Hong Kong, Hong Kong, China.|Department of Computer Science, The University of Hong Kong, Hong Kong, China.|Department of Computer Science, The University of Hong Kong, Hong Kong, China.|Department of Computer Science, The University of Hong Kong, Hong Kong, China.|Department of Computer Science, The University of Hong Kong, Hong Kong, China.', 'China|China|China|China|China|China|China|China|China|China|China|China', 0, 'Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts061', '22285832', 'SOAP3 is the first short read alignment tool that leverages the multi-processors in a graphic processing unit (GPU) to achieve a drastic improvement in speed. We adapted the compressed full-text index (BWT) used by SOAP2 in view of the advantages and disadvantages of GPU. When tested with millions of Illumina Hiseq 2000 length-100 bp reads, SOAP3 takes < 30 s to align a million read pairs onto the human reference genome and is at least 7.5 and 20 times faster than BWA and Bowtie, respectively. For aligning reads with up to four mismatches, SOAP3 aligns slightly more reads than BWA and Bowtie, this is because SOAP3, unlike BWA and Bowtie, is not heuristic-based and always reports all answers.'),
(76732, 2012, 'bio', 'Inhibition of HIV-1 protease: the rigidity perspective', 'Heal, J W|Jimenez-Roldan, J E|Wells, S A|Freedman, R B|Rxc3xb6mer, R A', 'MOAC Doctoral Training Centre, University of Warwick, Coventry CV4 7AL, UK. jack.heal@warwick.ac.uk|MOAC Doctoral Training Centre, University of Warwick, Coventry CV4 7AL, UK. jack.heal@warwick.ac.uk|MOAC Doctoral Training Centre, University of Warwick, Coventry CV4 7AL, UK. jack.heal@warwick.ac.uk|MOAC Doctoral Training Centre, University of Warwick, Coventry CV4 7AL, UK. jack.heal@warwick.ac.uk|MOAC Doctoral Training Centre, University of Warwick, Coventry CV4 7AL, UK. jack.heal@warwick.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 19, 'Catalytic Domain|Crystallography, X-Ray|HIV Protease|HIV Protease Inhibitors|HIV-1|Models, Molecular', 'Journal Article', '10.1093/bioinformatics/btr683', '22291339', 'HIV-1 protease is a key drug target due to its role in the life cycle of the HIV-1 virus. Rigidity analysis using the software First is a computationally inexpensive method for inferring functional information from protein crystal structures. We evaluate the rigidity of 206 high-resolution (2 xc3x85 or better) X-ray crystal structures of HIV-1 protease and compare the effects of different inhibitors binding to the enzyme.'),
(76733, 2012, 'bio', 'Predicting relapse prior to transplantation in chronic myeloid leukemia by integrating expert knowledge and expression data', 'Yeung, K Y|Gooley, T A|Zhang, A|Raftery, A E|Radich, J P|Oehler, V G', 'Department of Microbiology, University of Washington, Seattle, WA 98195, USA. kayee@u.washington.edu|Department of Microbiology, University of Washington, Seattle, WA 98195, USA. kayee@u.washington.edu|Department of Microbiology, University of Washington, Seattle, WA 98195, USA. kayee@u.washington.edu|Department of Microbiology, University of Washington, Seattle, WA 98195, USA. kayee@u.washington.edu|Department of Microbiology, University of Washington, Seattle, WA 98195, USA. kayee@u.washington.edu|Department of Microbiology, University of Washington, Seattle, WA 98195, USA. kayee@u.washington.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Bayes Theorem|Disease Progression|Hematopoietic Stem Cell Transplantation|Humans|Leukemia, Myelogenous, Chronic, BCR-ABL Positive|Leukemia, Myeloid, Chronic-Phase|Oligonucleotide Array Sequence Analysis|Polymerase Chain Reaction|Recurrence', 'Journal Article', '10.1093/bioinformatics/bts059', '22296787', 'Selecting a small number of signature genes for accurate classification of samples is essential for the development of diagnostic tests. However, many genes are highly correlated in gene expression data, and hence, many possible sets of genes are potential classifiers. Because treatment outcomes are poor in advanced chronic myeloid leukemia (CML), we hypothesized that expression of classifiers of advanced phase CML when detected in early CML [chronic phase (CP) CML], correlates with subsequent poorer therapeutic outcome.'),
(76734, 2012, 'bio', 'WegoLoc: accurate prediction of protein subcellular localization using weighted Gene Ontology terms', 'Chi, Sang-Mun|Nam, Dougu', 'School of Computer Science and Engineering, Kyungsung University, Nam-gu, Suyoung-ro 309, Pusan, South Korea. smchiks@ks.ac.kr|School of Computer Science and Engineering, Kyungsung University, Nam-gu, Suyoung-ro 309, Pusan, South Korea. smchiks@ks.ac.kr', '-|-', 39, 'Algorithms|Amino Acids|Animals|Computational Biology|Databases, Protein|Humans|Internet|Proteins|Software|Support Vector Machine|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts062', '22296788', 'We present an accurate and fast web server, WegoLoc for predicting subcellular localization of proteins based on sequence similarity and weighted Gene Ontology (GO) information. A term weighting method in the text categorization process is applied to GO terms for a support vector machine classifier. As a result, WegoLoc surpasses the state-of-the-art methods for previously used test datasets. WegoLoc supports three eukaryotic kingdoms (animals, fungi and plants) and provides human-specific analysis, and covers several sets of cellular locations. In addition, WegoLoc provides (i) multiple possible localizations of input protein(s) as well as their corresponding probability scores, (ii) weights of GO terms representing the contribution of each GO term in the prediction, and (iii) a BLAST E-value for the best hit with GO terms. If the similarity score does not meet a given threshold, an amino acid composition-based prediction is applied as a backup method.'),
(76735, 2012, 'bio', 'A gene-based test of association using canonical correlation analysis', 'Tang, Clara S|Ferreira, Manuel A R', 'Queensland Institute of Medical Research, Brisbane, QLD 4029, Australia.|Queensland Institute of Medical Research, Brisbane, QLD 4029, Australia.', 'Australia|Australia', 40, 'Gene Frequency|Genome-Wide Association Study|Humans|Multivariate Analysis|Quantitative Trait, Heritable', 'Journal Article', '10.1093/bioinformatics/bts051', '22296789', 'Canonical correlation analysis (CCA) measures the association between two sets of multidimensional variables. We reasoned that CCA could provide an efficient and powerful approach for both univariate and multivariate gene-based tests of association without the need for permutation testing.'),
(76736, 2012, 'bio', 'Hadoop-BAM: directly manipulating next generation sequencing data in the cloud', 'Niemenmaa, Matti|Kallio, Aleksi|Schumacher, André|Klemelä, Petri|Korpelainen, Eija|Heljanko, Keijo', 'Aalto University, Department of Information and Computer Science, Aalto, Finland. matti.niemenmaa@aalto.fi|Aalto University, Department of Information and Computer Science, Aalto, Finland. matti.niemenmaa@aalto.fi|Aalto University, Department of Information and Computer Science, Aalto, Finland. matti.niemenmaa@aalto.fi|Aalto University, Department of Information and Computer Science, Aalto, Finland. matti.niemenmaa@aalto.fi|Aalto University, Department of Information and Computer Science, Aalto, Finland. matti.niemenmaa@aalto.fi|Aalto University, Department of Information and Computer Science, Aalto, Finland. matti.niemenmaa@aalto.fi', 'Finland|Finland|Finland|Finland|Finland|Finland', 0, 'Genome|High-Throughput Nucleotide Sequencing|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts054', '22302568', 'Hadoop-BAM is a novel library for the scalable manipulation of aligned next-generation sequencing data in the Hadoop distributed computing framework. It acts as an integration layer between analysis applications and BAM files that are processed using Hadoop. Hadoop-BAM solves the issues related to BAM data access by presenting a convenient API for implementing map and reduce functions that can directly operate on BAM records. It builds on top of the Picard SAM JDK, so tools that rely on the Picard API are expected to be easily convertible to support large-scale distributed processing. In this article we demonstrate the use of Hadoop-BAM by building a coverage summarizing tool for the Chipster genome browser. Our results show that Hadoop offers good scalability, and one should avoid moving data in and out of Hadoop between analysis steps.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76737, 2012, 'bio', 'ArchTEx: accurate extraction and visualization of next-generation sequence data', 'Lai, William K M|Bard, Jonathan E|Buck, Michael J', 'Department of Biochemistry, State University of New York at Buffalo, Buffalo, NY 14203, USA.|Department of Biochemistry, State University of New York at Buffalo, Buffalo, NY 14203, USA.|Department of Biochemistry, State University of New York at Buffalo, Buffalo, NY 14203, USA.', 'United States|United States|United States', 0, 'Algorithms|Computational Biology|Expressed Sequence Tags|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts063', '22302569', 'The extension of mapped sequence tags is a common step in the analysis of single-end next-generation sequencing (NGS) data from protein localization and chromatin studies. The optimal extension can vary depending on experimental and technical conditions. Improper extension of sequence tags can obscure or mislead the interpretation of NGS results. We present an algorithm, ArchTEx (Architectural Tag Extender), which identifies the optimal extension of sequence tags based on the maximum correlation between forward and reverse tags and extracts and visualizes sites of interest using the predicted extension.'),
(76738, 2014, 'bio', 'Retraction Reconstructing disease phenome-genome association by bi-random walk', '-', '-', '-', 0, '-', 'Retraction of Publication', '10.1093/bioinformatics/bts067', '22302570', '-'),
(76739, 2012, 'bio', 'Evaluating the Drosophila Bicoid morphogen gradient system through dissecting the noise in transcriptional bursts', 'He, Feng|Ren, Jie|Wang, Wei|Ma, Jun', 'Division of Biomedical Informatics, Cincinnati Childrens Research Foundation, Cincinnati, OH 45229, USA.|Division of Biomedical Informatics, Cincinnati Childrens Research Foundation, Cincinnati, OH 45229, USA.|Division of Biomedical Informatics, Cincinnati Childrens Research Foundation, Cincinnati, OH 45229, USA.|Division of Biomedical Informatics, Cincinnati Childrens Research Foundation, Cincinnati, OH 45229, USA.', 'United States|United States|United States|United States', 13, 'Animals|Computational Biology|Drosophila|Drosophila Proteins|Gene Expression Regulation, Developmental|Gene Regulatory Networks|Homeodomain Proteins|Models, Statistical|Trans-Activators|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/bts068', '22302571', 'We describe a statistical model to dissect the noise in transcriptional bursts in a developmental system.'),
(76740, 2012, 'bio', 'pymzML--Python module for high-throughput bioinformatics on mass spectrometry data', 'Bald, Till|Barth, Johannes|Niehues, Anna|Specht, Michael|Hippler, Michael|Fufezan, Christian', 'Institute of Plant Biology and Biotechnology, University of Muenster, 48143 Muenster, Germany.|Institute of Plant Biology and Biotechnology, University of Muenster, 48143 Muenster, Germany.|Institute of Plant Biology and Biotechnology, University of Muenster, 48143 Muenster, Germany.|Institute of Plant Biology and Biotechnology, University of Muenster, 48143 Muenster, Germany.|Institute of Plant Biology and Biotechnology, University of Muenster, 48143 Muenster, Germany.|Institute of Plant Biology and Biotechnology, University of Muenster, 48143 Muenster, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Computational Biology|Mass Spectrometry|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/bts066', '22302572', 'pymzML is an extension to Python that offers (i) an easy access to mass spectrometry (MS) data that allows the rapid development of tools, (ii) a very fast parser for mzML data, the standard data format in MS and (iii) a set of functions to compare or handle spectra.'),
(76741, 2012, 'bio', 'Gencrypt: one-way cryptographic hashes to detect overlapping individuals across samples', 'Turchin, Michael C|Hirschhorn, Joel N', 'Childrens Hospital Boston, Boston, MA 02115, USA.|Childrens Hospital Boston, Boston, MA 02115, USA.', 'United States|United States', 3, 'Algorithms|Confidentiality|Ethics Committees, Research|Genome-Wide Association Study|Humans|Meta-Analysis as Topic|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/bts045', '22302573', 'Meta-analysis across genome-wide association studies is a common approach for discovering genetic associations. However, in some meta-analysis efforts, individual-level data cannot be broadly shared by study investigators due to privacy and Institutional Review Board concerns. In such cases, researchers cannot confirm that each study represents a unique group of people, leading to potentially inflated test statistics and false positives. To resolve this problem, we created a software tool, Gencrypt, which utilizes a security protocol known as one-way cryptographic hashes to allow overlapping participants to be identified without sharing individual-level data.'),
(76742, 2012, 'bio', 'Breakpointer: using local mapping artifacts to support sequence breakpoint discovery from single-end reads', 'Sun, Ruping|Love, Michael I|Zemojtel, Tomasz|Emde, Anne-Katrin|Chung, Ho-Ryun|Vingron, Martin|Haas, Stefan A', 'Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. ruping@molgen.mpg.de|Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. ruping@molgen.mpg.de|Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. ruping@molgen.mpg.de|Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. ruping@molgen.mpg.de|Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. ruping@molgen.mpg.de|Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. ruping@molgen.mpg.de|Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. ruping@molgen.mpg.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 14, 'Algorithms|Artifacts|Computational Biology|Genomic Structural Variation|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts064', '22302574', 'We developed Breakpointer, a fast algorithm to locate breakpoints of structural variants (SVs) from single-end reads produced by next-generation sequencing. By taking advantage of local non-uniform read distribution and misalignments created by SVs, Breakpointer scans the alignment of single-end reads to identify regions containing potential breakpoints. The detection of such breakpoints can indicate insertions longer than the read length and SVs located in repetitve regions which might be missd by other methods. Thus, Breakpointer complements existing methods to locate SVs from single-end reads.'),
(76743, 2012, 'bio', 'Predicting kinase substrates using conservation of local motif density', 'Lai, Andy C W|Nguyen Ba, Alex N|Moses, Alan M', 'Department of Cell and Systems Biology, University of Toronto, Toronto, Canada M5S 3G5.|Department of Cell and Systems Biology, University of Toronto, Toronto, Canada M5S 3G5.|Department of Cell and Systems Biology, University of Toronto, Toronto, Canada M5S 3G5.', 'Canada|Canada|Canada', 10, 'Amino Acid Sequence|CDC28 Protein Kinase, S cerevisiae|Computational Biology|Conserved Sequence|Models, Statistical|Phosphorylation|Phosphotransferases|Protein Interaction Domains and Motifs|Sequence Alignment|Substrate Specificity', 'Journal Article', '10.1093/bioinformatics/bts060', '22302575', 'Protein kinases represent critical links in cell signaling. A central problem in computational biology is to systematically identify their substrates.'),
(76744, 2012, 'bio', 'xQTL workbench: a scalable web environment for multi-level QTL analysis', 'Arends, Danny|van der Velde, K Joeri|Prins, Pjotr|Broman, Karl W|Möller, Steffen|Jansen, Ritsert C|Swertz, Morris A', 'Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands.|Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands.|Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands.|Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands.|Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands.|Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands.|Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Chromosome Mapping|Computational Biology|Humans|Internet|Quantitative Trait Loci|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts049', '22308096', 'xQTL workbench is a scalable web platform for the mapping of quantitative trait loci (QTLs) at multiple levels: for example gene expression (eQTL), protein abundance (pQTL), metabolite abundance (mQTL) and phenotype (phQTL) data. Popular QTL mapping methods for model organism and human populations are accessible via the web user interface. Large calculations scale easily on to multi-core computers, clusters and Cloud. All data involved can be uploaded and queried online: markers, genotypes, microarrays, NGS, LC-MS, GC-MS, NMR, etc. When new data types come available, xQTL workbench is quickly customized using the Molgenis software generator.'),
(76745, 2012, 'bio', 'IDEOM: an Excel interface for analysis of LC-MS-based metabolomics data', 'Creek, Darren J|Jankevics, Andris|Burgess, Karl E V|Breitling, Rainer|Barrett, Michael P', 'Institute of Infection, Immunity and Inflammation, Wellcome Trust Centre for Molecular Parasitology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK.|Institute of Infection, Immunity and Inflammation, Wellcome Trust Centre for Molecular Parasitology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK.|Institute of Infection, Immunity and Inflammation, Wellcome Trust Centre for Molecular Parasitology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK.|Institute of Infection, Immunity and Inflammation, Wellcome Trust Centre for Molecular Parasitology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK.|Institute of Infection, Immunity and Inflammation, Wellcome Trust Centre for Molecular Parasitology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Chromatography, Liquid|Computational Biology|Databases, Factual|Mass Spectrometry|Metabolomics|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts069', '22308147', 'The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data processing, particularly noise filtering and metabolite identification. IDEOM provides a user-friendly data processing application that automates filtering and identification of metabolite peaks, paying particular attention to common sources of noise and false identifications generated by liquid chromatography-mass spectrometry (LC-MS) platforms. Building on advanced processing tools such as mzMatch and XCMS, it allows users to run a comprehensive pipeline for data analysis and visualization from a graphical user interface within Microsoft Excel, a familiar program for most biological scientists.'),
(76746, 2012, 'bio', 'Improving your target-template alignment with MODalign', 'Barbato, Alessandro|Benkert, Pascal|Schwede, Torsten|Tramontano, Anna|Kosinski, Jan', 'Department of Physics, Sapienza University P.le A. Moro, 5, 00185 Rome, Italy.|Department of Physics, Sapienza University P.le A. Moro, 5, 00185 Rome, Italy.|Department of Physics, Sapienza University P.le A. Moro, 5, 00185 Rome, Italy.|Department of Physics, Sapienza University P.le A. Moro, 5, 00185 Rome, Italy.|Department of Physics, Sapienza University P.le A. Moro, 5, 00185 Rome, Italy.', 'Italy|Italy|Italy|Italy|Italy', 11, 'Internet|Models, Molecular|Protein Structure, Secondary|Proteins|Sequence Alignment|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts070', '22308148', 'MODalign is an interactive web-based tool aimed at helping protein structure modelers to inspect and manually modify the alignment between the sequences of a target protein and of its template(s). It interactively computes, displays and, upon modification of the target-template alignment, updates the multiple sequence alignments of the two protein families, their conservation score, secondary structure and solvent accessibility values, and local quality scores of the implied three-dimensional model(s). Although it has been designed to simplify the target-template alignment step in modeling, it is suitable for all cases where a sequence alignment needs to be inspected in the context of other biological information.'),
(76747, 2012, 'bio', 'Discriminating response groups in metabolic and regulatory pathway networks', 'Van Hemert, John L|Dickerson, Julie A', 'Bioinformatics and Computational Biology, Electrical and Computer Engineering Department, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology, Electrical and Computer Engineering Department, Iowa State University, Ames, IA 50011, USA.', 'United States|United States', 0, 'Arabidopsis|Computational Biology|Escherichia coli|Gene Regulatory Networks|Metabolic Networks and Pathways|Models, Statistical|Software', 'Journal Article', '10.1093/bioinformatics/bts039', '22308149', 'Analysis of omics experiments generates lists of entities (genes, metabolites, etc.) selected based on specific behavior, such as changes in response to stress or other signals. Functional interpretation of these lists often uses category enrichment tests using functional annotations like Gene Ontology terms and pathway membership. This approach does not consider the connected structure of biochemical pathways or the causal directionality of events.'),
(76748, 2012, 'bio', 'Automatic recognition of conceptualization zones in scientific articles and two life science applications', 'Liakata, Maria|Saha, Shyamasree|Dobnik, Simon|Batchelor, Colin|Rebholz-Schuhmann, Dietrich', 'Department of Computer Science, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3DB, UK. liakata@ebi.ac.uk|Department of Computer Science, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3DB, UK. liakata@ebi.ac.uk|Department of Computer Science, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3DB, UK. liakata@ebi.ac.uk|Department of Computer Science, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3DB, UK. liakata@ebi.ac.uk|Department of Computer Science, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3DB, UK. liakata@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 79, 'Algorithms|Artificial Intelligence|Internet|Pattern Recognition, Automated|Periodicals as Topic|Software|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/bts071', '22321698', 'Scholarly biomedical publications report on the findings of a research investigation. Scientists use a well-established discourse structure to relate their work to the state of the art, express their own motivation and hypotheses and report on their methods, results and conclusions. In previous work, we have proposed ways to explicitly annotate the structure of scientific investigations in scholarly publications. Here we present the means to facilitate automatic access to the scientific discourse of articles by automating the recognition of 11 categories at the sentence level, which we call Core Scientific Concepts (CoreSCs). These include: Hypothesis, Motivation, Goal, Object, Background, Method, Experiment, Model, Observation, Result and Conclusion. CoreSCs provide the structure and context to all statements and relations within an article and their automatic recognition can greatly facilitate biomedical information extraction by characterizing the different types of facts, hypotheses and evidence available in a scientific publication.'),
(76749, 2014, 'bio', 'A novel significance score for gene selection and ranking', 'Xiao, Yufei|Hsiao, Tzu-Hung|Suresh, Uthra|Chen, Hung-I Harry|Wu, Xiaowu|Wolf, Steven E|Chen, Yidong', 'Department of Epidemiology and Biostatistics, Computational Biology and Bioinformatics Division, Greehey Childrens Cancer Research Institute, Department of Surgery, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, United States Army Institute of Surgical Research, Fort Sam Houston, TX 78234 and Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA.|Department of Epidemiology and Biostatistics, Computational Biology and Bioinformatics Division, Greehey Childrens Cancer Research Institute, Department of Surgery, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, United States Army Institute of Surgical Research, Fort Sam Houston, TX 78234 and Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA.|Department of Epidemiology and Biostatistics, Computational Biology and Bioinformatics Division, Greehey Childrens Cancer Research Institute, Department of Surgery, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, United States Army Institute of Surgical Research, Fort Sam Houston, TX 78234 and Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA.|Department of Epidemiology and Biostatistics, Computational Biology and Bioinformatics Division, Greehey Childrens Cancer Research Institute, Department of Surgery, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, United States Army Institute of Surgical Research, Fort Sam Houston, TX 78234 and Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA.|Department of Epidemiology and Biostatistics, Computational Biology and Bioinformatics Division, Greehey Childrens Cancer Research Institute, Department of Surgery, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, United States Army Institute of Surgical Research, Fort Sam Houston, TX 78234 and Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA.|Department of Epidemiology and Biostatistics, Computational Biology and Bioinformatics Division, Greehey Childrens Cancer Research Institute, Department of Surgery, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, United States Army Institute of Surgical Research, Fort Sam Houston, TX 78234 and Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA.|Department of Epidemiology and Biostatistics, Computational Biology and Bioinformatics Division, Greehey Childrens Cancer Research Institute, Department of Surgery, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, United States Army Institute of Surgical Research, Fort Sam Houston, TX 78234 and Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA.', 'United States|United States|United States|United States|United States|United States|United States', 74, 'Breast Neoplasms|Databases, Genetic|Gene Expression|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|ROC Curve|Receptors, Estrogen', 'Journal Article', '10.1093/bioinformatics/btr671', '22321699', 'When identifying differentially expressed (DE) genes from high-throughput gene expression measurements, we would like to take both statistical significance (such as P-value) and biological relevance (such as fold change) into consideration. In gene set enrichment analysis (GSEA), a score that can combine fold change and P-value together is needed for better gene ranking.'),
(76750, 2012, 'bio', 'Mytoe: automatic analysis of mitochondrial dynamics', 'Lihavainen, Eero|Mäkelä, Jarno|Spelbrink, Johannes N|Ribeiro, Andre S', 'Department of Signal Processing, Tampere University of Technology, FI-33520 Tampere, Finland. eero.lihavainen@tut.fi|Department of Signal Processing, Tampere University of Technology, FI-33520 Tampere, Finland. eero.lihavainen@tut.fi|Department of Signal Processing, Tampere University of Technology, FI-33520 Tampere, Finland. eero.lihavainen@tut.fi|Department of Signal Processing, Tampere University of Technology, FI-33520 Tampere, Finland. eero.lihavainen@tut.fi', 'Finland|Finland|Finland|Finland', 0, 'Cell Line, Tumor|Cluster Analysis|Computational Biology|Computer Graphics|Humans|Image Processing, Computer-Assisted|Microscopy, Fluorescence|Mitochondria|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts073', '22321700', 'We present Mytoe, a tool for analyzing mitochondrial morphology and dynamics from fluorescence microscope images. The tool provides automated quantitative analysis of mitochondrial motion by optical flow estimation and of morphology by segmentation of individual branches of the network-like structure of the organelles. Mytoe quantifies several features of individual branches, such as length, tortuosity and speed, and of the macroscopic structure, such as mitochondrial area and degree of clustering. We validate the methods and apply them to the analysis of sequences of images of U2OS human cells with fluorescently labeled mitochondria.'),
(76751, 2012, 'bio', 'Spliceman--a computational web server that predicts sequence variations in pre-mRNA splicing', 'Lim, Kian Huat|Fairbrother, William Guy', 'Department of Molecular Biology, Cellular Biology and Biochemistry, Brown University, Providence, RI 02903, USA.|Department of Molecular Biology, Cellular Biology and Biochemistry, Brown University, Providence, RI 02903, USA.', 'United States|United States', 0, 'Algorithms|Animals|Base Sequence|Computational Biology|Databases, Nucleic Acid|Exons|Genetic Variation|Humans|Internet|Point Mutation|RNA Precursors|RNA Splicing|ROC Curve', 'Journal Article', '10.1093/bioinformatics/bts074', '22328782', 'It was previously demonstrated that splicing elements are positional dependent. We exploited this relationship between location and function by comparing positional distributions between all possible 4096 hexamers around a database of human splice sites. The distance measure used in this study found point mutations that produced higher distances disrupted splicing, whereas point mutations with smaller distances generally had no effect on splicing. Reasoning the idea that functional splicing elements have signature positional distributions around constitutively spliced exons, we introduce Spliceman-an online tool that predicts how likely distant mutations around annotated splice sites were to disrupt splicing. Spliceman takes a set of DNA sequences with point mutations and returns a ranked list to predict the effects of point mutations on pre-mRNA splicing. The current implementation included the analyses of 11 genomes: human, chimp, rhesus, mouse, rat, dog, cat, chicken, guinea pig, frog and zebrafish.'),
(76752, 2012, 'bio', 'The identification of short linear motif-mediated interfaces within the human interactome', 'Weatheritt, R J|Luck, K|Petsalaki, E|Davey, N E|Gibson, T J', 'Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.|Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.|Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.|Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.|Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Computational Biology|Databases, Protein|Humans|Markov Chains|Protein Binding|Protein Interaction Domains and Motifs|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts072', '22328783', 'Eukaryotic proteins are highly modular, containing multiple interaction interfaces that mediate binding to a network of regulators and effectors. Recent advances in high-throughput proteomics have rapidly expanded the number of known protein-protein interactions (PPIs), however, the molecular basis for the majority of these interactions remains to be elucidated. There has been a growing appreciation of the importance of a subset of these PPIs, namely those mediated by short linear motifs (SLiMs), particularly the canonical and ubiquitous SH2, SH3 and PDZ domain-binding motifs. However, these motif classes represent only a small fraction of known SLiMs and outside these examples little effort has been made, either bioinformatically or experimentally, to discover the full complement of motif instances.'),
(76753, 2012, 'bio', 'WaVPeak: picking NMR peaks through wavelet-based smoothing and volume-based filtering', 'Liu, Zhi|Abbas, Ahmed|Jing, Bing-Yi|Gao, Xin', 'The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen 361000, China.|The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen 361000, China.|The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen 361000, China.|The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen 361000, China.', 'China|China|China|China', 39, 'Electronic Data Processing|Magnetic Resonance Spectroscopy|Proteins|Software|Wavelet Analysis', 'Journal Article', '10.1093/bioinformatics/bts078', '22328784', 'Nuclear magnetic resonance (NMR) has been widely used as a powerful tool to determine the 3D structures of proteins in vivo. However, the post-spectra processing stage of NMR structure determination usually involves a tremendous amount of time and expert knowledge, which includes peak picking, chemical shift assignment and structure calculation steps. Detecting accurate peaks from the NMR spectra is a prerequisite for all following steps, and thus remains a key problem in automatic NMR structure determination.'),
(76754, 2012, 'bio', 'Susceptibility of the human pathways graphs to fragmentation by small sets of microRNAs', 'Naamati, Guy|Friedman, Yitzhak|Balaga, Ohad|Linial, Michal', 'School of Computer Science and Engineering, Institute of Life Sciences, Sudarsky Center for Computational Biology, The Hebrew University of Jerusalem, Jerusalem 91904, Israel.|School of Computer Science and Engineering, Institute of Life Sciences, Sudarsky Center for Computational Biology, The Hebrew University of Jerusalem, Jerusalem 91904, Israel.|School of Computer Science and Engineering, Institute of Life Sciences, Sudarsky Center for Computational Biology, The Hebrew University of Jerusalem, Jerusalem 91904, Israel.|School of Computer Science and Engineering, Institute of Life Sciences, Sudarsky Center for Computational Biology, The Hebrew University of Jerusalem, Jerusalem 91904, Israel.', 'Israel|Israel|Israel|Israel', 4, 'Algorithms|Computational Biology|Gene Expression|Gene Regulatory Networks|Humans|MicroRNAs|RNA, Messenger', 'Journal Article', '10.1093/bioinformatics/bts077', '22328785', 'MicroRNAs (miRNAs) are short sequences that negatively regulate gene expression. The current understanding of miRNA and their corresponding mRNA targets is primarily based on prediction programs. This study addresses the potential of a coordinated action of miRNAs to manipulate the human pathways. Specifically, we investigate the effectiveness of disrupting the topology of human pathway graphs through a regulation by miRNAs.'),
(76755, 2012, 'bio', 'Positional correlation analysis improves reconstruction of full-length transcripts and alternative isoforms from noisy array signals or short reads', 'Kawaguchi, Shuji|Iida, Kei|Harada, Erimi|Hanada, Kousuke|Matsui, Akihiro|Okamoto, Masanori|Shinozaki, Kazuo|Seki, Motoaki|Toyoda, Tetsuro', 'Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Algorithms|Computational Biology|Gene Expression Profiling|Logistic Models|Markov Chains|Protein Isoforms|RNA, Messenger|Sequence Analysis, DNA|Transcriptome', 'Journal Article', '10.1093/bioinformatics/bts065', '22332235', 'A reconstruction of full-length transcripts observed by next-generation sequencer or tiling arrays is an essential technique to know all phenomena of transcriptomes. Several techniques of the reconstruction have been developed. However, problems of high-level noises and biases still remain and interrupt the reconstruction. A method is required that is robust against noise and bias and correctly reconstructs transcripts regardless of equipment used.'),
(76756, 2012, 'bio', 'Toward community standards in the quest for orthologs', 'Dessimoz, Christophe|Gabaldón, Toni|Roos, David S|Sonnhammer, Erik L L|Herrero, Javier|Quest for Orthologs Consortium', 'Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics and Systems Engineering division, RIKEN Yokohama Institute, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Animals|Evolution, Molecular|Genes|Genomics|Humans|Models, Genetic', 'Congress', '10.1093/bioinformatics/bts050', '22332236', 'The identification of orthologs-genes pairs descended from a common ancestor through speciation, rather than duplication-has emerged as an essential component of many bioinformatics applications, ranging from the annotation of new genomes to experimental target prioritization. Yet, the development and application of orthology inference methods is hampered by the lack of consensus on source proteomes, file formats and benchmarks. The second Quest for Orthologs meeting brought together stakeholders from various communities to address these challenges. We report on achievements and outcomes of this meeting, focusing on topics of particular relevance to the research community at large. The Quest for Orthologs consortium is an open community that welcomes contributions from all researchers interested in orthology research and applications.'),
(76757, 2012, 'bio', 'Phylogenomic analysis of bacterial and archaeal sequences with AMPHORA2', 'Wu, Martin|Scott, Alexandra J', 'Department of Biology, University of Virginia, Charlottesville, VA 22904, USA. mw4yv@virginia.edu|Department of Biology, University of Virginia, Charlottesville, VA 22904, USA. mw4yv@virginia.edu', 'United States|United States', 225, 'Algorithms|Archaea|Bacteria|Computational Biology|Genome, Archaeal|Genome, Bacterial|Genomics|Metagenome|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/bts079', '22332237', 'With the explosive growth of bacterial and archaeal sequence data, large-scale phylogenetic analyses present both opportunities and challenges. Here we describe AMPHORA2, an automated phylogenomic inference tool that can be used for high-throughput, high-quality genome tree reconstruction and metagenomic phylotyping. Compared with its predecessor, AMPHORA2 has several major enhancements and new functions: it has a greatly expanded phylogenetic marker database and can analyze both bacterial and archaeal sequences, it incorporates probability-based sequence alignment masks that improve the phylogenetic accuracy, it can analyze DNA as well as protein sequences and is more sensitive in marker identification, finally, it is over 100× faster in metagenomic phylotyping.'),
(76758, 2012, 'bio', 'Biogem: an effective tool-based approach for scaling up open source software development in bioinformatics', 'Bonnal, Raoul J P|Aerts, Jan|Githinji, George|Goto, Naohisa|MacLean, Dan|Miller, Chase A|Mishima, Hiroyuki|Pagani, Massimiliano|Ramirez-Gonzalez, Ricardo|Smant, Geert|Strozzi, Francesco|Syme, Rob|Vos, Rutger|Wennblom, Trevor J|Woodcroft, Ben J|Katayama, Toshiaki|Prins, Pjotr', 'Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org|Integrative Biology Program, Istituto Nazionale Genetica Molecolare, Milan 20122, Italy. bonnal@ingm.org', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Ital', 23, 'Computational Biology|Internet|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/bts080', '22332238', 'Biogem provides a software development environment for the Ruby programming language, which encourages community-based software development for bioinformatics while lowering the barrier to entry and encouraging best practices. Biogem, with its targeted modular and decentralized approach, software generator, tools and tight web integration, is an improved general model for scaling up collaborative open source software development in bioinformatics.'),
(76759, 2012, 'bio', 'SBAL: a practical tool to generate and edit structure-based amino acid sequence alignments', 'Wang, Conan K|Broder, Ursula|Weeratunga, Saroja K|Gasser, Robin B|Loukas, Alex|Hofmann, Andreas', 'Structural Chemistry Program, Eskitis Institute for Cell and Molecular Therapies, Griffith University, Brisbane, Qld 4111, Australia. conan.wang@griffith.edu.au|Structural Chemistry Program, Eskitis Institute for Cell and Molecular Therapies, Griffith University, Brisbane, Qld 4111, Australia. conan.wang@griffith.edu.au|Structural Chemistry Program, Eskitis Institute for Cell and Molecular Therapies, Griffith University, Brisbane, Qld 4111, Australia. conan.wang@griffith.edu.au|Structural Chemistry Program, Eskitis Institute for Cell and Molecular Therapies, Griffith University, Brisbane, Qld 4111, Australia. conan.wang@griffith.edu.au|Structural Chemistry Program, Eskitis Institute for Cell and Molecular Therapies, Griffith University, Brisbane, Qld 4111, Australia. conan.wang@griffith.edu.au|Structural Chemistry Program, Eskitis Institute for Cell and Molecular Therapies, Griffith University, Brisbane, Qld 4111, Australia. conan.wang@griffith.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia', 18, 'Algorithms|Amino Acid Sequence|Computational Biology|Protein Structure, Secondary|Sequence Alignment|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts035', '22332239', 'Both alignment generation and visualization are important processes for producing biologically meaningful sequence alignments. Computational tools that combine reliable, automated and semi-automated approaches to produce secondary structure-based alignments with an appropriate visualization of the results are rare. We have developed SBAL, a tool to generate and edit secondary structure-based sequence alignments. It is easy to install and provides a user-friendly interface. Sequence alignments are displayed, with secondary structure assignments mapped to their corresponding regions in the sequence by using a simple colour scheme. The algorithm implemented for automated and semi-automated secondary structure-based alignment calculations shows a comparable performance to existing software.'),
(76760, 2012, 'bio', 'ShapePheno: unsupervised extraction of shape phenotypes from biological image collections', 'Karaletsos, Theofanis|Stegle, Oliver|Dreyer, Christine|Winn, John|Borgwardt, Karsten M', 'Machine Learning and Computational Biology Research Group, Max Planck Institute for Intelligent Systems and Max Planck Institute for Developmental Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany. theofanis.karaletsos@tuebingen.mpg.de|Machine Learning and Computational Biology Research Group, Max Planck Institute for Intelligent Systems and Max Planck Institute for Developmental Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany. theofanis.karaletsos@tuebingen.mpg.de|Machine Learning and Computational Biology Research Group, Max Planck Institute for Intelligent Systems and Max Planck Institute for Developmental Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany. theofanis.karaletsos@tuebingen.mpg.de|Machine Learning and Computational Biology Research Group, Max Planck Institute for Intelligent Systems and Max Planck Institute for Developmental Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany. theofanis.karaletsos@tuebingen.mpg.de|Machine Learning and Computational Biology Research Group, Max Planck Institute for Intelligent Systems and Max Planck Institute for Developmental Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany. theofanis.karaletsos@tuebingen.mpg.de', 'Germany|Germany|Germany|Germany|Germany', 4, 'Animals|Artificial Intelligence|Cluster Analysis|Computational Biology|Image Processing, Computer-Assisted|Male|Markov Chains|Models, Statistical|Pattern Recognition, Automated|Phenotype|Poecilia', 'Journal Article', '10.1093/bioinformatics/bts081', '22333244', 'Accurate large-scale phenotyping has recently gained considerable importance in biology. For example, in genome-wide association studies technological advances have rendered genotyping cheap, leaving phenotype acquisition as the major bottleneck. Automatic image analysis is one major strategy to phenotype individuals in large numbers. Current approaches for visual phenotyping focus predominantly on summarizing statistics and geometric measures, such as height and width of an individual, or color histograms and patterns. However, more subtle, but biologically informative phenotypes, such as the local deformation of the shape of an individual with respect to the population mean cannot be automatically extracted and quantified by current techniques.'),
(76761, 2012, 'bio', 'A method of finding optimal weight factors for compound identification in gas chromatography-mass spectrometry', 'Kim, Seongho|Koo, Imhoi|Wei, Xiaoli|Zhang, Xiang', 'Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA. s0kim023@louisville.edu|Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA. s0kim023@louisville.edu|Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA. s0kim023@louisville.edu|Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA. s0kim023@louisville.edu', 'United States|United States|United States|United States', 40, 'Gas Chromatography-Mass Spectrometry|Reference Standards|Software', 'Journal Article', '10.1093/bioinformatics/bts083', '22333245', 'The compound identification in gas chromatography-mass spectrometry (GC-MS) is achieved by matching the experimental mass spectrum to the mass spectra in a spectral library. It is known that the intensities with higher m/z value in the GC-MS mass spectrum are the most diagnostic. Therefore, to increase the relative significance of peak intensities of higher m/z value, the intensities and m/z values are usually transformed with a set of weight factors. A poor quality of weight factors can significantly decrease the accuracy of compound identification. With the significant enrichment of the mass spectral database and the broad application of GC-MS, it is important to re-visit the methods of discovering the optimal weight factors for high confident compound identification.'),
(76762, 2012, 'bio', 'Estimating population diversity with CatchAll', 'Bunge, John|Woodard, Linda|Böhning, Dankmar|Foster, James A|Connolly, Sean|Allen, Heather K', 'Department of Statistical Science, Cornell University, Ithaca, NY 14853, USA. jab18@cornell.edu|Department of Statistical Science, Cornell University, Ithaca, NY 14853, USA. jab18@cornell.edu|Department of Statistical Science, Cornell University, Ithaca, NY 14853, USA. jab18@cornell.edu|Department of Statistical Science, Cornell University, Ithaca, NY 14853, USA. jab18@cornell.edu|Department of Statistical Science, Cornell University, Ithaca, NY 14853, USA. jab18@cornell.edu|Department of Statistical Science, Cornell University, Ithaca, NY 14853, USA. jab18@cornell.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Bacteriophages|Computational Biology|Genetics, Population|Likelihood Functions|Linear Models|Models, Statistical|Software', 'Journal Article', '10.1093/bioinformatics/bts075', '22333246', 'The massive data produced by next-generation sequencing require advanced statistical tools. We address estimating the total diversity or species richness in a population. To date, only relatively simple methods have been implemented in available software. There is a need for software employing modern, computationally intensive statistical analyses including error, goodness-of-fit and robustness assessments.'),
(76763, 2012, 'bio', 'MotEvo: integrated Bayesian probabilistic methods for inferring regulatory sites and motifs on multiple alignments of DNA sequences', 'Arnold, Phil|Erb, Ionas|Pachkov, Mikhail|Molina, Nacho|van Nimwegen, Erik', 'Biozentrum, University of Basel, Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum, University of Basel, Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum, University of Basel, Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum, University of Basel, Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum, University of Basel, Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Animals|Base Sequence|Bayes Theorem|Binding Sites|Enhancer Elements, Genetic|Humans|Phylogeny|Protein Binding|Sequence Alignment|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btr695', '22334039', 'Probabilistic approaches for inferring transcription factor binding sites (TFBSs) and regulatory motifs from DNA sequences have been developed for over two decades. Previous work has shown that prediction accuracy can be significantly improved by incorporating features such as the competition of multiple transcription factors (TFs) for binding to nearby sites, the tendency of TFBSs for co-regulated TFs to cluster and form cis-regulatory modules and explicit evolutionary modeling of conservation of TFBSs across orthologous sequences. However, currently available tools only incorporate some of these features, and significant methodological hurdles hampered their synthesis into a single consistent probabilistic framework.'),
(76764, 2012, 'bio', 'CytoSaddleSum: a functional enrichment analysis plugin for Cytoscape based on sum-of-weights scores', 'Stojmirovic, Aleksandar|Bliskovsky, Alexander|Yu, Yi-Kuo', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.', 'United States|United States|United States', 0, 'Gene Deletion|Genes|National Library of Medicine (U.S.)|Software|United States', 'Journal Article', '10.1093/bioinformatics/bts041', '22345616', 'CytoSaddleSum provides Cytoscape users with access to the functionality of SaddleSum, a functional enrichment tool based on sum-of-weight scores. It operates by querying SaddleSum locally (using the standalone version) or remotely (through an HTTP request to a web server). The functional enrichment results are shown as a term relationship network, where nodes represent terms and edges show term relationships. Furthermore, query results are written as Cytoscape attributes allowing easy saving, retrieval and integration into network-based data analysis workflows.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76765, 2012, 'bio', 'DOMIRE: a web server for identifying structural domains and their neighbors in proteins', 'Samson, Franck|Shrager, Richard|Tai, Chin-Hsien|Sam, Vichetra|Lee, Byungkook|Munson, Peter J|Gibrat, Jean-François|Garnier, Jean', 'Institut National de la Recherche Agronomique, UR1077, Unité Mathématique, Informatique et Génome, 78350 Jouy-en-Josas, France.|Institut National de la Recherche Agronomique, UR1077, Unité Mathématique, Informatique et Génome, 78350 Jouy-en-Josas, France.|Institut National de la Recherche Agronomique, UR1077, Unité Mathématique, Informatique et Génome, 78350 Jouy-en-Josas, France.|Institut National de la Recherche Agronomique, UR1077, Unité Mathématique, Informatique et Génome, 78350 Jouy-en-Josas, France.|Institut National de la Recherche Agronomique, UR1077, Unité Mathématique, Informatique et Génome, 78350 Jouy-en-Josas, France.|Institut National de la Recherche Agronomique, UR1077, Unité Mathématique, Informatique et Génome, 78350 Jouy-en-Josas, France.|Institut National de la Recherche Agronomique, UR1077, Unité Mathématique, Informatique et Génome, 78350 Jouy-en-Josas, France.|Institut National de la Recherche Agronomique, UR1077, Unité Mathématique, Informatique et Génome, 78350 Jouy-en-Josas, France.', 'France|France|France|France|France|France|France|France', 2, 'Algorithms|Databases, Protein|Internet|Protein Structure, Tertiary|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/bts076', '22345617', 'The DOMIRE web server implements a novel, automatic, protein structural domain assignment procedure based on 3D substructures of the query protein which are also found within structures of a non-redundant protein database. These common 3D substructures are transformed into a co-occurrence matrix that offers a global view of the protein domain organization. Three different algorithms are employed to define structural domain boundaries from this co-occurrence matrix. For each query, a list of structural neighbors and their alignments are provided. DOMIRE, by displaying the protein structural domain organization, can be a useful tool for defining protein common cores and for unravelling the evolutionary relationship between different proteins.'),
(76766, 2012, 'bio', 'GMD: measuring the distance between histograms with applications on high-throughput sequencing reads', 'Zhao, Xiaobei|Sandelin, Albin', 'Bioinformatics Centre, Department of Biology and Biotech Research and Innovation Centre, Copenhagen University, Copenhagen, Denmark. xiaobei@binf.ku.dk|Bioinformatics Centre, Department of Biology and Biotech Research and Innovation Centre, Copenhagen University, Copenhagen, Denmark. xiaobei@binf.ku.dk', 'Denmark|Denmark', 13, 'Chromatin Immunoprecipitation|High-Throughput Nucleotide Sequencing|Histone Code|Histones|Sequence Analysis, DNA|Sequence Analysis, RNA|Software|Transcription Initiation Site', 'Journal Article', '10.1093/bioinformatics/bts087', '22345619', 'GMD (generalized minimum distance of distributions) is an R package to assess the similarity between spatial distributions of read-based sequencing data such as ChIP-seq and RNA-seq. GMD calculates the optimal distance between pairs of normalized signal distributions, optionally sliding one distribution over the other to align the distributions. GMD also provides graphical and downstream clustering tools.'),
(76767, 2012, 'bio', 'PERMORY-MPI: a program for high-speed parallel permutation testing in genome-wide association studies', 'Steiß, Volker|Letschert, Thomas|Schäfer, Helmut|Pahl, Roman', 'Institute of Medical Biometry and Epidemiology, Philipps-Universität Marburg, Marburg, Germany. volker.steiss@mni.thm.de|Institute of Medical Biometry and Epidemiology, Philipps-Universität Marburg, Marburg, Germany. volker.steiss@mni.thm.de|Institute of Medical Biometry and Epidemiology, Philipps-Universität Marburg, Marburg, Germany. volker.steiss@mni.thm.de|Institute of Medical Biometry and Epidemiology, Philipps-Universität Marburg, Marburg, Germany. volker.steiss@mni.thm.de', 'Germany|Germany|Germany|Germany', 0, 'Case-Control Studies|Genome-Wide Association Study|Humans|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/bts086', '22345620', 'PERMORY is software for accelerated permutation testing of genome-wide association studies (GWAS). We have parallelized PERMORY using the Message-Passing Interface resulting in a nearly linear speedup. Furthermore, we added accelerated analysis of GWAS using quantitative phenotypes, and an accurate estimation of the effective number of independent tests.'),
(76768, 2012, 'bio', 'RNA-Seq Atlas--a reference database for gene expression profiling in normal tissue by next-generation sequencing', 'Krupp, Markus|Marquardt, Jens U|Sahin, Ugur|Galle, Peter R|Castle, John|Teufel, Andreas', 'Department of Medicine I, Johannes Gutenberg University, 55131 Mainz, Germany. kruppm@uni-mainz.de|Department of Medicine I, Johannes Gutenberg University, 55131 Mainz, Germany. kruppm@uni-mainz.de|Department of Medicine I, Johannes Gutenberg University, 55131 Mainz, Germany. kruppm@uni-mainz.de|Department of Medicine I, Johannes Gutenberg University, 55131 Mainz, Germany. kruppm@uni-mainz.de|Department of Medicine I, Johannes Gutenberg University, 55131 Mainz, Germany. kruppm@uni-mainz.de|Department of Medicine I, Johannes Gutenberg University, 55131 Mainz, Germany. kruppm@uni-mainz.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 120, 'Databases, Nucleic Acid|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Internet|Neoplasms|Oligonucleotide Array Sequence Analysis|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts084', '22345621', 'Next-generation sequencing technology enables an entirely new perspective for clinical research and will speed up personalized medicine. In contrast to microarray-based approaches, RNA-Seq analysis provides a much more comprehensive and unbiased view of gene expression. Although the perspective is clear and the long-term success of this new technology obvious, bioinformatics resources making these data easily available especially to the biomedical research community are still evolving.'),
(76769, 2012, 'bio', 'Signal analysis for genome-wide maps of histone modifications measured by ChIP-seq', 'Beck, Dominik|Brandl, Miriam B|Boelen, Lies|Unnikrishnan, Ashwin|Pimanda, John E|Wong, Jason W H', 'Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, NSW 2052, Australia. d.beck@student.unsw.edu.au|Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, NSW 2052, Australia. d.beck@student.unsw.edu.au|Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, NSW 2052, Australia. d.beck@student.unsw.edu.au|Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, NSW 2052, Australia. d.beck@student.unsw.edu.au|Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, NSW 2052, Australia. d.beck@student.unsw.edu.au|Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, NSW 2052, Australia. d.beck@student.unsw.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia', 7, 'Animals|Chromatin Immunoprecipitation|Genome-Wide Association Study|High-Throughput Nucleotide Sequencing|Histone Code|Histones|Humans|Linear Models|Protein Processing, Post-Translational|Sequence Analysis, DNA|Signal-To-Noise Ratio|Speech Recognition Software', 'Journal Article', '10.1093/bioinformatics/bts085', '22345622', 'Chromatin structure, including post-translational modifications of histones, regulates gene expression, alternative splicing and cell identity. ChIP-seq is an increasingly used assay to study chromatin function. However, tools for downstream bioinformatics analysis are limited and are only based on the evaluation of signal intensities. We reasoned that new methods taking into account other signal characteristics such as peak shape, location and frequencies might reveal new insights into chromatin function, particularly in situation where differences in read intensities are subtle.'),
(76770, 2012, 'bio', 'An integrated strategy for prediction uncertainty analysis', 'Vanlier, J|Tiemann, C A|Hilbers, P A J|van Riel, N A W', 'Department of BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. j.vanlier@tue.nl|Department of BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. j.vanlier@tue.nl|Department of BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. j.vanlier@tue.nl|Department of BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. j.vanlier@tue.nl', 'Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Bayes Theorem|Janus Kinase 1|Likelihood Functions|Markov Chains|Models, Biological|Programming Languages|STAT Transcription Factors|Signal Transduction|Systems Biology|Uncertainty', 'Journal Article', '10.1093/bioinformatics/bts088', '22355081', 'To further our understanding of the mechanisms underlying biochemical pathways mathematical modelling is used. Since many parameter values are unknown they need to be estimated using experimental observations. The complexity of models necessary to describe biological pathways in combination with the limited amount of quantitative data results in large parameter uncertainty which propagates into model predictions. Therefore prediction uncertainty analysis is an important topic that needs to be addressed in Systems Biology modelling.'),
(76771, 2012, 'bio', 'Allele-specific expression analysis methods for high-density SNP microarray data', 'Liu, Ruijie|Maia, Ana-Teresa|Russell, Roslin|Caldas, Carlos|Ponder, Bruce A|Ritchie, Matthew E', 'Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia.|Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia.|Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia.|Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia.|Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia.|Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia', 6, 'Alleles|Genome-Wide Association Study|Genomic Imprinting|Humans|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/bts089', '22355082', 'In the past decade, a number of technologies to quantify allele-specific expression (ASE) in a genome-wide manner have become available to researchers. We investigate the application of single-nucleotide polymorphism (SNP) microarrays to this task, exploring data obtained from both cell lines and primary tissue for which both RNA and DNA profiles are available.'),
(76772, 2012, 'bio', 'Causal reasoning on biological networks: interpreting transcriptional changes', 'Chindelevitch, Leonid|Ziemek, Daniel|Enayetallah, Ahmed|Randhawa, Ranjit|Sidders, Ben|Brockel, Christoph|Huang, Enoch S', 'Computational Sciences Center of Emphasis, Pfizer Worldwide Research & Development, Cambridge, MA 02140, USA.|Computational Sciences Center of Emphasis, Pfizer Worldwide Research & Development, Cambridge, MA 02140, USA.|Computational Sciences Center of Emphasis, Pfizer Worldwide Research & Development, Cambridge, MA 02140, USA.|Computational Sciences Center of Emphasis, Pfizer Worldwide Research & Development, Cambridge, MA 02140, USA.|Computational Sciences Center of Emphasis, Pfizer Worldwide Research & Development, Cambridge, MA 02140, USA.|Computational Sciences Center of Emphasis, Pfizer Worldwide Research & Development, Cambridge, MA 02140, USA.|Computational Sciences Center of Emphasis, Pfizer Worldwide Research & Development, Cambridge, MA 02140, USA.', 'United States|United States|United States|United States|United States|United States|United States', 82, 'Algorithms|Breast Neoplasms|Cardiomegaly|Computational Biology|Gene Expression Profiling|Humans|Models, Biological', 'Journal Article', '10.1093/bioinformatics/bts090', '22355083', 'The interpretation of high-throughput datasets has remained one of the central challenges of computational biology over the past decade. Furthermore, as the amount of biological knowledge increases, it becomes more and more difficult to integrate this large body of knowledge in a meaningful manner. In this article, we propose a particular solution to both of these challenges.'),
(76773, 2012, 'bio', 'Oases: robust de novo RNA-seq assembly across the dynamic range of expression levels', 'Schulz, Marcel H|Zerbino, Daniel R|Vingron, Martin|Birney, Ewan', 'Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany.|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany.|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany.|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany.', 'Germany|Germany|Germany|Germany', 907, 'Algorithms|Alternative Splicing|Animals|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Mice|RNA, Messenger|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts094', '22368243', 'High-throughput sequencing has made the analysis of new model organisms more affordable. Although assembling a new genome can still be costly and difficult, it is possible to use RNA-seq to sequence mRNA. In the absence of a known genome, it is necessary to assemble these sequences de novo, taking into account possible alternative isoforms and the dynamic range of expression values.'),
(76774, 2012, 'bio', 'A new statistical approach to detecting differentially methylated loci for case control Illumina array methylation data', 'Chen, Zhongxue|Liu, Qingzhong|Nadarajah, Saralees', 'Center for Clinical and Translational Sciences, University of Texas Health Science Center at Houston, Houston, Texas 77030, USA. Zhongxue.Chen@uth.tmc.edu|Center for Clinical and Translational Sciences, University of Texas Health Science Center at Houston, Houston, Texas 77030, USA. Zhongxue.Chen@uth.tmc.edu|Center for Clinical and Translational Sciences, University of Texas Health Science Center at Houston, Houston, Texas 77030, USA. Zhongxue.Chen@uth.tmc.edu', 'United States|United States|United States', 22, 'Aged|Aged, 80 and over|Case-Control Studies|Computer Simulation|DNA Methylation|Female|Humans|Middle Aged|Models, Statistical|Oligonucleotide Array Sequence Analysis|Ovarian Neoplasms', 'Journal Article', '10.1093/bioinformatics/bts093', '22368244', 'As an epigenetic alteration, DNA methylation plays an important role in epigenetic controls of gene transcription. Recent advances in genome-wide scan of DNA methylation provide great opportunities in studying the impact of DNA methylation on many human diseases including various types of cancer. Due to the unique feature of this type of data, applicable statistical methods are limited and new sophisticated approaches are desirable.'),
(76775, 2012, 'bio', 'A Bayesian approach to targeted experiment design', 'Vanlier, J|Tiemann, C A|Hilbers, P A J|van Riel, N A W', 'Department of BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. j.vanlier@tue.nl|Department of BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. j.vanlier@tue.nl|Department of BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. j.vanlier@tue.nl|Department of BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. j.vanlier@tue.nl', 'Netherlands|Netherlands|Netherlands|Netherlands', 54, 'Algorithms|Bayes Theorem|Janus Kinases|Monte Carlo Method|Programming Languages|Research Design|STAT Transcription Factors|Signal Transduction|Systems Biology|Uncertainty', 'Journal Article', '10.1093/bioinformatics/bts092', '22368245', 'Systems biology employs mathematical modelling to further our understanding of biochemical pathways. Since the amount of experimental data on which the models are parameterized is often limited, these models exhibit large uncertainty in both parameters and predictions. Statistical methods can be used to select experiments that will reduce such uncertainty in an optimal manner. However, existing methods for optimal experiment design (OED) rely on assumptions that are inappropriate when data are scarce considering model complexity.'),
(76776, 2012, 'bio', 'R/DWD: distance-weighted discrimination for classification, visualization and batch adjustment', 'Huang, Hanwen|Lu, Xiaosun|Liu, Yufeng|Haaland, Perry|Marron, J S', 'Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. hanwen.huang@uth.tmc.edu|Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. hanwen.huang@uth.tmc.edu|Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. hanwen.huang@uth.tmc.edu|Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. hanwen.huang@uth.tmc.edu|Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. hanwen.huang@uth.tmc.edu', 'United States|United States|United States|United States|United States', 28, 'Computational Biology|Computer Simulation|Oligonucleotide Array Sequence Analysis|Software|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/bts096', '22368246', 'R/DWD is an extensible package for classification. It is built based on a recently developed powerful classification method called distance weighted discrimination (DWD). DWD is related to, and has been shown to be superior to, the support vector machine in situations that are fundamental to bioinformatics, such as very high dimensional data. DWD has proven to be very useful for several fundamental bioinformatics tasks, including classification, data visualization and removal of biases, such as batch effects. Earlier DWD implementations, however, relied on Matlab, which is not free and requires a license. The major contribution of the R/DWD package is an implementation that is completely in R and thus can be used without any requirements for licensing or software purchase. In addition, R/DWD also provides efficient solvers for second-order-cone-programming and quadratic programming.'),
(76777, 2012, 'bio', 'SiteComp: a server for ligand binding site analysis in protein structures', 'Lin, Yingjie|Yoo, Seungyeul|Sanchez, Roberto', 'Department of Structural and Chemical Biology, Mount Sinai School of Medicine, New York, NY 10029, USA.|Department of Structural and Chemical Biology, Mount Sinai School of Medicine, New York, NY 10029, USA.|Department of Structural and Chemical Biology, Mount Sinai School of Medicine, New York, NY 10029, USA.', 'United States|United States|United States', 24, 'Binding Sites|Computers|Ligands|Models, Molecular|Prostaglandin-Endoperoxide Synthases|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts095', '22368247', 'Computational characterization of ligand-binding sites in proteins provides preliminary information for functional annotation, protein design and ligand optimization. SiteComp implements binding site analysis for comparison of binding sites, evaluation of residue contribution to binding sites and identification of sub-sites with distinct molecular interaction properties.'),
(76778, 2012, 'bio', 'Unipro UGENE: a unified bioinformatics toolkit', 'Okonechnikov, Konstantin|Golosova, Olga|Fursov, Mikhail|UGENE team', 'Unipro Center for Information Technologies, Novosibirsk, Russia. ugene@unipro.ru|Unipro Center for Information Technologies, Novosibirsk, Russia. ugene@unipro.ru|Unipro Center for Information Technologies, Novosibirsk, Russia. ugene@unipro.ru|Unipro Center for Information Technologies, Novosibirsk, Russia. ugene@unipro.ru', '-|-|-|-', 783, 'Algorithms|Computational Biology|Computing Methodologies|High-Throughput Nucleotide Sequencing|Molecular Sequence Annotation|Phylogeny|Sequence Alignment|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/bts091', '22368248', 'Unipro UGENE is a multiplatform open-source software with the main goal of assisting molecular biologists without much expertise in bioinformatics to manage, analyze and visualize their data. UGENE integrates widely used bioinformatics tools within a common user interface. The toolkit supports multiple biological data formats and allows the retrieval of data from remote data sources. It provides visualization modules for biological objects such as annotated genome sequences, Next Generation Sequencing (NGS) assembly data, multiple sequence alignments, phylogenetic trees and 3D structures. Most of the integrated algorithms are tuned for maximum performance by the usage of multithreading and special processor instructions. UGENE includes a visual environment for creating reusable workflows that can be launched on local resources or in a High Performance Computing (HPC) environment. UGENE is written in C++ using the Qt framework. The built-in plugin system and structured UGENE API make it possible to extend the toolkit with new functionality.'),
(76779, 2012, 'bio', 'SED-ED, a workflow editor for computational biology experiments written in SED-ML', 'Adams, Richard R', 'SynthSys Edinburgh, University of Edinburgh, Edinburgh, UK. richard.adams@ed.ac.uk', 'United Kingdom', 8, 'Computational Biology|Humans|Models, Biological|Programming Languages|Software|Systems Biology|User-Computer Interface|Workflow', 'Journal Article', '10.1093/bioinformatics/bts101', '22368254', 'The simulation experiment description markup language (SED-ML) is a new community data standard to encode computational biology experiments in a computer-readable XML format. Its widespread adoption will require the development of software support to work with SED-ML files. Here, we describe a software tool, SED-ED, to view, edit, validate and annotate SED-ML documents while shielding end-users from the underlying XML representation. SED-ED supports modellers who wish to create, understand and further develop a simulation description provided in SED-ML format.'),
(76780, 2012, 'bio', 'High-quality sequence clustering guided by network topology and multiple alignment likelihood', 'Miele, Vincent|Penel, Simon|Daubin, Vincent|Picard, Franck|Kahn, Daniel|Duret, Laurent', 'Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France. vincent.miele@univ-lyon1.fr|Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France. vincent.miele@univ-lyon1.fr|Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France. vincent.miele@univ-lyon1.fr|Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France. vincent.miele@univ-lyon1.fr|Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France. vincent.miele@univ-lyon1.fr|Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France. vincent.miele@univ-lyon1.fr', 'France|France|France|France|France|France', 21, 'Algorithms|Amino Acid Sequence|Cluster Analysis|Phylogeny|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/bts098', '22368255', 'Proteins can be naturally classified into families of homologous sequences that derive from a common ancestor. The comparison of homologous sequences and the analysis of their phylogenetic relationships provide useful information regarding the function and evolution of genes. One important difficulty of clustering methods is to distinguish highly divergent homologous sequences from sequences that only share partial homology due to evolution by protein domain rearrangements. Existing clustering methods require parameters that have to be set a priori. Given the variability in the evolution pattern among proteins, these parameters cannot be optimal for all gene families.'),
(76781, 2012, 'bio', 'Rchange: algorithms for computing energy changes of RNA secondary structures in response to base mutations', 'Kiryu, Hisanori|Asai, Kiyoshi', 'Department of Computational Biology, Faculty of Frontier Science, The University of Tokyo, Kashiwa, Chiba, Japan. kiryu-h@k.u-tokyo.ac.jp|Department of Computational Biology, Faculty of Frontier Science, The University of Tokyo, Kashiwa, Chiba, Japan. kiryu-h@k.u-tokyo.ac.jp', 'Japan|Japan', 10, 'Algorithms|Anticodon|Base Composition|Nucleic Acid Conformation|Point Mutation|RNA|RNA, Transfer|Software|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/bts097', '22373787', 'Measuring the effects of base mutations is a powerful tool for functional and evolutionary analyses of RNA structures. To date, only a few methods have been developed for systematically computing the thermodynamic changes of RNA secondary structures in response to base mutations.'),
(76782, 2012, 'bio', 'Rapid identification of non-human sequences in high-throughput sequencing datasets', 'Bhaduri, Aparna|Qu, Kun|Lee, Carolyn S|Ungewickell, Alexander|Khavari, Paul A', 'Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA 94304, USA. abhaduri@stanford.edu|Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA 94304, USA. abhaduri@stanford.edu|Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA 94304, USA. abhaduri@stanford.edu|Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA 94304, USA. abhaduri@stanford.edu|Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA 94304, USA. abhaduri@stanford.edu', 'United States|United States|United States|United States|United States', 55, 'Genome|Genome, Human|High-Throughput Nucleotide Sequencing|Host-Pathogen Interactions|Humans|Sequence Analysis, DNA|Software|Viruses', 'Journal Article', '10.1093/bioinformatics/bts100', '22377895', 'Rapid identification of non-human sequences (RINS) is an intersection-based pathogen detection workflow that utilizes a user-provided custom reference genome set for identification of non-human sequences in deep sequencing datasets. In <2 h, RINS correctly identified the known virus in the dataset SRR73726 and is compatible with any computer capable of running the prerequisite alignment and assembly programs. RINS accurately identifies sequencing reads from intact or mutated non-human genomes in a dataset and robustly generates contigs with these non-human sequences (Supplementary Material).'),
(76783, 2012, 'bio', 'StochSens--Matlab package for sensitivity analysis of stochastic chemical systems', 'Komorowski, Michal|Zurauskiene, Justina|Stumpf, Michael P H', 'Division of Molecular Biosciences, Imperial College London, London, UK. mkomor@ippt.gov.pl|Division of Molecular Biosciences, Imperial College London, London, UK. mkomor@ippt.gov.pl|Division of Molecular Biosciences, Imperial College London, London, UK. mkomor@ippt.gov.pl', 'United Kingdom|United Kingdom|United Kingdom', 15, 'Algorithms|Enzymes|Gene Expression|Kinetics|Models, Statistical|Software', 'Journal Article', '10.1093/bioinformatics/btr714', '22378710', 'The growing interest in the role of stochasticity in biochemical systems drives the demand for tools to analyse stochastic dynamical models of chemical reactions. One powerful tool to elucidate performance of dynamical systems is sensitivity analysis. Traditionally, however, the concept of sensitivity has mainly been applied to deterministic systems, and the difficulty to generalize these concepts for stochastic systems results from necessity of extensive Monte Carlo simulations.'),
(76784, 2012, 'bio', 'GENI-DB: a database of global events for epidemic intelligence', 'Collier, Nigel|Doan, Son', 'National Institute of Informatics, ROIS, Tokyo, Japan. collier@nii.ac.jp|National Institute of Informatics, ROIS, Tokyo, Japan. collier@nii.ac.jp', 'Japan|Japan', 0, 'Animals|Databases, Factual|Humans|Internationality|Internet|Mass Media|Population Surveillance|Veterinary Medicine', 'Journal Article', '10.1093/bioinformatics/bts099', '22383735', 'We present a novel public health database (GENI-DB) in which news events on the topic of over 176 infectious diseases and chemicals affecting human and animal health are compiled from surveillance of the global online news media in 10 languages. News event frequency data were gathered systematically through the BioCaster public health surveillance system from July 2009 to the present and is available to download by the research community for purposes of analyzing trends in the global burden of infectious diseases. Database search can be conducted by year, country, disease and language.'),
(76785, 2012, 'bio', 'Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays', 'Aghaeepour, Nima|Chattopadhyay, Pratip K|Ganesan, Anuradha|ONeill, Kieran|Zare, Habil|Jalali, Adrin|Hoos, Holger H|Roederer, Mario|Brinkman, Ryan R', 'Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada.|Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada.|Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada.|Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada.|Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada.|Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada.|Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada.|Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada.|Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 56, 'Biomarkers|Computational Biology|Flow Cytometry|HIV Infections|Humans|Immunophenotyping|Predictive Value of Tests|Proportional Hazards Models|Retrospective Studies|T-Lymphocyte Subsets', 'Journal Article', '10.1093/bioinformatics/bts082', '22383736', 'Polychromatic flow cytometry (PFC), has enormous power as a tool to dissect complex immune responses (such as those observed in HIV disease) at a single cell level. However, analysis tools are severely lacking. Although high-throughput systems allow rapid data collection from large cohorts, manual data analysis can take months. Moreover, identification of cell populations can be subjective and analysts rarely examine the entirety of the multidimensional dataset (focusing instead on a limited number of subsets, the biology of which has usually already been well-described). Thus, the value of PFC as a discovery tool is largely wasted.'),
(76786, 2012, 'bio', 'WHIDE--a web tool for visual data mining colocation patterns in multivariate bioimages', 'Kölling, Jan|Langenkämper, Daniel|Abouna, Sylvie|Khan, Michael|Nattkemper, Tim W', 'Faculty of Technology, Bielefeld University, Bielefeld, Germany.|Faculty of Technology, Bielefeld University, Bielefeld, Germany.|Faculty of Technology, Bielefeld University, Bielefeld, Germany.|Faculty of Technology, Bielefeld University, Bielefeld, Germany.|Faculty of Technology, Bielefeld University, Bielefeld, Germany.', 'Germany|Germany|Germany|Germany|Germany', 28, 'Colonic Neoplasms|Data Mining|Diagnostic Imaging|Humans|Internet|Principal Component Analysis|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization|Spectrum Analysis, Raman', 'Journal Article', '10.1093/bioinformatics/bts104', '22390938', 'Bioimaging techniques rapidly develop toward higher resolution and dimension. The increase in dimension is achieved by different techniques such as multitag fluorescence imaging, Matrix Assisted Laser Desorption / Ionization (MALDI) imaging or Raman imaging, which record for each pixel an N-dimensional intensity array, representing local abundances of molecules, residues or interaction patterns. The analysis of such multivariate bioimages (MBIs) calls for new approaches to support users in the analysis of both feature domains: space (i.e. sample morphology) and molecular colocation or interaction. In this article, we present our approach WHIDE (Web-based Hyperbolic Image Data Explorer) that combines principles from computational learning, dimension reduction and visualization in a free web application.'),
(76787, 2012, 'bio', 'Combining multiple approaches for gene microarray classification', 'Nanni, Loris|Brahnam, Sheryl|Lumini, Alessandra', 'Department of Information Engineering, University of Padua, Padova, Italy. loris.nanni@unipd.it|Department of Information Engineering, University of Padua, Padova, Italy. loris.nanni@unipd.it|Department of Information Engineering, University of Padua, Padova, Italy. loris.nanni@unipd.it', 'Italy|Italy|Italy', 0, 'Area Under Curve|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/bts108', '22390939', 'The microarray report measures the expressions of tens of thousands of genes, producing a feature vector that is high in dimensionality and that contains much irrelevant information. This dimensionality degrades classification performance. Moreover, datasets typically contain few samples for training, leading to the curse of dimensionality problem. It is essential, therefore, to find good methods for reducing the size of the feature set.'),
(76788, 2012, 'bio', 'CentiLib: comprehensive analysis and exploration of network centralities', 'Gräßler, Johannes|Koschützki, Dirk|Schreiber, Falk', 'Department of Natural Sciences III, Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany.|Department of Natural Sciences III, Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany.|Department of Natural Sciences III, Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany.', 'Germany|Germany|Germany', 13, 'Computer Graphics|Information Science|Models, Biological|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts106', '22390940', 'CentiLib is a library and plug-in for the comprehensive analysis and exploration of network centralities. It provides 17 different node centrality and four graph centrality measures in a user-friendly interface and supports the exploration of analysis results within the networks. Its architecture allows for easy adaption to Java-based network analysis, simulation and visualization tools, which is demonstrated by providing the plug-in for two popular network analysis tools-Cytoscape and Vanted. With the ability to quantitatively analyze biological networks in an interactive and visual manner, CentiLib supports a better understanding of complex biological networks and processes.'),
(76789, 2012, 'bio', 'AntigenMap 3D: an online antigenic cartography resource', 'Barnett, J Lamar|Yang, Jialiang|Cai, Zhipeng|Zhang, Tong|Wan, Xiu-Feng', 'Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS 39762, USA.|Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS 39762, USA.|Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS 39762, USA.|Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS 39762, USA.|Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS 39762, USA.', 'United States|United States|United States|United States|United States', 34, 'Antigenic Variation|Antigens|Humans|Influenza A virus|Influenza Vaccines|Models, Immunological', 'Journal Article', '10.1093/bioinformatics/bts105', '22399675', 'Antigenic cartography is a useful technique to visualize and minimize errors in immunological data by projecting antigens to 2D or 3D cartography. However, a 2D cartography may not be sufficient to capture the antigenic relationship from high-dimensional immunological data. AntigenMap 3D presents an online, interactive, and robust 3D antigenic cartography construction and visualization resource. AntigenMap 3D can be applied to identify antigenic variants and vaccine strain candidates for pathogens with rapid antigenic variations, such as influenza A virus.'),
(76790, 2012, 'bio', 'Evolutionary inaccuracy of pairwise structural alignments', 'Sadowski, M I|Taylor, W R', 'Division of Mathematical Biology, MRC National Institute for Medical Research, The Ridgeway, Mill Hill, London, UK.|Division of Mathematical Biology, MRC National Institute for Medical Research, The Ridgeway, Mill Hill, London, UK.', 'United Kingdom|United Kingdom', 0, 'Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/bts103', '22399676', 'Structural alignment methods are widely used to generate gold standard alignments for improving multiple sequence alignments and transferring functional annotations, as well as for assigning structural distances between proteins. However, the correctness of the alignments generated by these methods is difficult to assess objectively since little is known about the exact evolutionary history of most proteins. Since homology is an equivalence relation, an upper bound on alignment quality can be found by assessing the consistency of alignments. Measuring the consistency of current methods of structure alignment and determining the causes of inconsistencies can, therefore, provide information on the quality of current methods and suggest possibilities for further improvement.'),
(76791, 2012, 'bio', 'Mirroring co-evolving trees in the light of their topologies', 'Hajirasouliha, Iman|Schönhuth, Alexander|de Juan, David|Valencia, Alfonso|Sahinalp, S Cenk', 'School of Computing Science, Simon Fraser University, Burnaby, BC, Canada. imanh@sfu.ca|School of Computing Science, Simon Fraser University, Burnaby, BC, Canada. imanh@sfu.ca|School of Computing Science, Simon Fraser University, Burnaby, BC, Canada. imanh@sfu.ca|School of Computing Science, Simon Fraser University, Burnaby, BC, Canada. imanh@sfu.ca|School of Computing Science, Simon Fraser University, Burnaby, BC, Canada. imanh@sfu.ca', 'Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Animals|Humans|Phylogeny|Protein Structure, Tertiary|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts109', '22399677', 'Determining the interaction partners among protein/domain families poses hard computational problems, in particular in the presence of paralogous proteins. Available approaches aim to identify interaction partners among protein/domain families through maximizing the similarity between trimmed versions of their phylogenetic trees. Since maximization of any natural similarity score is computationally difficult, many approaches employ heuristics to evaluate the distance matrices corresponding to the tree topologies in question. In this article, we devise an efficient deterministic algorithm which directly maximizes the similarity between two leaf labeled trees with edge lengths, obtaining a score-optimal alignment of the two trees in question.'),
(76792, 2012, 'bio', 'Bioimage informatics: a new category in Bioinformatics', 'Peng, Hanchuan|Bateman, Alex|Valencia, Alfonso|Wren, Jonathan D', 'School of Computing Science, Simon Fraser University, Burnaby, BC, Canada. imanh@sfu.ca|School of Computing Science, Simon Fraser University, Burnaby, BC, Canada. imanh@sfu.ca|School of Computing Science, Simon Fraser University, Burnaby, BC, Canada. imanh@sfu.ca|School of Computing Science, Simon Fraser University, Burnaby, BC, Canada. imanh@sfu.ca', 'Canada|Canada|Canada|Canada', 16, 'Audiovisual Aids|Computational Biology|Congresses as Topic|Image Processing, Computer-Assisted', 'Editorial', '10.1093/bioinformatics/bts111', '22399678', '-'),
(76793, 2012, 'bio', 'rehh: an R package to detect footprints of selection in genome-wide SNP data from haplotype structure', 'Gautier, Mathieu|Vitalis, Renaud', 'INRA, Montferrier-sur-Lez Cedex, France. mathieu.gautier@supagro.inra.fr|INRA, Montferrier-sur-Lez Cedex, France. mathieu.gautier@supagro.inra.fr', 'France|France', 0, 'Animals|Cattle|Genome-Wide Association Study|Haplotypes|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/bts115', '22402612', 'With the development of next-generation sequencing and genotyping approaches, large single nucleotide polymorphism haplotype datasets are becoming available in a growing number of both model and non-model species. Identifying genomic regions with unexpectedly high local haplotype homozygosity relatively to neutral expectation represents a powerful strategy to ascertain candidate genes responding to natural or artificial selection. To facilitate genome-wide scans of selection based on the analysis of long-range haplotypes, we developed the R package rehh. It provides a versatile tool to detect the footprints of recent or ongoing selection with several graphical functions that help visual interpretation of the results.'),
(76794, 2012, 'bio', 'A strategy for building neuroanatomy ontologies', 'Osumi-Sutherland, David|Reeve, Simon|Mungall, Christopher J|Neuhaus, Fabian|Ruttenberg, Alan|Jefferis, Gregory S X E|Armstrong, J Douglas', 'Department of Genetics, University of Cambridge, Cambridge, UK.|Department of Genetics, University of Cambridge, Cambridge, UK.|Department of Genetics, University of Cambridge, Cambridge, UK.|Department of Genetics, University of Cambridge, Cambridge, UK.|Department of Genetics, University of Cambridge, Cambridge, UK.|Department of Genetics, University of Cambridge, Cambridge, UK.|Department of Genetics, University of Cambridge, Cambridge, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 19, 'Animals|Arthropod Antennae|Brain|Drosophila|Internet|Nervous System|Neuroanatomy|Neurons|Software|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts113', '22402613', 'Advancing our understanding of how nervous systems work will require the ability to store and annotate 3D anatomical datasets, recording morphology, partonomy and connectivity at multiple levels of granularity from subcellular to gross anatomy. It will also require the ability to integrate this data with other data-types including functional, genetic and electrophysiological data. The web ontology language OWL2 provides the means to solve many of these problems. Using it, one can rigorously define and relate classes of anatomical structure using multiple criteria. The resulting classes can be used to annotate datasets recording, for example, gene expression or electrophysiology. Reasoning software can be used to automate classification and error checking and to construct and answer sophisticated combinatorial queries. But for such queries to give consistent and biologically meaningful results, it is important that both classes and the terms (relations) used to relate them are carefully defined.'),
(76795, 2012, 'bio', 'YOABS: yet other aligner of biological sequences--an efficient linearly scaling nucleotide aligner', 'Galinsky, V L', 'Qualg Inc., La Jolla, CA, 92037, USA. vit@ucsd.edu', 'United States', 0, 'Algorithms|Genome, Human|Humans|Reproducibility of Results|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts102', '22402614', 'Explosive growth of short-read sequencing technologies in the recent years resulted in rapid development of many new alignment algorithms and programs. But most of them are not efficient or not applicable for reads > or approximately equal to 200 bp because these algorithms specifically designed to process short queries with relatively low sequencing error rates. However, the current trend to increase reliability of detection of structural variations in assembled genomes as well as to facilitate de novo sequencing demand complimenting high-throughput short-read platforms with long-read mapping. Thus, algorithms and programs for efficient mapping of longer reads are becoming crucial. However, the choice of long-read aligners effective in terms of both performance and memory are limited and includes only handful of hash table (BLAT, SSAHA2) or trie (Burrows-Wheeler Transform - Smith-Waterman (BWT-SW), Burrows-Wheeler Alignerr - Smith-Waterman (BWA-SW)) based algorithms.'),
(76796, 2012, 'bio', 'SMURFLite: combining simplified Markov random fields with simulated evolution improves remote homology detection for beta-structural proteins into the twilight zone', 'Daniels, Noah M|Hosur, Raghavendra|Berger, Bonnie|Cowen, Lenore J', 'Department of Computer Science, Tufts University, Medford, MA 02155, USA.|Department of Computer Science, Tufts University, Medford, MA 02155, USA.|Department of Computer Science, Tufts University, Medford, MA 02155, USA.|Department of Computer Science, Tufts University, Medford, MA 02155, USA.', 'United States|United States|United States|United States', 0, 'Amino Acid Sequence|Genome, Bacterial|Humans|Markov Chains|Models, Molecular|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Software|Thermotoga maritima', 'Journal Article', '10.1093/bioinformatics/bts110', '22408192', 'One of the most successful methods to date for recognizing protein sequences that are evolutionarily related has been profile hidden Markov models (HMMs). However, these models do not capture pairwise statistical preferences of residues that are hydrogen bonded in beta sheets. These dependencies have been partially captured in the HMM setting by simulated evolution in the training phase and can be fully captured by Markov random fields (MRFs). However, the MRFs can be computationally prohibitive when beta strands are interleaved in complex topologies. We introduce SMURFLite, a method that combines both simplified MRFs and simulated evolution to substantially improve remote homology detection for beta structures. Unlike previous MRF-based methods, SMURFLite is computationally feasible on any beta-structural motif.'),
(76797, 2012, 'bio', 'Defining and providing robust controls for microRNA prediction', 'Ritchie, William|Gao, Dadi|Rasko, John E J', 'Gene and Stem Cell Therapy Program, Centenary Institute, University of Sydney, Sydney, New South Wales, Australia. w.ritchie@centenary.org.au|Gene and Stem Cell Therapy Program, Centenary Institute, University of Sydney, Sydney, New South Wales, Australia. w.ritchie@centenary.org.au|Gene and Stem Cell Therapy Program, Centenary Institute, University of Sydney, Sydney, New South Wales, Australia. w.ritchie@centenary.org.au', 'Australia|Australia|Australia', 0, 'Algorithms|Animals|Brain|Databases, Genetic|Fibroblasts|Gene Expression Profiling|Gene Knockout Techniques|Humans|Mice|MicroRNAs|RNA, Messenger|Rats|Reference Standards|Ribonuclease III', 'Journal Article', '10.1093/bioinformatics/bts114', '22408193', 'microRNAs are short non-coding RNAs that regulate gene expression by inhibiting target mRNA genes. Next-generation sequencing combined with bioinformatics analyses provide an opportunity to predict numerous novel miRNAs. The efficiency of these predictions relies on the set of positive and negative controls used. We demonstrate that commonly used positive and negative controls may be unreliable and provide a rational methodology with which to replace them.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76798, 2012, 'bio', 'Deriving transcriptional programs and functional processes from gene expression databases', 'Chang, Jeffrey T', 'Department of Integrative Biology and Pharmacology, The University of Texas Health Science Center in Houston, Houston, TX 77030, USA. jeffrey.t.chang@uth.tmc.edu', 'United States', 3, 'Algorithms|Breast Neoplasms|Cell Cycle|Data Mining|Databases, Genetic|E2F Transcription Factors|Gene Expression Profiling|Gene Regulatory Networks|Humans', 'Journal Article', '10.1093/bioinformatics/bts112', '22408194', 'A system-wide approach to revealing the underlying molecular state of a cell is a long-standing biological challenge. Developed over the last decade, gene expression profiles possess the characteristics of such an assay. They have the capacity to reveal both underlying molecular events as well as broader phenotypes such as clinical outcomes. To interpret these profiles, many gene sets have been developed that characterize biological processes. However, the full potential of these gene sets has not yet been achieved. Since the advent of gene expression databases, many have posited that they can reveal properties of activities that are not evident from individual datasets, analogous to how the expression of a single gene generally cannot reveal the activation of a biological process.'),
(76799, 2012, 'bio', 'SEQanswers: an open access community for collaboratively decoding genomes', 'Li, Jing-Woei|Schmieder, Robert|Ward, R Matthew|Delenick, Joann|Olivares, Eric C|Mittelman, David', 'School of Life Sciences, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR.|School of Life Sciences, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR.|School of Life Sciences, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR.|School of Life Sciences, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR.|School of Life Sciences, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR.|School of Life Sciences, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong', 43, 'Cooperative Behavior|Genomics|High-Throughput Nucleotide Sequencing|Human Genome Project|Humans|Internet|Metagenome', 'Journal Article', '10.1093/bioinformatics/bts128', '22419780', 'The affordability of high-throughput sequencing has created an unprecedented surge in the use of genomic data in basic, translational and clinical research. The rapid evolution of sequencing technology, coupled with its broad adoption across biology and medicine, necessitates fast, collaborative interdisciplinary discussion. SEQanswers provides a real-time knowledge-sharing resource to address this need, covering experimental and computational aspects of sequencing and sequence analysis. Developers of popular analysis tools are among the >4000 active members, and ~40 peer-reviewed publications have referenced SEQanswers.'),
(76800, 2012, 'bio', 'IsoCor: correcting MS data in isotope labeling experiments', 'Millard, Pierre|Letisse, Fabien|Sokol, Serguei|Portais, Jean-Charles', 'Université de Toulouse, 135 Avenue de Rangueil, Toulouse, France.|Université de Toulouse, 135 Avenue de Rangueil, Toulouse, France.|Université de Toulouse, 135 Avenue de Rangueil, Toulouse, France.|Université de Toulouse, 135 Avenue de Rangueil, Toulouse, France.', 'France|France|France|France', 0, 'Algorithms|Isotope Labeling|Mass Spectrometry|Software', 'Journal Article', '10.1093/bioinformatics/bts127', '22419781', 'Mass spectrometry (MS) is widely used for isotopic labeling studies of metabolism and other biological processes. Quantitative applications-e.g. metabolic flux analysis-require tools to correct the raw MS data for the contribution of all naturally abundant isotopes. IsoCor is a software that allows such correction to be applied to any chemical species. Hence it can be used to exploit any isotopic tracer, from well-known ((13)C, (15)N, (18)O, etc) to unusual ((57)Fe, (77)Se, etc) isotopes. It also provides new features-e.g. correction for the isotopic purity of the tracer-to improve the accuracy of quantitative isotopic studies, and implements an efficient algorithm to process large datasets. Its user-friendly interface makes isotope labeling experiments more accessible to a wider biological community.'),
(76801, 2012, 'bio', 'PINALOG: a novel approach to align protein interaction networks--implications for complex detection and function prediction', 'Phan, Hang T T|Sternberg, Michael J E', 'Division of Molecular Biosciences, Faculty of Natural Sciences, Imperial College, London, UK.|Division of Molecular Biosciences, Faculty of Natural Sciences, Imperial College, London, UK.', 'United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Humans|Protein Interaction Maps|Proteins|Sequence Alignment|Sequence Analysis, Protein|Yeasts', 'Journal Article', '10.1093/bioinformatics/bts119', '22419782', 'Analysis of protein-protein interaction networks (PPINs) at the system level has become increasingly important in understanding biological processes. Comparison of the interactomes of different species not only provides a better understanding of species evolution but also helps with detecting conserved functional components and in function prediction. Method and'),
(76802, 2012, 'bio', 'Harmonization of gene/protein annotations: towards a gold standard MEDLINE', 'Campos, David|Matos, Sxc3xa9rgio|Lewin, Ian|Oliveira, Josxc3xa9 Luxc3xads|Rebholz-Schuhmann, Dietrich', 'University of Aveiro, IEETA/DETI, Campus Universitxc3xa1rio de Santiago, Aveiro, Portugal. david.campos@ua.pt|University of Aveiro, IEETA/DETI, Campus Universitxc3xa1rio de Santiago, Aveiro, Portugal. david.campos@ua.pt|University of Aveiro, IEETA/DETI, Campus Universitxc3xa1rio de Santiago, Aveiro, Portugal. david.campos@ua.pt|University of Aveiro, IEETA/DETI, Campus Universitxc3xa1rio de Santiago, Aveiro, Portugal. david.campos@ua.pt|University of Aveiro, IEETA/DETI, Campus Universitxc3xa1rio de Santiago, Aveiro, Portugal. david.campos@ua.pt', 'Portugal|Portugal|Portugal|Portugal|Portugal', 10, 'Animals|Artificial Intelligence|Data Mining|Humans|MEDLINE|Mice|Molecular Sequence Annotation|Proteins|Terminology as Topic|United States', 'Journal Article', '10.1093/bioinformatics/bts125', '22419783', 'The recognition of named entities (NER) is an elementary task in biomedical text mining. A number of NER solutions have been proposed in recent years, taking advantage of available annotated corpora, terminological resources and machine-learning techniques. Currently, the best performing solutions combine the outputs from selected annotation solutions measured against a single corpus. However, little effort has been spent on a systematic analysis of methods harmonizing the annotation results and measuring against a combination of Gold Standard Corpora (GSCs).'),
(76803, 2012, 'bio', 'Predicting the lethal phenotype of the knockout mouse by integrating comprehensive genomic data', 'Yuan, Yuan|Xu, Yanxun|Xu, Jianfeng|Ball, Robyn L|Liang, Han', 'Graduate Program in Structural and Computational Biology and Molecular Biophysics, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA.|Graduate Program in Structural and Computational Biology and Molecular Biophysics, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA.|Graduate Program in Structural and Computational Biology and Molecular Biophysics, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA.|Graduate Program in Structural and Computational Biology and Molecular Biophysics, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA.|Graduate Program in Structural and Computational Biology and Molecular Biophysics, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA.', 'United States|United States|United States|United States|United States', 0, 'Animals|Artificial Intelligence|Genes, Lethal|Humans|Mice|Mice, Knockout|Models, Animal|Phenotype', 'Journal Article', '10.1093/bioinformatics/bts120', '22419784', 'The phenotypes of knockout mice provide crucial information for understanding the biological functions of mammalian genes. Among various knockout phenotypes, lethality is of great interest because those involved genes play essential roles. With the availability of large-scale genomic data, we aimed to assess how well the integration of various genomic features can predict the lethal phenotype of single-gene knockout mice.'),
(76804, 2012, 'bio', 'SAMSCOPE: an OpenGL-based real-time interactive scale-free SAM viewer', 'Popendorf, Kris|Sakakibara, Yasubumi', 'Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Yokohama, Japan.|Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Yokohama, Japan.', 'Japan|Japan', 0, 'Animals|Bacillus subtilis|Computer Graphics|Genome|Humans|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts122', '22419785', 'Existing SAM visualization tools like samtools tview (Li et al., 2009) are limited to a small region of the genome, and tools like Tablet (Milne et al., 2010) are limited to a relatively small number of reads and may fail outright on large datasets. We need to visualize complex ChIP-Seq and RNA-Seq features such as polarity as well as coverage across whole 3 Gbp genomes such as Human. We have addressed these problems in a lightweight visualization system called SAMSCOPE accelerated by OpenGL. The extensive pre-processing and fast OpenGL interface of SAMSCOPE provides instantaneous and intuitive browsing of complex data at all levels of detail across multiple experiments.'),
(76805, 2012, 'bio', 'Fulcrum: condensing redundant reads from high-throughput sequencing studies', 'Burriesci, Matthew S|Lehnert, Erik M|Pringle, John R', 'Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305-5120, USA.|Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305-5120, USA.|Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305-5120, USA.', 'United States|United States|United States', 22, 'Algorithms|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Pseudomonas|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts123', '22419786', 'Ultra-high-throughput sequencing produces duplicate and near-duplicate reads, which can consume computational resources in downstream applications. A tool that collapses such reads should reduce storage and assembly complications and costs.'),
(76806, 2012, 'bio', 'Industrial methodology for process verification in research (IMPROVER): toward systems biology verification', 'Meyer, Pablo|Hoeng, Julia|Rice, J Jeremy|Norel, Raquel|Sprengel, Jörg|Stolle, Katrin|Bonk, Thomas|Corthesy, Stephanie|Royyuru, Ajay|Peitsch, Manuel C|Stolovitzky, Gustavo', 'IBM Computational Biology Center, Yorktown Heights, NY 10598, USA.|IBM Computational Biology Center, Yorktown Heights, NY 10598, USA.|IBM Computational Biology Center, Yorktown Heights, NY 10598, USA.|IBM Computational Biology Center, Yorktown Heights, NY 10598, USA.|IBM Computational Biology Center, Yorktown Heights, NY 10598, USA.|IBM Computational Biology Center, Yorktown Heights, NY 10598, USA.|IBM Computational Biology Center, Yorktown Heights, NY 10598, USA.|IBM Computational Biology Center, Yorktown Heights, NY 10598, USA.|IBM Computational Biology Center, Yorktown Heights, NY 10598, USA.|IBM Computational Biology Center, Yorktown Heights, NY 10598, USA.|IBM Computational Biology Center, Yorktown Heights, NY 10598, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Peer Review|Periodicals as Topic|Reproducibility of Results|Systems Biology|Workflow', 'Journal Article', '10.1093/bioinformatics/bts116', '22423044', 'Analyses and algorithmic predictions based on high-throughput data are essential for the success of systems biology in academic and industrial settings. Organizations, such as companies and academic consortia, conduct large multi-year scientific studies that entail the collection and analysis of thousands of individual experiments, often over many physical sites and with internal and outsourced components. To extract maximum value, the interested parties need to verify the accuracy and reproducibility of data and methods before the initiation of such large multi-year studies. However, systematic and well-established verification procedures do not exist for automated collection and analysis workflows in systems biology which could lead to inaccurate conclusions.'),
(76807, 2012, 'bio', 'BioQ: tracing experimental origins in public genomic databases using a novel data provenance model', 'Saccone, Scott F|Quan, Jiaxi|Jones, Peter L', 'Department of Psychiatry, Washington University, Saint Louis, MO 63110, USA. ssaccone@wustl.edu|Department of Psychiatry, Washington University, Saint Louis, MO 63110, USA. ssaccone@wustl.edu|Department of Psychiatry, Washington University, Saint Louis, MO 63110, USA. ssaccone@wustl.edu', 'United States|United States|United States', 10, 'Databases, Genetic|Disease|Genetic Variation|Genome|Genome, Human|HapMap Project|Humans|Internet', 'Journal Article', '10.1093/bioinformatics/bts117', '22426342', 'Public genomic databases, which are often used to guide genetic studies of human disease, are now being applied to genomic medicine through in silico integrative genomics. These databases, however, often lack tools for systematically determining the experimental origins of the data.'),
(76808, 2012, 'bio', 'GRiP: a computational tool to simulate transcription factor binding in prokaryotes', 'Zabet, Nicolae Radu|Adryan, Boris', 'Cambridge Systems Biology Centre, University of Cambridge, Tennis Court Road, Cambridge, UK. n.r.zabet@gen.cam.ac.uk|Cambridge Systems Biology Centre, University of Cambridge, Tennis Court Road, Cambridge, UK. n.r.zabet@gen.cam.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Base Sequence|Binding Sites|Computer Simulation|DNA|Escherichia coli K12|Gene Expression Regulation|Prokaryotic Cells|Protein Binding|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bts132', '22426343', 'Transcription factors (TFs) are proteins that regulate gene activity by binding to specific sites on the DNA. Understanding the way these molecules locate their target site is of great importance in understanding gene regulation. We developed a comprehensive computational model of this process and estimated the model parameters in (N.R.Zabet and B.Adryan, submitted for publication).'),
(76809, 2012, 'bio', 'Proteus: a web-based, context-specific modelling tool for molecular networks', 'Gnad, Florian|Estrada, Javier|Gunawardena, Jeremy', 'Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.|Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.|Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.', 'United States|United States|United States', 0, 'Animals|Databases, Factual|Internet|Models, Biological|Signal Transduction|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/bts126', '22426344', 'Molecular networks are often studied in diverse cellular or experimental contexts, with highly context-specific details. Modelling introduces further choices as to levels of mathematical description. The resulting possibilities are difficult to explore rapidly, hampering the integration of modelling and experiment. We have developed Proteus, a web-based, context-specific tool for building compartmentalized, ordinary differential equation (ODE) models. It is inspired by the idea of a molecular toolkit for Ca(2+) signalling. Toolkits in Proteus are context-independent representations of biological systems as sets of components, which may correspond to mechanisms of differing levels of complexity. Users pick and choose components from a toolkit and, for each component, pick and choose from different mechanisms, each of which describes a different instantiation of the components mechanism. Proteus combines these choices into a system of ODEs, which may then be downloaded in SBML (Systems Biology Markup Language), Matlab or Fortran format and independently analyzed. Toolkits, components and mechanisms are user-constructible, either de novo or by cannibalizing existing models, including all those in the Biomodels database. A wide variety of context-specific models may thereby be rapidly built, modified and explored.'),
(76810, 2012, 'bio', 'GOHTAM: a website for Genomic Origin of Horizontal Transfers, Alignment and Metagenomics', 'Ménigaud, Sabine|Mallet, Ludovic|Picord, Géraldine|Churlaud, Cécile|Borrel, Alexandre|Deschavanne, Patrick', 'Molécules Thérapeutiques in silico, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR-S 973, Université Paris Diderot, Sorbonne Paris Cité, 35 rue Héléne Brion, Paris, France.|Molécules Thérapeutiques in silico, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR-S 973, Université Paris Diderot, Sorbonne Paris Cité, 35 rue Héléne Brion, Paris, France.|Molécules Thérapeutiques in silico, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR-S 973, Université Paris Diderot, Sorbonne Paris Cité, 35 rue Héléne Brion, Paris, France.|Molécules Thérapeutiques in silico, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR-S 973, Université Paris Diderot, Sorbonne Paris Cité, 35 rue Héléne Brion, Paris, France.|Molécules Thérapeutiques in silico, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR-S 973, Université Paris Diderot, Sorbonne Paris Cité, 35 rue Héléne Brion, Paris, France.|Molécules Thérapeutiques in silico, Institut National de la Santé et de la Recherche Médicale (INSERM) UMR-S 973, Université Paris Diderot, Sorbonne Paris Cité, 35 rue Héléne Brion, Paris, France.', 'France|France|France|France|France|France', 0, 'Bacteria|Gene Transfer, Horizontal|Genome|Genome, Bacterial|Metagenomics|Phylogeny|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts118', '22426345', 'This website allows the detection of horizontal transfers based on a combination of parametric methods and proposes an origin by researching neighbors in a bank of genomic signatures. This bank is also used to research an origin to DNA fragments from metagenomics studies.'),
(76811, 2012, 'bio', 'JETTA: junction and exon toolkits for transcriptome analysis', 'Seok, Junhee|Xu, Weihong|Gao, Hong|Davis, Ronald W|Xiao, Wenzhong', 'Stanford Genome Technology Center, 855 California Street, Palo Alto, CA 94304, USA.|Stanford Genome Technology Center, 855 California Street, Palo Alto, CA 94304, USA.|Stanford Genome Technology Center, 855 California Street, Palo Alto, CA 94304, USA.|Stanford Genome Technology Center, 855 California Street, Palo Alto, CA 94304, USA.|Stanford Genome Technology Center, 855 California Street, Palo Alto, CA 94304, USA.', 'United States|United States|United States|United States|United States', 19, 'Alternative Splicing|Exons|Gene Expression Profiling|Genome-Wide Association Study|Humans|Liver|Muscles|Oligonucleotide Array Sequence Analysis|RNA Splice Sites|Software', 'Journal Article', '10.1093/bioinformatics/bts134', '22433281', 'High-throughput genome-wide studies of alternatively spliced mRNA transcripts have become increasingly important in clinical research. Consequently, easy-to-use software tools are required to process data from these studies, for example, using exon and junction arrays. Here, we introduce JETTA, an integrated software package for the calculation of gene expression indices as well as the identification and visualization of alternative splicing events. We demonstrate the software using data of human liver and muscle samples hybridized on an exon-junction array.'),
(76812, 2012, 'bio', 'Fast stochastic algorithm for simulating evolutionary population dynamics', 'Mather, William H|Hasty, Jeff|Tsimring, Lev S', 'Department of Bioengineering, University of California-San Diego, CA 92093, USA.|Department of Bioengineering, University of California-San Diego, CA 92093, USA.|Department of Bioengineering, University of California-San Diego, CA 92093, USA.', 'United States|United States|United States', 8, 'Algorithms|Bacteria|Biological Evolution|Computer Simulation|Mutation', 'Journal Article', '10.1093/bioinformatics/bts130', '22437850', 'Many important aspects of evolutionary dynamics can only be addressed through simulations. However, accurate simulations of realistically large populations over long periods of time needed for evolution to proceed are computationally expensive. Mutants can be present in very small numbers and yet (if they are more fit than others) be the key part of the evolutionary process. This leads to significant stochasticity that needs to be accounted for. Different evolutionary events occur at very different time scales: mutations are typically much rarer than reproduction and deaths.'),
(76813, 2012, 'bio', 'MDWeb and MDMoby: an integrated web-based platform for molecular dynamics simulations', 'Hospital, Adam|Andrio, Pau|Fenollosa, Carles|Cicin-Sain, Damjan|Orozco, Modesto|Gelpí, Josep Lluís', 'Joint IRB-BSC Program on Computational Biology, Institute of Research in Biomedicine, Barcelona Science Park, Josep Samitier 1-5, Barcelona, Spain.|Joint IRB-BSC Program on Computational Biology, Institute of Research in Biomedicine, Barcelona Science Park, Josep Samitier 1-5, Barcelona, Spain.|Joint IRB-BSC Program on Computational Biology, Institute of Research in Biomedicine, Barcelona Science Park, Josep Samitier 1-5, Barcelona, Spain.|Joint IRB-BSC Program on Computational Biology, Institute of Research in Biomedicine, Barcelona Science Park, Josep Samitier 1-5, Barcelona, Spain.|Joint IRB-BSC Program on Computational Biology, Institute of Research in Biomedicine, Barcelona Science Park, Josep Samitier 1-5, Barcelona, Spain.|Joint IRB-BSC Program on Computational Biology, Institute of Research in Biomedicine, Barcelona Science Park, Josep Samitier 1-5, Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain', 78, 'Humans|Internet|Molecular Dynamics Simulation|Nucleic Acids|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts139', '22437851', 'MDWeb and MDMoby constitute a web-based platform to help access to molecular dynamics (MD) in the standard and high-throughput regime. The platform provides tools to prepare systems from PDB structures mimicking the procedures followed by human experts. It provides inputs and can send simulations for three of the most popular MD packages (Amber, NAMD and Gromacs). Tools for analysis of trajectories, either provided by the user or retrieved from our MoDEL database (http://mmb.pcb.ub.es/MoDEL) are also incorporated. The platform has two ways of access, a set of web-services based on the BioMoby framework (MDMoby), programmatically accessible and a web portal (MDWeb).'),
(76814, 2012, 'bio', 'FTEC: a coalescent simulator for modeling faster than exponential growth', 'Reppell, Mark|Boehnke, Michael|Zöllner, Sebastian', 'Department of Biostatistics and Center for Statistical Genetics and Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA. mreppell@umich.edu|Department of Biostatistics and Center for Statistical Genetics and Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA. mreppell@umich.edu|Department of Biostatistics and Center for Statistical Genetics and Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA. mreppell@umich.edu', 'United States|United States|United States', 0, 'Computer Simulation|Genetics, Population|Humans|Models, Genetic|Population Density|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/bts135', '22441586', 'Recent genetic studies as well as recorded history point to massive growth in human population sizes during the recent past. To model and understand this growth accurately we introduce FTEC, an easy-to-use coalescent simulation program capable of simulating haplotype samples drawn from a population that has undergone faster than exponential growth. Samples drawn from a population that has undergone faster than exponential growth show an excess of very rare variation and more rapid LD decay when compared with samples drawn from a population that has maintained a constant size over time.'),
(76815, 2012, 'bio', 'CpGassoc: an R function for analysis of DNA methylation microarray data', 'Barfield, Richard T|Kilaru, Varun|Smith, Alicia K|Conneely, Karen N', 'Department of Bioinformatics and Biostatistics, School of Public Health, Emory University at Atlanta, GA 30322, USA. rtbarfi@emory.edu|Department of Bioinformatics and Biostatistics, School of Public Health, Emory University at Atlanta, GA 30322, USA. rtbarfi@emory.edu|Department of Bioinformatics and Biostatistics, School of Public Health, Emory University at Atlanta, GA 30322, USA. rtbarfi@emory.edu|Department of Bioinformatics and Biostatistics, School of Public Health, Emory University at Atlanta, GA 30322, USA. rtbarfi@emory.edu', 'United States|United States|United States|United States', 105, 'CpG Islands|DNA Methylation|Humans|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/bts124', '22451269', 'With the increasing availability of high-density methylation microarrays, there has been growing interest in analysis of DNA methylation data. We have developed CpGassoc, an R package that can efficiently perform the statistical analysis needed for increasingly large methylation datasets. CpGassoc is a modular, expandable package with functions to perform rapid analyses of DNA methylation data via fixed or mixed effects models, to perform basic quality control, to carry out permutation tests, and to display results via an array of publication-quality plots.'),
(76816, 2012, 'bio', 'ADMIT: a toolbox for guaranteed model invalidation, estimation and qualitative-quantitative modeling', 'Streif, Stefan|Savchenko, Anton|Rumschinski, Philipp|Borchers, Steffen|Findeisen, Rolf', 'Otto-von-Guericke Universität Magdeburg, Institute for Automation Engineering, Systems Theory and Automatic Control Laboratory, Magdeburg, Germany. stefan.streif@ovgu.de|Otto-von-Guericke Universität Magdeburg, Institute for Automation Engineering, Systems Theory and Automatic Control Laboratory, Magdeburg, Germany. stefan.streif@ovgu.de|Otto-von-Guericke Universität Magdeburg, Institute for Automation Engineering, Systems Theory and Automatic Control Laboratory, Magdeburg, Germany. stefan.streif@ovgu.de|Otto-von-Guericke Universität Magdeburg, Institute for Automation Engineering, Systems Theory and Automatic Control Laboratory, Magdeburg, Germany. stefan.streif@ovgu.de|Otto-von-Guericke Universität Magdeburg, Institute for Automation Engineering, Systems Theory and Automatic Control Laboratory, Magdeburg, Germany. stefan.streif@ovgu.de', 'Germany|Germany|Germany|Germany|Germany', 31, 'Algorithms|Models, Biological|Monte Carlo Method|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/bts137', '22451270', 'Often competing hypotheses for biochemical networks exist in the form of different mathematical models with unknown parameters. Considering available experimental data, it is then desired to reject model hypotheses that are inconsistent with the data, or to estimate the unknown parameters. However, these tasks are complicated because experimental data are typically sparse, uncertain, and are frequently only available in form of qualitative if-then observations. ADMIT (Analysis, Design and Model Invalidation Toolbox) is a MatLab(TM)-based tool for guaranteed model invalidation, state and parameter estimation. The toolbox allows the integration of quantitative measurement data, a priori knowledge of parameters and states, and qualitative information on the dynamic or steady-state behavior. A constraint satisfaction problem is automatically generated and algorithms are implemented for solving the desired estimation, invalidation or analysis tasks. The implemented methods built on convex relaxation and optimization and therefore provide guaranteed estimation results and certificates for invalidity.'),
(76817, 2012, 'bio', '1001 Proteomes: a functional proteomics portal for the analysis of Arabidopsis thaliana accessions', 'Joshi, Hiren J|Christiansen, Katy M|Fitz, Joffrey|Cao, Jun|Lipzen, Anna|Martin, Joel|Smith-Moritz, A Michelle|Pennacchio, Len A|Schackwitz, Wendy S|Weigel, Detlef|Heazlewood, Joshua L', 'Joint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.|Joint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.|Joint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.|Joint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.|Joint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.|Joint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.|Joint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.|Joint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.|Joint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.|Joint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.|Joint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Amino Acid Substitution|Arabidopsis|Arabidopsis Proteins|DNA, Plant|Databases, Protein|Phosphorylation|Polymorphism, Single Nucleotide|Protein Processing, Post-Translational|Proteome|Proteomics|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts133', '22451271', 'The sequencing of over a thousand natural strains of the model plant Arabidopsis thaliana is producing unparalleled information at the genetic level for plant researchers. To enable the rapid exploitation of these data for functional proteomics studies, we have created a resource for the visualization of protein information and proteomic datasets for sequenced natural strains of A. thaliana.'),
(76818, 2012, 'bio', 'OCAP: an open comprehensive analysis pipeline for iTRAQ', 'Wang, Penghao|Yang, Pengyi|Yang, Jean Yee Hwa', 'School of Mathematics and Statistics, University of Sydney, Camperdown, NSW2006, Australia. penghao.wang@sydney.edu.au|School of Mathematics and Statistics, University of Sydney, Camperdown, NSW2006, Australia. penghao.wang@sydney.edu.au|School of Mathematics and Statistics, University of Sydney, Camperdown, NSW2006, Australia. penghao.wang@sydney.edu.au', 'Australia|Australia|Australia', 7, 'Algorithms|Disease|Humans|Mass Spectrometry|Proteins|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/bts150', '22467906', 'Mass spectrometry-based iTRAQ protein quantification is a high-throughput assay for determining relative protein expressions and identifying disease biomarkers. Processing and analysis of these large and complex data involves a number of distinct components and it is desirable to have a pipeline to efficiently integrate these together. To date, there are limited public available comprehensive analysis pipelines for iTRAQ data and many of these existing pipelines have limited visualization tools and no convenient interfaces with downstream analyses. We have developed a new open source comprehensive iTRAQ analysis pipeline, OCAP, integrating a wavelet-based preprocessing algorithm which provides better peak picking, a new quantification algorithm and a suite of visualizsation tools. OCAP is mainly developed in C++ and is provided as a standalone version (OCAP_standalone) as well as an R package. The R package (OCAP) provides the necessary interfaces with downstream statistical analysis.'),
(76819, 2012, 'bio', 'A subspace method for the detection of transcription factor binding sites', 'Pairó, Erola|Maynou, Joan|Marco, Santiago|Perera, Alexandre', 'Institut de Bioenginyeria de Catalunya, Baldiri Reixach 4, 08028 Barcelona, Spain. epairo@ibecbarcelona.eu|Institut de Bioenginyeria de Catalunya, Baldiri Reixach 4, 08028 Barcelona, Spain. epairo@ibecbarcelona.eu|Institut de Bioenginyeria de Catalunya, Baldiri Reixach 4, 08028 Barcelona, Spain. epairo@ibecbarcelona.eu|Institut de Bioenginyeria de Catalunya, Baldiri Reixach 4, 08028 Barcelona, Spain. epairo@ibecbarcelona.eu', 'Spain|Spain|Spain|Spain', 5, 'Algorithms|Animals|Binding Sites|Humans|Nucleotide Motifs|Position-Specific Scoring Matrices|Protein Binding|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bts147', '22467907', 'The identification of the sites at which transcription factors (TFs) bind to Deoxyribonucleic acid (DNA) is an important problem in molecular biology. Many computational methods have been developed for motif finding, most of them based on position-specific scoring matrices (PSSMs) which assume the independence of positions within a binding site. However, some experimental and computational studies demonstrate that interdependences within the positions exist.'),
(76820, 2012, 'bio', 'GECA: a fast tool for gene evolution and conservation analysis in eukaryotic protein families', 'Fawal, Nizar|Savelli, Bruno|Dunand, Christophe|Mathé, Catherine', 'Université de Toulouse, UPS, UMR 5546, Laboratoire de Recherche en Sciences Végétales, BP 42617 Auze ville, F-31326 Castanet-Tolosan, France.|Université de Toulouse, UPS, UMR 5546, Laboratoire de Recherche en Sciences Végétales, BP 42617 Auze ville, F-31326 Castanet-Tolosan, France.|Université de Toulouse, UPS, UMR 5546, Laboratoire de Recherche en Sciences Végétales, BP 42617 Auze ville, F-31326 Castanet-Tolosan, France.|Université de Toulouse, UPS, UMR 5546, Laboratoire de Recherche en Sciences Végétales, BP 42617 Auze ville, F-31326 Castanet-Tolosan, France.', 'France|France|France|France', 0, 'Conserved Sequence|Eukaryota|Evolution, Molecular|Exons|Introns|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/bts153', '22467908', 'GECA is a fast, user-friendly and freely-available tool for representing gene exon/intron organization and highlighting changes in gene structure among members of a gene family. It relies on protein alignment, completed with the identification of common introns in the corresponding genes using CIWOG. GECA produces a main graphical representation showing the resulting aligned set of gene structures, where exons are to scale. The important and original feature of GECA is that it combines these gene structures with a symbolic display highlighting sequence similarity between subsequent genes. It is worth noting that this combination of gene structure with the indications of similarities between related genes allows rapid identification of possible events of gain or loss of introns, or points to erroneous structural annotations. The output image is generated in a portable network graphics format which can be used for scientific publications.'),
(76821, 2012, 'bio', 'DADP: the database of anuran defense peptides', 'Novkovixc4x87, Mario|Simunixc4x87, Juraj|Bojovixc4x87, Viktor|Tossi, Alessandro|Juretixc4x87, Davor', 'Department of Physics, Faculty of Science, University of Split, 21000 Split, Croatia.|Department of Physics, Faculty of Science, University of Split, 21000 Split, Croatia.|Department of Physics, Faculty of Science, University of Split, 21000 Split, Croatia.|Department of Physics, Faculty of Science, University of Split, 21000 Split, Croatia.|Department of Physics, Faculty of Science, University of Split, 21000 Split, Croatia.', 'Croatia|Croatia|Croatia|Croatia|Croatia', 89, 'Animals|Antimicrobial Cationic Peptides|Anura|Databases, Factual|Databases, Protein|Deoxyadenine Nucleotides|Peptides|Phylogeny|Skin', 'Journal Article', '10.1093/bioinformatics/bts141', '22467909', 'Anuran tissues, and especially skin, are a rich source of bioactive peptides and their precursors. We here present a manually curated database of antimicrobial and other defense peptides with a total of 2571 entries, most of them in the precursor form with demarcated signal peptide (SP), acidic proregion(s) and bioactive moiety(s) corresponding to 1923 non-identical bioactive sequences. Search functions on the corresponding web server facilitate the extraction of six distinct SP classes. The more conserved of these can be used for searching cDNA and UniProtKB databases for potential bioactive peptides, for creating PROSITE search patterns, and for phylogenetic analysis.'),
(76822, 2012, 'bio', 'AutoLabDB: a substantial open source database schema to support a high-throughput automated laboratory', 'Sparkes, Andrew|Clare, Amanda', 'Department of Computer Science, Aberystwyth University, Penglais, Aberystwyth, SY23 3DB, UK.|Department of Computer Science, Aberystwyth University, Penglais, Aberystwyth, SY23 3DB, UK.', 'United Kingdom|United Kingdom', 6, 'Automation, Laboratory|Databases, Factual|High-Throughput Screening Assays|Laboratories|Management Information Systems|Systems Biology', 'Journal Article', '10.1093/bioinformatics/bts140', '22467910', 'Modern automated laboratories need substantial data management solutions to both store and make accessible the details of the experiments they perform. To be useful, a modern Laboratory Information Management System (LIMS) should be flexible and easily extensible to support evolving laboratory requirements, and should be based on the solid foundations of a robust, well-designed database. We have developed such a database schema to support an automated laboratory that performs experiments in systems biology and high-throughput screening.'),
(76823, 2012, 'bio', 'Inferring gene regulatory networks by ANOVA', 'Kxc3xbcffner, Robert|Petri, Tobias|Tavakkolkhah, Pegah|Windhager, Lukas|Zimmer, Ralf', 'Department of Informatics, Ludwig-Maximilians University, Amalienstr. 17, 80333 Munich, Germany. kueffner@bio.ifi.lmu.de|Department of Informatics, Ludwig-Maximilians University, Amalienstr. 17, 80333 Munich, Germany. kueffner@bio.ifi.lmu.de|Department of Informatics, Ludwig-Maximilians University, Amalienstr. 17, 80333 Munich, Germany. kueffner@bio.ifi.lmu.de|Department of Informatics, Ludwig-Maximilians University, Amalienstr. 17, 80333 Munich, Germany. kueffner@bio.ifi.lmu.de|Department of Informatics, Ludwig-Maximilians University, Amalienstr. 17, 80333 Munich, Germany. kueffner@bio.ifi.lmu.de', 'Germany|Germany|Germany|Germany|Germany', 64, 'Analysis of Variance|Escherichia coli|Gene Expression Profiling|Gene Regulatory Networks|Saccharomyces cerevisiae|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bts143', '22467911', 'To improve the understanding of molecular regulation events, various approaches have been developed for deducing gene regulatory networks from mRNA expression data.'),
(76824, 2012, 'bio', 'Reno: regularized non-parametric analysis of protein lysate array data', 'Li, Bin|Liang, Feng|Hu, Jianhua|He, And Xuming', 'Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA.|Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA.|Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA.|Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA.', 'United States|United States|United States|United States', 2, 'Algorithms|Cell Line, Tumor|Humans|Neoplasms|Protein Array Analysis|Proteins|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/bts131', '22467912', 'The reverse-phase protein lysate arrays have been used to quantify the relative expression levels of a protein in a number of cellular samples simultaneously. To avoid quantification bias due to mis-specification of commonly used parametric models, a nonparametric approach based on monotone response curves may be used. The existing methods, however, aggregate the protein concentration levels of replicates of each sample, and therefore fail to account for within-sample variability.'),
(76825, 2012, 'bio', 'Penalized logistic regression for high-dimensional DNA methylation data with case-control studies', 'Sun, Hokeun|Wang, Shuang', 'Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.|Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.', 'United States|United States', 52, 'Case-Control Studies|Computer Simulation|CpG Islands|DNA Methylation|Female|Gene Expression Regulation, Neoplastic|Genetic Predisposition to Disease|Humans|Logistic Models|Ovarian Neoplasms', 'Journal Article', '10.1093/bioinformatics/bts145', '22467913', 'DNA methylation is a molecular modification of DNA that plays crucial roles in regulation of gene expression. Particularly, CpG rich regions are frequently hypermethylated in cancer tissues, but not methylated in normal tissues. However, there are not many methodological literatures of case-control association studies for high-dimensional DNA methylation data, compared with those of microarray gene expression. One key feature of DNA methylation data is a grouped structure among CpG sites from a gene that are possibly highly correlated. In this article, we proposed a penalized logistic regression model for correlated DNA methylation CpG sites within genes from high-dimensional array data. Our regularization procedure is based on a combination of the l(1) penalty and squared l(2) penalty on degree-scaled differences of coefficients of CpG sites within one gene, so it induces both sparsity and smoothness with respect to the correlated regression coefficients. We combined the penalized procedure with a stability selection procedure such that a selection probability of each regression coefficient was provided which helps us make a stable and confident selection of methylation CpG sites that are possibly truly associated with the outcome.'),
(76826, 2012, 'bio', 'Predicting giant transmembrane xcexb2-barrel architecture', 'Reboul, Cyril F|Mahmood, Khalid|Whisstock, James C|Dunstone, Michelle A', 'Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia.|Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia.|Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia.|Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia.', 'Australia|Australia|Australia|Australia', 18, 'Bacterial Proteins|Bacterial Toxins|Models, Molecular|Pore Forming Cytotoxic Proteins|Protein Structure, Secondary|Streptolysins', 'Journal Article', '10.1093/bioinformatics/bts152', '22467914', 'The xcexb2-barrel is a ubiquitous fold that is deployed to accomplish a wide variety of biological functions including membrane-embedded pores. Key influences of xcexb2-barrel lumen diameter include the number of xcexb2-strands (n) and the degree of shear (S), the latter value measuring the extent to which the xcexb2-sheet is tilted within the xcexb2-barrel. Notably, it has previously been reported that the shear value for small antiparallel xcexb2-barrels (nxe2x89xa424) typically ranges between n and 2n. Conversely, it has been suggested that the xcexb2-strands in giant antiparallel xcexb2-barrels, such as those formed by pore forming cholesterol-dependent cytolysins (CDC), are parallel relative to the axis of the xcexb2-barrel, i.e. S=0. The S=0 arrangement, however, has never been observed in crystal structures of small xcexb2-barrels. Therefore, the structural basis for how CDCs form a xcexb2-barrel and span a membrane remains to be understood.'),
(76827, 2012, 'bio', 'DeOri: a database of eukaryotic DNA replication origins', 'Gao, Feng|Luo, Hao|Zhang, Chun-Ting', 'Department of Physics, Tianjin University, Tianjin, China.|Department of Physics, Tianjin University, Tianjin, China.|Department of Physics, Tianjin University, Tianjin, China.', 'China|China|China', 16, 'Animals|DNA Replication|Databases, Genetic|Eukaryota|Genome, Fungal|Genome-Wide Association Study|Humans|Mice|Replication Origin|Schizosaccharomyces', 'Journal Article', '10.1093/bioinformatics/bts151', '22467915', 'DNA replication, a central event for cell proliferation, is the basis of biological inheritance. The identification of replication origins helps to reveal the mechanism of the regulation of DNA replication. However, only few eukaryotic replication origins were characterized not long ago, nevertheless, recent genome-wide approaches have boosted the number of mapped replication origins. To gain a comprehensive understanding of the nature of eukaryotic replication origins, we have constructed a Database of Eukaryotic ORIs (DeOri), which contains all the eukaryotic ones identified by genome-wide analyses currently available. A total of 16 145 eukaryotic replication origins have been collected from 6 eukaryotic organisms in which genome-wide studies have been performed, the replication-origin numbers being 433, 7489, 1543, 148, 348 and 6184 for humans, mice, Arabidopsis thaliana, Kluyveromyces lactis, Schizosaccharomyces pombe and Drosophila melanogaster, respectively.'),
(76828, 2012, 'bio', 'Large-scale analysis of conserved rare codon clusters suggests an involvement in co-translational molecular recognition events', 'Chartier, Matthieu|Gaudreault, Francis|Najmanovich, Rafael', 'Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 12e Avenue Nord, Sherbrooke, Québec, Canada.|Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 12e Avenue Nord, Sherbrooke, Québec, Canada.|Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 12e Avenue Nord, Sherbrooke, Québec, Canada.', 'Canada|Canada|Canada', 30, 'Algorithms|Bacteria|Bacteriophages|Cluster Analysis|Codon|Protein Biosynthesis|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts149', '22467916', 'An increasing amount of evidence from experimental and computational analysis suggests that rare codon clusters are functionally important for protein activity. Most of the studies on rare codon clusters were performed on a limited number of proteins or protein families. In the present study, we present the Sherlocc program and how it can be used for large scale protein family analysis of evolutionarily conserved rare codon clusters and their relation to protein function and structure. This large-scale analysis was performed using the whole Pfam database covering over 70% of the known protein sequence universe. Our program Sherlocc, detects statistically relevant conserved rare codon clusters and produces a user-friendly HTML output.'),
(76829, 2012, 'bio', 'MageComet--web application for harmonizing existing large-scale experiment descriptions', 'Xue, Vincent|Burdett, Tony|Lukk, Margus|Taylor, Julie|Brazma, Alvis|Parkinson, Helen', 'Department of Computer Science, Hunter College, City University of New York, NY 10065, USA. xue.vin@gmail.com|Department of Computer Science, Hunter College, City University of New York, NY 10065, USA. xue.vin@gmail.com|Department of Computer Science, Hunter College, City University of New York, NY 10065, USA. xue.vin@gmail.com|Department of Computer Science, Hunter College, City University of New York, NY 10065, USA. xue.vin@gmail.com|Department of Computer Science, Hunter College, City University of New York, NY 10065, USA. xue.vin@gmail.com|Department of Computer Science, Hunter College, City University of New York, NY 10065, USA. xue.vin@gmail.com', 'United States|United States|United States|United States|United States|United States', 1, 'Data Mining|Databases, Genetic|Internet|Meta-Analysis as Topic|Molecular Sequence Annotation|Transcriptome', 'Journal Article', '10.1093/bioinformatics/bts148', '22474121', 'Meta-analysis of large gene expression datasets obtained from public repositories requires consistently annotated data. Curation of such experiments, however, is an expert activity which involves repetitive manipulation of text. Existing tools for automated curation are few, which bottleneck the analysis pipeline.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76830, 2012, 'bio', 'CONTRA: copy number analysis for targeted resequencing', 'Li, Jason|Lupat, Richard|Amarasinghe, Kaushalya C|Thompson, Ella R|Doyle, Maria A|Ryland, Georgina L|Tothill, Richard W|Halgamuge, Saman K|Campbell, Ian G|Gorringe, Kylie L', 'Bioinformatics Core Facility, Peter MacCallum Cancer Centre, VIC 3002, Australia. Jason.Li@petermac.org|Bioinformatics Core Facility, Peter MacCallum Cancer Centre, VIC 3002, Australia. Jason.Li@petermac.org|Bioinformatics Core Facility, Peter MacCallum Cancer Centre, VIC 3002, Australia. Jason.Li@petermac.org|Bioinformatics Core Facility, Peter MacCallum Cancer Centre, VIC 3002, Australia. Jason.Li@petermac.org|Bioinformatics Core Facility, Peter MacCallum Cancer Centre, VIC 3002, Australia. Jason.Li@petermac.org|Bioinformatics Core Facility, Peter MacCallum Cancer Centre, VIC 3002, Australia. Jason.Li@petermac.org|Bioinformatics Core Facility, Peter MacCallum Cancer Centre, VIC 3002, Australia. Jason.Li@petermac.org|Bioinformatics Core Facility, Peter MacCallum Cancer Centre, VIC 3002, Australia. Jason.Li@petermac.org|Bioinformatics Core Facility, Peter MacCallum Cancer Centre, VIC 3002, Australia. Jason.Li@petermac.org|Bioinformatics Core Facility, Peter MacCallum Cancer Centre, VIC 3002, Australia. Jason.Li@petermac.org', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 192, 'Animals|Computer Simulation|DNA Copy Number Variations|Exome|HapMap Project|Humans|Mice|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts146', '22474122', 'In light of the increasing adoption of targeted resequencing (TR) as a cost-effective strategy to identify disease-causing variants, a robust method for copy number variation (CNV) analysis is needed to maximize the value of this promising technology.'),
(76831, 2012, 'bio', 'Rknots: topological analysis of knotted biopolymers with R', 'Comoglio, Federico|Rinaldi, Maurizio', 'Department of Biosystems Science and Engineering, ETH Zurich, Basel, CH-4058, Switzerland. federico.comoglio@bsse.ethz.ch|Department of Biosystems Science and Engineering, ETH Zurich, Basel, CH-4058, Switzerland. federico.comoglio@bsse.ethz.ch', 'Switzerland|Switzerland', 4, 'Algorithms|Biopolymers|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts160', '22492311', 'Rknots is a flexible R package providing tools for the detection and characterization of topological knots in biological polymers. The package is well documented and provides a simple syntax for data import and preprocessing, structure reduction, topological analyses and 2D and 3D visualization. Remarkably, Rknots is not limited to protein knots and allows researchers from interdisciplinary fields to analyze different topological structures and to develop simple yet fully custom pipelines.'),
(76832, 2012, 'bio', 'LOESS correction for length variation in gene set-based genomic sequence analysis', 'Aboukhalil, Anton|Bulyk, Martha L', 'Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.|Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.', 'United States|United States', 2, 'Algorithms|Animals|DNA|Drosophila melanogaster|Protein Structure, Tertiary|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bts155', '22492312', 'Sequence analysis algorithms are often applied to sets of DNA, RNA or protein sequences to identify common or distinguishing features. Controlling for sequence length variation is critical to properly score sequence features and identify true biological signals rather than length-dependent artifacts.'),
(76833, 2012, 'bio', 'Approximate probabilistic analysis of biopathway dynamics', 'Liu, Bing|Hagiescu, Andrei|Palaniappan, Sucheendra K|Chattopadhyay, Bipasa|Cui, Zheng|Wong, Weng-Fai|Thiagarajan, P S', 'Department of Computer Science, National University of Singapore, Singapore.|Department of Computer Science, National University of Singapore, Singapore.|Department of Computer Science, National University of Singapore, Singapore.|Department of Computer Science, National University of Singapore, Singapore.|Department of Computer Science, National University of Singapore, Singapore.|Department of Computer Science, National University of Singapore, Singapore.|Department of Computer Science, National University of Singapore, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 15, 'Algorithms|Bayes Theorem|Biological Clocks|Computer Graphics|Epidermal Growth Factor|Humans|Models, Biological|Monte Carlo Method|Myosin Light Chains|Nerve Growth Factor|Programming Languages|Signal Transduction|Software|Systems Biology|Thrombin', 'Journal Article', '10.1093/bioinformatics/bts166', '22492313', 'Biopathways are often modeled as systems of ordinary differential equations (ODEs). Such systems will usually have many unknown parameters and hence will be difficult to calibrate. Since the data available for calibration will have limited precision, an approximate representation of the ODEs dynamics should suffice. One must, however, be able to efficiently construct such approximations for large models and perform model calibration and subsequent analysis.'),
(76834, 2012, 'bio', 'Eoulsan: a cloud computing-based framework facilitating high throughput sequencing analyses', 'Jourdren, Laurent|Bernard, Maria|Dillies, Marie-Agnès|Le Crom, Stéphane', 'École normale supérieure, Institut de Biologie de lENS, INSERM U1024, Paris, France. eoulsan@biologie.ens.fr|École normale supérieure, Institut de Biologie de lENS, INSERM U1024, Paris, France. eoulsan@biologie.ens.fr|École normale supérieure, Institut de Biologie de lENS, INSERM U1024, Paris, France. eoulsan@biologie.ens.fr|École normale supérieure, Institut de Biologie de lENS, INSERM U1024, Paris, France. eoulsan@biologie.ens.fr', 'France|France|France|France', 83, 'Algorithms|Animals|Computational Biology|High-Throughput Nucleotide Sequencing|Mice|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts165', '22492314', 'We developed a modular and scalable framework called Eoulsan, based on the Hadoop implementation of the MapReduce algorithm dedicated to high-throughput sequencing data analysis. Eoulsan allows users to easily set up a cloud computing cluster and automate the analysis of several samples at once using various software solutions available. Our tests with Amazon Web Services demonstrated that the computation cost is linear with the number of instances booked as is the running time with the increasing amounts of data.'),
(76835, 2012, 'bio', 'Rigorous assessment of gene set enrichment tests', 'Naeem, Haroon|Zimmer, Ralf|Tavakkolkhah, Pegah|Küffner, Robert', 'Department of Informatics, Ludwig-Maximilians Universität, Amalienstrasse 17, Munich, Germany.|Department of Informatics, Ludwig-Maximilians Universität, Amalienstrasse 17, Munich, Germany.|Department of Informatics, Ludwig-Maximilians Universität, Amalienstrasse 17, Munich, Germany.|Department of Informatics, Ludwig-Maximilians Universität, Amalienstrasse 17, Munich, Germany.', 'Germany|Germany|Germany|Germany', 18, 'Escherichia coli|Gene Expression Profiling|Gene Regulatory Networks|Humans|MicroRNAs|Saccharomyces cerevisiae|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bts164', '22492315', 'Several statistical tests are available to detect the enrichment of differential expression in gene sets. Such tests were originally proposed for analyzing gene sets associated with biological processes. The objective evaluation of tests on real measurements has not been possible as it is difficult to decide a priori, which processes will be affected in given experiments.'),
(76836, 2012, 'bio', 'On the calculation of signal transduction ability of signaling transduction pathways in intracellular communication: systematic approach', 'Chen, Bor-Sen|Wu, Chia-Chou', 'Department of Electrical Engineering, Laboratory of Control and Systems Biology, National Tsing Hua University, Hsinchu, Taiwan, ROC. bschen@ee.nthu.edu.tw|Department of Electrical Engineering, Laboratory of Control and Systems Biology, National Tsing Hua University, Hsinchu, Taiwan, ROC. bschen@ee.nthu.edu.tw', '-|-', 0, 'Cell Communication|Computational Biology|Fuzzy Logic|MAP Kinase Signaling System|NF-kappa B|Nonlinear Dynamics|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/bts159', '22492637', 'The major function of signal transduction pathways in cells is to sense signals from the environment and process the information through signaling molecules in order to regulate the activity of transcription factors. On the molecular level, the information transmitted by a small number of signal molecules is amplified in the internal signaling pathway through enzyme catalysis, molecular modification and via the activation or inhibition of interactions. However, the dynamic system behavior of a signaling pathway can be complex and, despite knowledge of the pathway components and interactions, it is still a challenge to interpret the pathways behavior. Therefore, a systematic method is proposed in this study to quantify the signal transduction ability.'),
(76837, 2012, 'bio', 'Detection of differentially expressed segments in tiling array data', 'Otto, Christian|Reiche, Kristin|Hackermüller, Jörg', 'Bioinformatics Group, Department of Computer Science and Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany.|Bioinformatics Group, Department of Computer Science and Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany.|Bioinformatics Group, Department of Computer Science and Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany.', 'Germany|Germany|Germany', 9, 'Exons|Genome, Human|Genome-Wide Association Study|Humans|Introns|Oligonucleotide Array Sequence Analysis|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/bts142', '22492638', 'Tiling arrays have been a mainstay of unbiased genome-wide transcriptomics over the last decade. Currently available approaches to identify expressed or differentially expressed segments in tiling array data are limited in the recovery of the underlying gene structures and require several parameters that are intensity-related or partly dataset-specific.'),
(76838, 2012, 'bio', 'Fast protein binding site comparisons using visual words representation', 'Pang, Bin|Zhao, Nan|Korkin, Dmitry|Shyu, Chi-Ren', 'Informatics Institute, University of Missouri, Columbia, MO 65211, USA.|Informatics Institute, University of Missouri, Columbia, MO 65211, USA.|Informatics Institute, University of Missouri, Columbia, MO 65211, USA.|Informatics Institute, University of Missouri, Columbia, MO 65211, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Area Under Curve|Binding Sites|Cluster Analysis|Databases, Protein|Protein Binding|Proteins|Vocabulary', 'Journal Article', '10.1093/bioinformatics/bts138', '22492639', 'Finding geometrically similar protein binding sites is crucial for understanding protein functions and can provide valuable information for protein-protein docking and drug discovery. As the number of known protein-protein interaction structures has dramatically increased, a high-throughput and accurate protein binding site comparison method is essential. Traditional alignment-based methods can provide accurate correspondence between the binding sites but are computationally expensive.'),
(76839, 2012, 'bio', 'PaGeFinder: quantitative identification of spatiotemporal pattern genes', 'Pan, Jian-Bo|Hu, Shi-Chang|Wang, Hao|Zou, Quan|Ji, Zhi-Liang', 'Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, School of Life Sciences, Xiamen University, Xiamen, Fujian, P R China.|Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, School of Life Sciences, Xiamen University, Xiamen, Fujian, P R China.|Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, School of Life Sciences, Xiamen University, Xiamen, Fujian, P R China.|Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, School of Life Sciences, Xiamen University, Xiamen, Fujian, P R China.|Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, School of Life Sciences, Xiamen University, Xiamen, Fujian, P R China.', 'China|China|China|China|China', 36, 'Animals|Gene Expression Profiling|Genes, Essential|Humans|Organ Specificity', 'Journal Article', '10.1093/bioinformatics/bts169', '22492640', 'Pattern Gene Finder (PaGeFinder) is a web-based server for on-line detection of gene expression patterns from serial transcriptomic data generated by high-throughput technologies like microarray or next-generation sequencing. Three particular parameters, the specificity measure, the dispersion measure and the contribution measure, were introduced and implemented in PaGeFinder to help quantitative and interactive identification of pattern genes like housekeeping genes, specific (selective) genes and repressed genes. Besides the on-line computation service, the PaGeFinder also provides downloadable Java programs for local detection of gene expression patterns.'),
(76840, 2012, 'bio', 'Differential variability improves the identification of cancer risk markers in DNA methylation studies profiling precursor cancer lesions', 'Teschendorff, Andrew E|Widschwendter, Martin', 'Statistical Genomics Group, Paul OGorman Building, UCL Cancer Institute, University College London, 72 Huntley Street, London, UK. a.teschendorff@ucl.ac.uk|Statistical Genomics Group, Paul OGorman Building, UCL Cancer Institute, University College London, 72 Huntley Street, London, UK. a.teschendorff@ucl.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Breast Neoplasms|Cervical Intraepithelial Neoplasia|DNA Methylation|Female|Genetic Markers|Humans|Papillomavirus Infections|Precancerous Conditions|Randomized Controlled Trials as Topic|Risk|Transcriptome|Uterine Cervical Neoplasms', 'Journal Article', '10.1093/bioinformatics/bts170', '22492641', 'The standard paradigm in omic disciplines has been to identify biologically relevant biomarkers using statistics that reflect differences in mean levels of a molecular quantity such as mRNA expression or DNA methylation. Recently, however, it has been proposed that differential epigenetic variability may mark genes that contribute to the risk of complex genetic diseases like cancer and that identification of risk and early detection markers may therefore benefit from statistics based on differential variability.'),
(76841, 2012, 'bio', 'GRASS: a generic algorithm for scaffolding next-generation sequencing assemblies', 'Gritsenko, Alexey A|Nijkamp, Jurgen F|Reinders, Marcel J T|de Ridder, Dick', 'The Delft Bioinformatics Lab, Department of Mediamatics, Delft University of Technology, Mekelweg 4, Delft. a.gritsenko@tudelft.nl|The Delft Bioinformatics Lab, Department of Mediamatics, Delft University of Technology, Mekelweg 4, Delft. a.gritsenko@tudelft.nl|The Delft Bioinformatics Lab, Department of Mediamatics, Delft University of Technology, Mekelweg 4, Delft. a.gritsenko@tudelft.nl|The Delft Bioinformatics Lab, Department of Mediamatics, Delft University of Technology, Mekelweg 4, Delft. a.gritsenko@tudelft.nl', '-|-|-|-', 0, 'Algorithms|Contig Mapping|Escherichia coli|Genome, Bacterial|High-Throughput Nucleotide Sequencing|Pseudomonas syringae|Sequence Analysis, DNA|Xanthomonadaceae', 'Journal Article', '10.1093/bioinformatics/bts175', '22492642', 'The increasing availability of second-generation high-throughput sequencing (HTS) technologies has sparked a growing interest in de novo genome sequencing. This in turn has fueled the need for reliable means of obtaining high-quality draft genomes from short-read sequencing data. The millions of reads usually involved in HTS experiments are first assembled into longer fragments called contigs, which are then scaffolded, i.e. ordered and oriented using additional information, to produce even longer sequences called scaffolds. Most existing scaffolders of HTS genome assemblies are not suited for using information other than paired reads to perform scaffolding. They use this limited information to construct scaffolds, often preferring scaffold length over accuracy, when faced with the tradeoff.'),
(76842, 2012, 'bio', 'Metab2MeSH: annotating compounds with medical subject headings', 'Sartor, Maureen A|Ade, Alex|Wright, Zach|States, David|Omenn, Gilbert S|Athey, Brian|Karnovsky, Alla', 'National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI 48109, USA.|National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI 48109, USA.|National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI 48109, USA.|National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI 48109, USA.|National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI 48109, USA.|National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI 48109, USA.|National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI 48109, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Databases, Chemical|Databases, Genetic|Humans|Medical Subject Headings|Metabolomics|Neoplasms|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts156', '22492643', 'Progress in high-throughput genomic technologies has led to the development of a variety of resources that link genes to functional information contained in the biomedical literature. However, tools attempting to link small molecules to normal and diseased physiology and published data relevant to biologists and clinical investigators, are still lacking. With metabolomics rapidly emerging as a new omics field, the task of annotating small molecule metabolites becomes highly relevant. Our tool Metab2MeSH uses a statistical approach to reliably and automatically annotate compounds with concepts defined in Medical Subject Headings, and the National Library of Medicines controlled vocabulary for biomedical concepts. These annotations provide links from compounds to biomedical literature and complement existing resources such as PubChem and the Human Metabolome Database.'),
(76843, 2012, 'bio', 'A comprehensive computational model of facilitated diffusion in prokaryotes', 'Zabet, Nicolae Radu|Adryan, Boris', 'Cambridge Systems Biology Centre, University of Cambridge, Tennis Court Road, Cambridge, UK. n.r.zabet@gen.cam.ac.uk|Cambridge Systems Biology Centre, University of Cambridge, Tennis Court Road, Cambridge, UK. n.r.zabet@gen.cam.ac.uk', 'United Kingdom|United Kingdom', 0, 'Computer Simulation|DNA|Escherichia coli|Facilitated Diffusion|Lac Repressors|Models, Chemical|Thermodynamics|Transcriptional Activation', 'Journal Article', '10.1093/bioinformatics/bts178', '22492644', 'Gene activity is mediated by site-specific transcription factors (TFs). Their binding to defined regions in the genome determines the rate at which their target genes are transcribed.'),
(76844, 2012, 'bio', 'PhyLAT: a phylogenetic local alignment tool', 'Sun, Hongtao|Buhler, Jeremy D', 'Department of Computer Science and Engineering, Washington University, Saint Louis, MO 63130, USA. sunhongtao@wustl.edu|Department of Computer Science and Engineering, Washington University, Saint Louis, MO 63130, USA. sunhongtao@wustl.edu', 'United States|United States', 4, 'Animals|Artificial Intelligence|Biological Evolution|Databases, Genetic|Genome|Humans|Opossums|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts158', '22492645', 'The expansion of DNA sequencing capacity has enabled the sequencing of whole genomes from a number of related species. These genomes can be combined in a multiple alignment that provides useful information about the evolutionary history at each genomic locus. One area in which evolutionary information can productively be exploited is in aligning a new sequence to a database of existing, aligned genomes. However, existing high-throughput alignment tools are not designed to work effectively with multiple genome alignments.'),
(76845, 2012, 'bio', 'CRNreals: a toolbox for distinguishability and identifiability analysis of biochemical reaction networks', 'Szederkényi, Gábor|Banga, Julio R|Alonso, Antonio A', '(Bio)Process Engineering Group, IIM-CSIC, Spanish National Research Council, C/Eduardo Cabello 6, Vigo, Spain. szeder@scl.sztaki.hu.|(Bio)Process Engineering Group, IIM-CSIC, Spanish National Research Council, C/Eduardo Cabello 6, Vigo, Spain. szeder@scl.sztaki.hu.|(Bio)Process Engineering Group, IIM-CSIC, Spanish National Research Council, C/Eduardo Cabello 6, Vigo, Spain. szeder@scl.sztaki.hu.', 'Spain|Spain|Spain', 0, 'Animals|Humans|Metabolic Networks and Pathways|Signal Transduction|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/bts171', '22492646', 'Chemical reaction network theory is widely used in modeling and analyzing complex biochemical systems such as metabolic networks and cell signalling pathways. Being able to produce all the biologically and chemically important qualitative dynamical features, chemical reaction networks (CRNs) have attracted significant attention in the systems biology community. It is well-known that the reliable inference of CRN models generally requires thorough identifiability and distinguishability analysis together with carefully selected prior modeling assumptions. Here, we present a software toolbox CRNreals that supports the distinguishability and identifiability analysis of CRN models using recently published optimization-based procedures.'),
(76846, 2012, 'bio', 'Bayesian integration of networks without gold standards', 'Weile, Jochen|James, Katherine|Hallinan, Jennifer|Cockell, Simon J|Lord, Phillip|Wipat, Anil|Wilkinson, Darren J', 'Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.|Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.|Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.|Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.|Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.|Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.|Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 9, 'Algorithms|Bayes Theorem|Epistasis, Genetic|Likelihood Functions|Protein Interaction Mapping|Saccharomyces cerevisiae', 'Journal Article', '10.1093/bioinformatics/bts154', '22492647', 'Biological experiments give insight into networks of processes inside a cell, but are subject to error and uncertainty. However, due to the overlap between the large number of experiments reported in public databases it is possible to assess the chances of individual observations being correct. In order to do so, existing methods rely on high-quality gold standard reference networks, but such reference networks are not always available.'),
(76847, 2012, 'bio', 'Matrix eQTL: ultra fast eQTL analysis via large matrix operations', 'Shabalin, Andrey A', 'Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. shabalin@email.unc.edu', 'United States', 543, 'Algorithms|Cystic Fibrosis|Gene Expression|Genotype|Humans|Models, Genetic|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Software', 'Journal Article', '10.1093/bioinformatics/bts163', '22492648', 'Expression quantitative trait loci (eQTL) analysis links variations in gene expression levels to genotypes. For modern datasets, eQTL analysis is a computationally intensive task as it involves testing for association of billions of transcript-SNP (single-nucleotide polymorphism) pair. The heavy computational burden makes eQTL analysis less popular and sometimes forces analysts to restrict their attention to just a small subset of transcript-SNP pairs. As more transcripts and SNPs get interrogated over a growing number of samples, the demand for faster tools for eQTL analysis grows stronger.'),
(76848, 2012, 'bio', 'Estimating the order of mutations during tumorigenesis from tumor genome sequencing data', 'Youn, Ahrim|Simon, Richard', 'Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, MSC 7434, Bethesda, MD 20892-7434, USA.|Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, MSC 7434, Bethesda, MD 20892-7434, USA.', 'United States|United States', 14, 'Cell Transformation, Neoplastic|Colonic Neoplasms|Computational Biology|DNA Mutational Analysis|Genes, Neoplasm|Genomics|Humans|Lung Neoplasms|Models, Statistical|Mutation|Software', 'Journal Article', '10.1093/bioinformatics/bts168', '22492649', 'Tumors are thought to develop and evolve through a sequence of genetic and epigenetic somatic alterations to progenitor cells. Early stages of human tumorigenesis are hidden from view. Here, we develop a method for inferring some aspects of the order of mutational events during tumorigenesis based on genome sequencing data for a set of tumors. This method does not assume that the sequence of driver alterations is the same for each tumor, but enables the degree of similarity or difference in the sequence to be evaluated.'),
(76849, 2012, 'bio', 'A de novo metagenomic assembly program for shotgun DNA reads', 'Lai, Binbin|Ding, Ruogu|Li, Yang|Duan, Liping|Zhu, Huaiqiu', 'State Key Lab for Turbulence and Complex Systems and Department of Biomedical Engineering, College of Engineering, Center for Theoretical Biology, Center for Protein Science, Peking University, Beijing, China.|State Key Lab for Turbulence and Complex Systems and Department of Biomedical Engineering, College of Engineering, Center for Theoretical Biology, Center for Protein Science, Peking University, Beijing, China.|State Key Lab for Turbulence and Complex Systems and Department of Biomedical Engineering, College of Engineering, Center for Theoretical Biology, Center for Protein Science, Peking University, Beijing, China.|State Key Lab for Turbulence and Complex Systems and Department of Biomedical Engineering, College of Engineering, Center for Theoretical Biology, Center for Protein Science, Peking University, Beijing, China.|State Key Lab for Turbulence and Complex Systems and Department of Biomedical Engineering, College of Engineering, Center for Theoretical Biology, Center for Protein Science, Peking University, Beijing, China.', 'China|China|China|China|China', 32, 'Algorithms|Contig Mapping|High-Throughput Nucleotide Sequencing|Metagenomics|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts162', '22495746', 'A high-quality assembly of reads generated from shotgun sequencing is a substantial step in metagenome projects. Although traditional assemblers have been employed in initial analysis of metagenomes, they cannot surmount the challenges created by the features of metagenomic data.'),
(76850, 2012, 'bio', 'Ligand-binding site prediction using ligand-interacting and binding site-enriched protein triangles', 'Xie, Zhong-Ru|Hwang, Ming-Jing', 'Institute of Biomedical Informatics, National Yang-Ming University, Taipei 112, Taiwan.|Institute of Biomedical Informatics, National Yang-Ming University, Taipei 112, Taiwan.', '-|-', 18, 'Algorithms|Binding Sites|Computational Biology|Internet|Ligands|Models, Molecular|Protein Binding|Protein Structure, Tertiary|Proteins', 'Comparative Study', '10.1093/bioinformatics/bts182', '22495747', 'Knowledge about the site at which a ligand binds provides an important clue for predicting the function of a protein and is also often a prerequisite for performing docking computations in virtual drug design and screening. We have previously shown that certain ligand-interacting triangles of protein atoms, called protein triangles, tend to occur more frequently at ligand-binding sites than at other parts of the protein.'),
(76851, 2012, 'bio', 'Ranking viruses: measures of positional importance within networks define core viruses for rational polyvalent vaccine development', 'Anderson, Tavis K|Laegreid, William W|Cerutti, Francesco|Osorio, Fernando A|Nelson, Eric A|Christopher-Hennings, Jane|Goldberg, Tony L', 'Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI 53706, USA.|Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI 53706, USA.|Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI 53706, USA.|Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI 53706, USA.|Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI 53706, USA.|Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI 53706, USA.|Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI 53706, USA.', 'United States|United States|United States|United States|United States|United States|United States', 14, 'Algorithms|Antigenic Variation|Computational Biology|Epitopes, T-Lymphocyte|Porcine respiratory and reproductive syndrome virus|RNA Viruses|Viral Envelope Proteins', 'Journal Article', '10.1093/bioinformatics/bts181', '22495748', 'The extraordinary genetic and antigenic variability of RNA viruses is arguably the greatest challenge to the development of broadly effective vaccines. No single viral variant can induce sufficiently broad immunity, and incorporating all known naturally circulating variants into one multivalent vaccine is not feasible. Furthermore, no objective strategies currently exist to select actual viral variants that should be included or excluded in polyvalent vaccines.'),
(76852, 2012, 'bio', 'CheShift-2: graphic validation of protein structures', 'Martin, Osvaldo A|Vila, Jorge A|Scheraga, Harold A', 'Universidad Nacional de San Luis, IMASL-CONICET, Ejxc3xa9rcito de Los Andes, San Luis, Argentina.|Universidad Nacional de San Luis, IMASL-CONICET, Ejxc3xa9rcito de Los Andes, San Luis, Argentina.|Universidad Nacional de San Luis, IMASL-CONICET, Ejxc3xa9rcito de Los Andes, San Luis, Argentina.', 'Argentina|Argentina|Argentina', 13, 'Animals|Cattle|Crystallography, X-Ray|Cytochromes b5|Dyneins|Histidine|Internet|Models, Molecular|Protein Conformation|Proteins|Rabbits|Rats|Software', 'Journal Article', '10.1093/bioinformatics/bts179', '22495749', 'The differences between observed and predicted (13)C(xcexb1) chemical shifts can be used as a sensitive probe with which to detect possible local flaws in protein structures. For this reason, we previously introduced CheShift, a Web server for protein structure validation. Now, we present CheShift-2 in which a graphical user interface is implemented to render such local flaws easily visible. A series of applications to 15 ensembles of conformations illustrate the ability of CheShift-2 to locate the main structural flaws rapidly and accurately on a per-residue basis. Since accuracy plays a central role in CheShift predictions, the treatment of histidine (His) is investigated here by exploring which form of His should be used in CheShift-2.'),
(76853, 2012, 'bio', 'ape 30: New tools for distance-based phylogenetics and evolutionary analysis in R', 'Popescu, Andrei-Alin|Huber, Katharina T|Paradis, Emmanuel', 'School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich, UK.|School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich, UK.|School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich, UK.', 'United Kingdom|United Kingdom|United Kingdom', 155, 'Biological Evolution|Phylogeny|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts184', '22495750', 'Reflecting its continuously increasing versatility and functionality, the popularity of the ape (analysis of phylogenetics and evolution) software package has grown steadily over the years. Among its features, it has a strong distance-based component allowing the user to compute distances from aligned DNA sequences based on most methods from the literature and also build phylogenetic trees from them. However, even data generated with modern genomic approaches can fail to give rise to sufficiently reliable distance estimates. One way to overcome this problem is to exclude such estimates from data analysis giving rise to an incomplete distance data set (as opposed to a complete one). So far their analysis has been out of reach for ape. To remedy this, we have incorporated into ape several methods from the literature for phylogenetic inference from incomplete distance matrices. In addition, we have also extended apes repertoire for phylogenetic inference from complete distances, added a new object class to efficiently encode sets of splits of taxa, and extended the functionality of some of its existing functions.'),
(76854, 2012, 'bio', 'CistromeMap: a knowledgebase and web server for ChIP-Seq and DNase-Seq studies in mouse and human', 'Qin, Bo|Zhou, Meng|Ge, Ying|Taing, Len|Liu, Tao|Wang, Qian|Wang, Su|Chen, Junsheng|Shen, Lingling|Duan, Xikun|Hu, Shengen|Li, Wei|Long, Henry|Zhang, Yong|Liu, X Shirley', 'Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092, China.', 'China|China|China|China|China|China|China|China|China|China|China|China|China|China|China', 25, 'Animals|Chromatin Immunoprecipitation|Databases, Genetic|Gene Expression Regulation|Humans|Knowledge Bases|Mice|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/bts157', '22495751', 'Transcription and chromatin regulators, and histone modifications play essential roles in gene expression regulation. We have created CistromeMap as a web server to provide a comprehensive knowledgebase of all of the publicly available ChIP-Seq and DNase-Seq data in mouse and human. We have also manually curated metadata to ensure annotation consistency, and developed a user-friendly display matrix for quick navigation and retrieval of data for specific factors, cells and papers. Finally, we provide users with summary statistics of ChIP-Seq and DNase-Seq studies.'),
(76855, 2012, 'bio', 'GeneclusterViz: a tool for conserved gene cluster visualization, exploration and analysis', 'Pejaver, Vikas R|An, Jaehyun|Rhee, Sungmin|Bhan, Ankita|Choi, Jeong-Hyeon|Liu, Boshu|Lee, Heewook|Brown, Pamela J|Kysela, David|Brun, Yves V|Kim, Sun', 'School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA.|School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA.|School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA.|School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA.|School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA.|School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA.|School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA.|School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA.|School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA.|School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA.|School of Informatics and Computing, Indiana University Bloomington, IN 47404, USA.', 'India|India|India|India|India|India|India|India|India|India|India', 5, 'Alphaproteobacteria|Cluster Analysis|Escherichia coli|Genome|Multigene Family|Phylogeny|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/bts177', '22495752', 'Gene clusters are arrangements of functionally related genes on a chromosome. In bacteria, it is expected that evolutionary pressures would conserve these arrangements due to the functional advantages they provide. Visualization of conserved gene clusters across multiple genomes provides key insights into their evolutionary histories. Therefore, a software tool that enables visualization and functional analyses of gene clusters would be a great asset to the biological research community.'),
(76856, 2012, 'bio', 'Fast and accurate inference of local ancestry in Latino populations', 'Baran, Yael|Pasaniuc, Bogdan|Sankararaman, Sriram|Torgerson, Dara G|Gignoux, Christopher|Eng, Celeste|Rodriguez-Cintron, William|Chapela, Rocio|Ford, Jean G|Avila, Pedro C|Rodriguez-Santana, Jose|Burchard, Esteban Gonzàlez|Halperin, Eran', 'The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel-Aviv 69978, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 132, 'Algorithms|European Continental Ancestry Group|Gene Flow|Genetics, Population|Haplotypes|Hispanic Americans|Humans|Indians, North American|Linkage Disequilibrium|Markov Chains|Mexico|Puerto Rico|United States', 'Journal Article', '10.1093/bioinformatics/bts144', '22495753', 'It is becoming increasingly evident that the analysis of genotype data from recently admixed populations is providing important insights into medical genetics and population history. Such analyses have been used to identify novel disease loci, to understand recombination rate variation and to detect recent selection events. The utility of such studies crucially depends on accurate and unbiased estimation of the ancestry at every genomic locus in recently admixed populations. Although various methods have been proposed and shown to be extremely accurate in two-way admixtures (e.g. African Americans), only a few approaches have been proposed and thoroughly benchmarked on multi-way admixtures (e.g. Latino populations of the Americas).'),
(76857, 2012, 'bio', 'IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth', 'Peng, Yu|Leung, Henry C M|Yiu, S M|Chin, Francis Y L', 'Department of Computer Science, The University of Hong Kong, Pokfulam Road, Hong Kong.|Department of Computer Science, The University of Hong Kong, Pokfulam Road, Hong Kong.|Department of Computer Science, The University of Hong Kong, Pokfulam Road, Hong Kong.|Department of Computer Science, The University of Hong Kong, Pokfulam Road, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong', 1226, 'Algorithms|Bacteria|Genome|High-Throughput Nucleotide Sequencing|Metagenomics|Sequence Analysis, DNA|Single-Cell Analysis', 'Journal Article', '10.1093/bioinformatics/bts174', '22495754', 'Next-generation sequencing allows us to sequence reads from a microbial environment using single-cell sequencing or metagenomic sequencing technologies. However, both technologies suffer from the problem that sequencing depth of different regions of a genome or genomes from different species are highly uneven. Most existing genome assemblers usually have an assumption that sequencing depths are even. These assemblers fail to construct correct long contigs.'),
(76858, 2012, 'bio', 'RFMapp: ribosome flow model application', 'Zur, Hadas|Tuller, Tamir', 'The Blavatnik School of Computer Science, Faculty of Exact Sciences, Tel Aviv University, Ramat Aviv 69978, Israel.|The Blavatnik School of Computer Science, Faculty of Exact Sciences, Tel Aviv University, Ramat Aviv 69978, Israel.', 'Israel|Israel', 8, 'Base Sequence|Codon|Computational Biology|Computer Graphics|Models, Molecular|Protein Biosynthesis|RNA, Messenger|Ribosomes|Saccharomyces cerevisiae|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts185', '22495755', 'The RFMapp is a graphical user interface application based on the RFM (ribosome flow model), enabling the estimation of the translation elongation rates of messenger ribonucleic acids (mRNAs) and the profile of ribosomal densities along the mRNAs, in a computationally efficient way. The RFMapp is based on the approach previously described by Reuveni et al., and unlike other traditional approaches in the field, which are mainly related to the genes mean codon translation efficiency, the RFM additionally considers the codon order, the ribosomes size and their order. Thus, it has been shown that RFM outperforms traditional predictors when analyzing both heterologous and endogenous genes.'),
(76859, 2012, 'bio', 'ChemSpot: a hybrid system for chemical named entity recognition', 'Rocktäschel, Tim|Weidlich, Michael|Leser, Ulf', 'Department of Computer Science, Humboldt-Universität zu Berlin, Rudower Chaussee 25, 12489 Berlin, Germany.|Department of Computer Science, Humboldt-Universität zu Berlin, Rudower Chaussee 25, 12489 Berlin, Germany.|Department of Computer Science, Humboldt-Universität zu Berlin, Rudower Chaussee 25, 12489 Berlin, Germany.', 'Germany|Germany|Germany', 136, 'Artificial Intelligence|Computational Biology|Dictionaries, Chemical as Topic|Information Storage and Retrieval|Natural Language Processing|Pharmaceutical Preparations|Software|Terminology as Topic', 'Journal Article', '10.1093/bioinformatics/bts183', '22500000', 'The accurate identification of chemicals in text is important for many applications, including computer-assisted reconstruction of metabolic networks or retrieval of information about substances in drug development. But due to the diversity of naming conventions and traditions for such molecules, this task is highly complex and should be supported by computational tools.'),
(76860, 2012, 'bio', 'optiCall: a robust genotype-calling algorithm for rare, low-frequency and common variants', 'Shah, T S|Liu, J Z|Floyd, J A B|Morris, J A|Wirth, N|Barrett, J C|Anderson, C A', 'Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.|Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.|Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.|Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.|Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.|Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.|Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Cluster Analysis|Genetic Association Studies|Genotype|Humans|Models, Statistical|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/bts180', '22500001', 'Existing microarray genotype-calling algorithms adopt either SNP-by-SNP (SNP-wise) or sample-by-sample (sample-wise) approaches to calling. We have developed a novel genotype-calling algorithm for the Illumina platform, optiCall, that uses both SNP-wise and sample-wise calling to more accurately ascertain genotypes at rare, low-frequency and common variants.'),
(76861, 2012, 'bio', 'Bpipe: a tool for running and managing bioinformatics pipelines', 'Sadedin, Simon P|Pope, Bernard|Oshlack, Alicia', 'Murdoch Childrens Research Institute, Royal Childrens Hospital, Flemington Road, Parkville, Victoria 3052, Australia. simon.sadedin@mcri.edu.au|Murdoch Childrens Research Institute, Royal Childrens Hospital, Flemington Road, Parkville, Victoria 3052, Australia. simon.sadedin@mcri.edu.au|Murdoch Childrens Research Institute, Royal Childrens Hospital, Flemington Road, Parkville, Victoria 3052, Australia. simon.sadedin@mcri.edu.au', 'Australia|Australia|Australia', 80, 'Computational Biology|Programming Languages|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/bts167', '22500002', 'Bpipe is a simple, dedicated programming language for defining and executing bioinformatics pipelines. It specializes in enabling users to turn existing pipelines based on shell scripts or command line tools into highly flexible, adaptable and maintainable workflows with a minimum of effort. Bpipe ensures that pipelines execute in a controlled and repeatable fashion and keeps audit trails and logs to ensure that experimental results are reproducible. Requiring only Java as a dependency, Bpipe is fully self-contained and cross-platform, making it very easy to adopt and deploy into existing environments.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(76862, 2012, 'bio', 'pIRS: Profile-based Illumina pair-end reads simulator', 'Hu, Xuesong|Yuan, Jianying|Shi, Yujian|Lu, Jianliang|Liu, Binghang|Li, Zhenyu|Chen, Yanxiang|Mu, Desheng|Zhang, Hao|Li, Nan|Yue, Zhen|Bai, Fan|Li, Heng|Fan, Wei', 'BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.|BGI-Shenzhen, Shenzhen Biodynamic Optical Imaging Center, Peking University, Beijing, China.', 'China|China|China|China|China|China|China|China|China|China|China|China|China|China', 105, 'Computer Simulation|High-Throughput Nucleotide Sequencing|Human Genome Project|Humans|Markov Chains|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts187', '22508794', 'The next-generation high-throughput sequencing technologies, especially from Illumina, have been widely used in re-sequencing and de novo assembly studies. However, there is no existing software that can simulate Illumina reads with real error and quality distributions and coverage bias yet, which is very useful in relevant software development and study designing of sequencing projects.'),
(76863, 2012, 'bio', 'Stability of gene rankings from RNAi screens', 'Siebourg, Juliane|Merdes, Gunter|Misselwitz, Benjamin|Hardt, Wolf-Dietrich|Beerenwinkel, Niko', 'Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.|Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.|Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.|Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.|Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Animals|Computational Biology|Computer Simulation|Drosophila|Gene Knockdown Techniques|Models, Statistical|RNA Interference|Reproducibility of Results', 'Comparative Study', '10.1093/bioinformatics/bts192', '22513992', 'Genome-wide RNA interference (RNAi) experiments are becoming a widely used approach for identifying intracellular molecular pathways of specific functions. However, detecting all relevant genes involved in a biological process is challenging, because typically only few samples per gene knock-down are available and readouts tend to be very noisy. We investigate the reliability of top scoring hit lists obtained from RNAi screens, compare the performance of different ranking methods, and propose a new ranking method to improve the reproducibility of gene selection.'),
(76864, 2012, 'bio', 'INRICH: interval-based enrichment analysis for genome-wide association studies', 'Lee, Phil H|ODushlaine, Colm|Thomas, Brett|Purcell, Shaun M', 'Analytic and Translational Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, MA 02114, USA.|Analytic and Translational Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, MA 02114, USA.|Analytic and Translational Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, MA 02114, USA.|Analytic and Translational Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, MA 02114, USA.', 'United States|United States|United States|United States', 0, 'Genes|Genome-Wide Association Study|Genomics|Humans|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/bts191', '22513993', 'Here we present INRICH (INterval enRICHment analysis), a pathway-based genome-wide association analysis tool that tests for enriched association signals of predefined gene-sets across independent genomic intervals. INRICH has wide applicability, fast running time and, most importantly, robustness to potential genomic biases and confounding factors. Such factors, including varying gene size and single-nucleotide polymorphism density, linkage disequilibrium within and between genes and overlapping genes with similar annotations, are often not accounted for by existing gene-set enrichment methods. By using a genomic permutation procedure, we generate experiment-wide empirical significance values, corrected for the total number of sets tested, implicitly taking overlap of sets into account. By simulation we confirm a properly controlled type I error rate and reasonable power of INRICH under diverse parameter settings. As a proof of principle, we describe the application of INRICH on the NHGRI GWAS catalog.'),
(76865, 2012, 'bio', 'TSSi--an R package for transcription start site identification from 5 mRNA tag data', 'Kreutz, C|Gehring, J S|Lang, D|Reski, R|Timmer, J|Rensing, S A', 'Institute for Physics, University of Freiburg, Germany. ckreutz@fdm.uni-freiburg.de|Institute for Physics, University of Freiburg, Germany. ckreutz@fdm.uni-freiburg.de|Institute for Physics, University of Freiburg, Germany. ckreutz@fdm.uni-freiburg.de|Institute for Physics, University of Freiburg, Germany. ckreutz@fdm.uni-freiburg.de|Institute for Physics, University of Freiburg, Germany. ckreutz@fdm.uni-freiburg.de|Institute for Physics, University of Freiburg, Germany. ckreutz@fdm.uni-freiburg.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|High-Throughput Nucleotide Sequencing|Internet|RNA, Messenger|Software|Transcription Initiation Site', 'Journal Article', '10.1093/bioinformatics/bts189', '22513994', 'High-throughput sequencing has become an essential experimental approach for the investigation of transcriptional mechanisms. For some applications like ChIP-seq, several approaches for the prediction of peak locations exist. However, these methods are not designed for the identification of transcription start sites (TSSs) because such datasets contain qualitatively different noise. In this application note, the R package TSSi is presented which provides a heuristic framework for the identification of TSSs based on 5 mRNA tag data. Probabilistic assumptions for the distribution of the data, i.e. for the observed positions of the mapped reads, as well as for systematic errors, i.e. for reads which map closely but not exactly to a real TSS, are made and can be adapted by the user. The framework also comprises a regularization procedure which can be applied as a preprocessing step to decrease the noise and thereby reduce the number of false predictions.'),
(76866, 2012, 'bio', 'NanoStringNorm: an extensible R package for the pre-processing of NanoString mRNA and miRNA data', 'Waggott, Daryl|Chu, Kenneth|Yin, Shaoming|Wouters, Bradly G|Liu, Fei-Fei|Boutros, Paul C', 'Informatics and Biocomputing Platform, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Informatics and Biocomputing Platform, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Informatics and Biocomputing Platform, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Informatics and Biocomputing Platform, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Informatics and Biocomputing Platform, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Informatics and Biocomputing Platform, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|MicroRNAs|Nanotechnology|Paraffin Embedding|RNA, Messenger|Software', 'Journal Article', '10.1093/bioinformatics/bts188', '22513995', 'The NanoString nCounter Platform is a new and promising technology for measuring nucleic acid abundances. It has several advantages over PCR-based techniques, including avoidance of amplification, direct sequence interrogation and digital detection for absolute quantification. These features minimize aspects of experimental error and hold promise for dealing with challenging experimental conditions such as archival formalin-fixed paraffin-embedded samples. However, systematic inter-sample technical artifacts caused by variability in sample preservation, bio-molecular extraction and platform fluctuations must be removed to ensure robust data.'),
(76867, 2012, 'bio', 'Automated gene-model curation using global discriminative learning', 'Bernal, Axel|Crammer, Koby|Pereira, Fernando', 'Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA 19104, USA. abernal@seas.upenn.edu|Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA 19104, USA. abernal@seas.upenn.edu|Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA 19104, USA. abernal@seas.upenn.edu', 'United States|United States|United States', 1, 'Algorithms|Animals|Arabidopsis|Artificial Intelligence|Caenorhabditis elegans|Computational Biology|Genomics|Humans|Models, Genetic', 'Journal Article', '10.1093/bioinformatics/bts176', '22513996', 'Gene-model curation creates consensus gene models by combining multiple sources of protein-coding evidence that may be incomplete or inconsistent. To date, manual curation still produces the highest quality models. However, manual curation is too slow and costly to be completed even for the most important organisms. In recent years, machine-learned ensemble gene predictors have become a viable alternative to manual curation. Current approaches make use of signal and genomic region consistency among sources and some voting scheme to resolve conflicts in the evidence. As a further step in that direction, we have developed eCRAIG (ensemble CRAIG), an automated curation tool that combines multiple sources of evidence using global discriminative training. This allows efficient integration of different types of genomic evidence with complex statistical dependencies to maximize directly annotation accuracy. Our method goes beyond previous work in integrating novel non-linear annotation agreement features, as well as combinations of intrinsic features of the target sequence and extrinsic annotation features.'),
(76868, 2012, 'bio', 'Improving GO semantic similarity measures by exploring the ontology beneath the terms and modelling uncertainty', 'Yang, Haixuan|Nepusz, Tamás|Paccanaro, Alberto', 'Department of Computer Science and Centre for Systems and Synthetic Biology, Royal Holloway, University of London, Egham, TW20 0EX, UK.|Department of Computer Science and Centre for Systems and Synthetic Biology, Royal Holloway, University of London, Egham, TW20 0EX, UK.|Department of Computer Science and Centre for Systems and Synthetic Biology, Royal Holloway, University of London, Egham, TW20 0EX, UK.', 'United Kingdom|United Kingdom|United Kingdom', 62, 'Algorithms|Molecular Sequence Annotation|Multiprotein Complexes|Proteins|Saccharomyces cerevisiae|Semantics|Terminology as Topic|Uncertainty|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts129', '22522134', 'Several measures have been recently proposed for quantifying the functional similarity between gene products according to well-structured controlled vocabularies where biological terms are organized in a tree or in a directed acyclic graph (DAG) structure. However, existing semantic similarity measures ignore two important facts. First, when calculating the similarity between two terms, they disregard the descendants of these terms. While this makes no difference when the ontology is a tree, we shall show that it has important consequences when the ontology is a DAG-this is the case, for example, with the Gene Ontology (GO). Second, existing similarity measures do not model the inherent uncertainty which comes from the fact that our current knowledge of the gene annotation and of the ontology structure is incomplete. Here, we propose a novel approach based on downward random walks that can be used to improve any of the existing similarity measures to exhibit these two properties. The approach is computationally efficient-random walks do not need to be simulated as we provide formulas to calculate their stationary distributions.'),
(76869, 2012, 'bio', 'GLOGS: a fast and powerful method for GWAS of binary traits with risk covariates in related populations', 'Stanhope, Stephen A|Abney, Mark', 'Department of Human Genetics, University of Chicago, 920 E. 58th St., Chicago, IL 60637, USA. sstanhop@bsd.uchicago.edu|Department of Human Genetics, University of Chicago, 920 E. 58th St., Chicago, IL 60637, USA. sstanhop@bsd.uchicago.edu', 'United States|United States', 6, 'Genome-Wide Association Study|Humans|Logistic Models|Models, Genetic|Phenotype|Risk', 'Journal Article', '10.1093/bioinformatics/bts190', '22522135', 'Mixed model-based approaches to genome-wide association studies (GWAS) of binary traits in related individuals can account for non-genetic risk factors in an integrated manner. However, they are technically challenging. GLOGS (Genome-wide LOGistic mixed model/Score test) addresses such challenges with efficient statistical procedures and a parallel implementation. GLOGS has high power relative to alternative approaches as risk covariate effects increase, and can complete a GWAS in minutes.'),
(76870, 2012, 'bio', 'A hybrid approach to protein differential expression in mass spectrometry-based proteomics', 'Wang, Xuan|Anderson, Gordon A|Smith, Richard D|Dabney, Alan R', 'Department of Statistics, Texas A&M University, 3143 TAMU, College Station, TX 77843, USA.|Department of Statistics, Texas A&M University, 3143 TAMU, College Station, TX 77843, USA.|Department of Statistics, Texas A&M University, 3143 TAMU, College Station, TX 77843, USA.|Department of Statistics, Texas A&M University, 3143 TAMU, College Station, TX 77843, USA.', 'United States|United States|United States|United States', 17, 'Computer Simulation|Humans|Likelihood Functions|Logistic Models|Mass Spectrometry|Proteins|Proteomics', 'Journal Article', '10.1093/bioinformatics/bts193', '22522136', 'Quantitative mass spectrometry-based proteomics involves statistical inference on protein abundance, based on the intensities of each proteins associated spectral peaks. However, typical MS-based proteomics datasets have substantial proportions of missing observations, due at least in part to censoring of low intensities. This complicates intensity-based differential expression analysis.'),
(76871, 2012, 'bio', 'Probabilistic suffix array: efficient modeling and prediction of protein families', 'Lin, Jie|Adjeroh, Donald|Jiang, Bing-Hua', 'Faculty of Software, Fujian Normal University, Fuzhou 350108, China.|Faculty of Software, Fujian Normal University, Fuzhou 350108, China.|Faculty of Software, Fujian Normal University, Fuzhou 350108, China.', 'China|China|China', 0, 'Algorithms|Markov Chains|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bts121', '22522137', 'Markov models are very popular for analyzing complex sequences such as protein sequences, whose sources are unknown, or whose underlying statistical characteristics are not well understood. A major problem is the computational complexity involved with using Markov models, especially the exponential growth of their size with the order of the model. The probabilistic suffix tree (PST) and its improved variant sparse probabilistic suffix tree (SPST) have been proposed to address some of the key problems with Markov models. The use of the suffix tree, however, implies that the space requirement for the PST/SPST could still be high.'),
(76872, 2012, 'bio', 'NuST: analysis of the interplay between nucleoid organization and gene expression', 'Scolari, Vittore F|Zarei, Mina|Osella, Matteo|Lagomarsino, Marco Cosentino', 'Genomic Physics Group, UMR 7238 CNRS Génomique des Microorganismes, Université Pierre et Marie Curie, 15 rue de LÉcole de Médecine, 75006, Paris, France. vittore.scolari@upmc.fr|Genomic Physics Group, UMR 7238 CNRS Génomique des Microorganismes, Université Pierre et Marie Curie, 15 rue de LÉcole de Médecine, 75006, Paris, France. vittore.scolari@upmc.fr|Genomic Physics Group, UMR 7238 CNRS Génomique des Microorganismes, Université Pierre et Marie Curie, 15 rue de LÉcole de Médecine, 75006, Paris, France. vittore.scolari@upmc.fr|Genomic Physics Group, UMR 7238 CNRS Génomique des Microorganismes, Université Pierre et Marie Curie, 15 rue de LÉcole de Médecine, 75006, Paris, France. vittore.scolari@upmc.fr', 'France|France|France|France', 9, 'Algorithms|Chromosomes, Bacterial|Computational Biology|Databases, Genetic|Escherichia coli|Gene Expression|Genome, Bacterial|Internet|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts201', '22531214', 'Different experimental results suggest the presence of an interplay between global transcriptional regulation and chromosome spatial organization in bacteria. The identification and clear visualization of spatial clusters of contiguous genes targeted by specific DNA-binding proteins or sensitive to nucleoid perturbations can elucidate links between nucleoid structure and gene expression patterns. Similarly, statistical analysis to assess correlations between results from independent experiments can provide the integrated analysis needed in this line of research. NuST (Nucleoid Survey tools), based on the Escherichia coli genome, gives the non-expert the possibility to analyze the aggregation of genes or loci sets along the genome coordinate, at different scales of observation. It is useful to discover correlations between different sources of data (e.g. expression, binding or genomic data) and genome organization. A user can use it on datasets in the form of gene lists coming from his/her own experiments or bioinformatic analyses, but also make use of the internal database, which collects data from many published studies.'),
(76873, 2012, 'bio', 'DelPhi web server v2: incorporating atomic-style geometrical figures into the computational protocol', 'Smith, Nicholas|Witham, Shawn|Sarkar, Subhra|Zhang, Jie|Li, Lin|Li, Chuan|Alexov, Emil', 'Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA. nsmith@clemson.edu|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA. nsmith@clemson.edu|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA. nsmith@clemson.edu|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA. nsmith@clemson.edu|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA. nsmith@clemson.edu|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA. nsmith@clemson.edu|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA. nsmith@clemson.edu', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Computational Biology|Internet|Models, Molecular|Nanostructures|Software|Static Electricity|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts200', '22531215', 'A new edition of the DelPhi web server, DelPhi web server v2, is released to include atomic presentation of geometrical figures. These geometrical objects can be used to model nano-size objects together with real biological macromolecules. The position and size of the object can be manipulated by the user in real time until desired results are achieved. The server fixes structural defects, adds hydrogen atoms and calculates electrostatic energies and the corresponding electrostatic potential and ionic distributions.'),
(76874, 2012, 'bio', 'Tachyon search speeds up retrieval of similar sequences by several orders of magnitude', 'Tan, Joshua|Kuchibhatla, Durga|Sirota, Fernanda L|Sherman, Westley A|Gattermayer, Tobias|Kwoh, Chia Yee|Eisenhaber, Frank|Schneider, Georg|Maurer-Stroh, Sebastian', 'Bioinformatics Institute (BII), Agency for Science Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.|Bioinformatics Institute (BII), Agency for Science Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.|Bioinformatics Institute (BII), Agency for Science Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.|Bioinformatics Institute (BII), Agency for Science Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.|Bioinformatics Institute (BII), Agency for Science Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.|Bioinformatics Institute (BII), Agency for Science Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.|Bioinformatics Institute (BII), Agency for Science Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.|Bioinformatics Institute (BII), Agency for Science Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.|Bioinformatics Institute (BII), Agency for Science Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 0, 'Algorithms|Amino Acid Sequence|Databases, Protein|Humans|Internet|Search Engine', 'Journal Article', '10.1093/bioinformatics/bts197', '22531216', 'The usage of current sequence search tools becomes increasingly slower as databases of protein sequences continue to grow exponentially. Tachyon, a new algorithm that identifies closely related protein sequences ~200 times faster than standard BLAST, circumvents this limitation with a reduced database and oligopeptide matching heuristic.'),
(76875, 2012, 'bio', 'Accurate extension of multiple sequence alignments using a phylogeny-aware graph algorithm', 'Löytynoja, Ari|Vilella, Albert J|Goldman, Nick', 'EMBL-European Bioinformatics Institute, Hinxton, CB10 1SD, UK. ari.loytynoja@helsinki.fi|EMBL-European Bioinformatics Institute, Hinxton, CB10 1SD, UK. ari.loytynoja@helsinki.fi|EMBL-European Bioinformatics Institute, Hinxton, CB10 1SD, UK. ari.loytynoja@helsinki.fi', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/bts198', '22531217', 'Accurate alignment of large numbers of sequences is demanding and the computational burden is further increased by downstream analyses depending on these alignments. With the abundance of sequence data, an integrative approach of adding new sequences to existing alignments without their full re-computation and maintaining the relative matching of existing sequences is an attractive option. Another current challenge is the extension of reference alignments with fragmented sequences, as those coming from next-generation metagenomics, that contain relatively little information. Widely used methods for alignment extension are based on profile representation of reference sequences. These do not incorporate and use phylogenetic information and are affected by the composition of the reference alignment and the phylogenetic positions of query sequences.'),
(76876, 2012, 'bio', 'MMFPh: a maximal motif finder for phosphoproteomics datasets', 'Wang, Tuobin|Kettenbach, Arminja N|Gerber, Scott A|Bailey-Kellogg, Chris', 'Department of Computer Science, Dartmouth College, Hanover, NH 03755, USA.|Department of Computer Science, Dartmouth College, Hanover, NH 03755, USA.|Department of Computer Science, Dartmouth College, Hanover, NH 03755, USA.|Department of Computer Science, Dartmouth College, Hanover, NH 03755, USA.', 'United States|United States|United States|United States', 21, 'Algorithms|Amino Acid Motifs|Humans|Internet|Phosphorylation|Proteins|Proteome|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/bts195', '22531218', 'Protein phosphorylation, driven by specific recognition of substrates by kinases and phosphatases, plays central roles in a variety of important cellular processes such as signaling and enzyme activation. Mass spectrometry enables the determination of phosphorylated peptides (and thereby proteins) in scenarios ranging from targeted in vitro studies to in vivo cell lysates under particular conditions. The characterization of commonalities among identified phosphopeptides provides insights into the specificities of the kinases involved in a study. Several algorithms have been developed to uncover linear motifs representing position-specific amino acid patterns in sets of phosphopeptides. To more fully capture the available information, reduce sensitivity to both parameter choices and natural experimental variation, and develop more precise characterizations of kinase specificities, it is necessary to determine all statistically significant motifs represented in a dataset.'),
(76877, 2012, 'bio', 'PSI-Search: iterative HOE-reduced profile SSEARCH searching', 'Li, Weizhong|McWilliam, Hamish|Goujon, Mickael|Cowley, Andrew|Lopez, Rodrigo|Pearson, William R', 'EMBL - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 18, 'Amino Acid Motifs|Computational Biology|Databases, Protein|Internet|Programming Languages|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/bts240', '22539666', 'Iterative similarity searches with PSI-BLAST position-specific score matrices (PSSMs) find many more homologs than single searches, but PSSMs can be contaminated when homologous alignments are extended into unrelated protein domains-homologous over-extension (HOE). PSI-Search combines an optimal Smith-Waterman local alignment sequence search, using SSEARCH, with the PSI-BLAST profile construction strategy. An optional sequence boundary-masking procedure, which prevents alignments from being extended after they are initially included, can reduce HOE errors in the PSSM profile. Preventing HOE improves selectivity for both PSI-BLAST and PSI-Search, but PSI-Search has ~4-fold better selectivity than PSI-BLAST and similar sensitivity at 50% and 60% family coverage. PSI-Search is also produces 2- for 4-fold fewer false-positives than JackHMMER, but is ~5% less sensitive.'),
(76878, 2012, 'bio', 'CNVRuler: a copy number variation-based case-control association analysis tool', 'Kim, Ji-Hong|Hu, Hae-Jin|Yim, Seon-Hee|Bae, Joon Seol|Kim, Seon-Young|Chung, Yeun-Jun', 'Integrated Research Center for Genome Polymorphism, Department of Microbiology, School of Medicine, Catholic University of Korea, Seoul 137-701, Korea.|Integrated Research Center for Genome Polymorphism, Department of Microbiology, School of Medicine, Catholic University of Korea, Seoul 137-701, Korea.|Integrated Research Center for Genome Polymorphism, Department of Microbiology, School of Medicine, Catholic University of Korea, Seoul 137-701, Korea.|Integrated Research Center for Genome Polymorphism, Department of Microbiology, School of Medicine, Catholic University of Korea, Seoul 137-701, Korea.|Integrated Research Center for Genome Polymorphism, Department of Microbiology, School of Medicine, Catholic University of Korea, Seoul 137-701, Korea.|Integrated Research Center for Genome Polymorphism, Department of Microbiology, School of Medicine, Catholic University of Korea, Seoul 137-701, Korea.', '-|-|-|-|-|-', 34, 'Algorithms|Case-Control Studies|DNA Copy Number Variations|Genome-Wide Association Study|Software', 'Journal Article', '10.1093/bioinformatics/bts239', '22539667', 'The method for genome-wide association study (GWAS) based on copy number variation (CNV) is not as well established as that for single nucleotide polymorphism (SNP)-GWAS. Although there are several tools for CNV association studies, most of them do not provide appropriate definitions of CNV regions (CNVRs), which are essential for CNV-association studies. Here we present a user-friendly program called CNVRuler for CNV-association studies. Outputs from the 10 most common CNV defining algorithms can be directly used as input files for determining the three different definitions of CNVRs. Once CNVRs are defined, CNVRuler supports four kinds of statistical association tests and options for population stratification. CNVRuler is based on the open-source programs R and Java from Sun Microsystems.'),
(76879, 2012, 'bio', 'Boosting automatic event extraction from the literature using domain adaptation and coreference resolution', 'Miwa, Makoto|Thompson, Paul|Ananiadou, Sophia', 'The National Centre for Text Mining (NaCTeM), UK. makoto.miwa@manchester.ac.uk|The National Centre for Text Mining (NaCTeM), UK. makoto.miwa@manchester.ac.uk|The National Centre for Text Mining (NaCTeM), UK. makoto.miwa@manchester.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Data Mining|Genes|Proteins|Software', 'Evaluation Studies', '10.1093/bioinformatics/bts237', '22539668', 'In recent years, several biomedical event extraction (EE) systems have been developed. However, the nature of the annotated training corpora, as well as the training process itself, can limit the performance levels of the trained EE systems. In particular, most event-annotated corpora do not deal adequately with coreference. This impacts on the trained systems ability to recognize biomedical entities, thus affecting their performance in extracting events accurately. Additionally, the fact that most EE systems are trained on a single annotated corpus further restricts their coverage.'),
(76880, 2012, 'bio', 'Statistical interpretation of machine learning-based feature importance scores for biomarker discovery', 'Huynh-Thu, Vân Anh|Saeys, Yvan|Wehenkel, Louis|Geurts, Pierre', 'Department of Electrical Engineering and Computer Science, University of Liège, 4000 Liège, Belgium. vahuynh@ulg.ac.be|Department of Electrical Engineering and Computer Science, University of Liège, 4000 Liège, Belgium. vahuynh@ulg.ac.be|Department of Electrical Engineering and Computer Science, University of Liège, 4000 Liège, Belgium. vahuynh@ulg.ac.be|Department of Electrical Engineering and Computer Science, University of Liège, 4000 Liège, Belgium. vahuynh@ulg.ac.be', 'Belgium|Belgium|Belgium|Belgium', 0, 'Artificial Intelligence|Biomarkers|Computational Biology|Data Interpretation, Statistical|Transcriptome', 'Evaluation Studies', '10.1093/bioinformatics/bts238', '22539669', 'Univariate statistical tests are widely used for biomarker discovery in bioinformatics. These procedures are simple, fast and their output is easily interpretable by biologists but they can only identify variables that provide a significant amount of information in isolation from the other variables. As biological processes are expected to involve complex interactions between variables, univariate methods thus potentially miss some informative biomarkers. Variable relevance scores provided by machine learning techniques, however, are potentially able to highlight multivariate interacting effects, but unlike the p-values returned by univariate tests, these relevance scores are usually not statistically interpretable. This lack of interpretability hampers the determination of a relevance threshold for extracting a feature subset from the rankings and also prevents the wide adoption of these methods by practicians.'),
(76881, 2012, 'bio', 'RNA-SeQC: RNA-seq metrics for quality control and process optimization', 'DeLuca, David S|Levin, Joshua Z|Sivachenko, Andrey|Fennell, Timothy|Nazaire, Marc-Danie|Williams, Chris|Reich, Michael|Winckler, Wendy|Getz, Gad', 'Broad Institute of MIT and Harvard, Cambridge, MA, USA. ddeluca@broadinstitute.org|Broad Institute of MIT and Harvard, Cambridge, MA, USA. ddeluca@broadinstitute.org|Broad Institute of MIT and Harvard, Cambridge, MA, USA. ddeluca@broadinstitute.org|Broad Institute of MIT and Harvard, Cambridge, MA, USA. ddeluca@broadinstitute.org|Broad Institute of MIT and Harvard, Cambridge, MA, USA. ddeluca@broadinstitute.org|Broad Institute of MIT and Harvard, Cambridge, MA, USA. ddeluca@broadinstitute.org|Broad Institute of MIT and Harvard, Cambridge, MA, USA. ddeluca@broadinstitute.org|Broad Institute of MIT and Harvard, Cambridge, MA, USA. ddeluca@broadinstitute.org|Broad Institute of MIT and Harvard, Cambridge, MA, USA. ddeluca@broadinstitute.org', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 340, 'Gene Expression Profiling|Gene Library|High-Throughput Nucleotide Sequencing|Internet|Quality Control|RNA|RNA, Ribosomal|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts196', '22539670', 'RNA-seq, the application of next-generation sequencing to RNA, provides transcriptome-wide characterization of cellular activity. Assessment of sequencing performance and library quality is critical to the interpretation of RNA-seq data, yet few tools exist to address this issue. We introduce RNA-SeQC, a program which provides key measures of data quality. These metrics include yield, alignment and duplication rates, GC bias, rRNA content, regions of alignment (exon, intron and intragenic), continuity of coverage, 3/5 bias and count of detectable transcripts, among others. The software provides multi-sample evaluation of library construction protocols, input materials and other experimental parameters. The modularity of the software enables pipeline integration and the routine monitoring of key measures of data quality such as the number of alignable reads, duplication rates and rRNA contamination. RNA-SeQC allows investigators to make informed decisions about sample inclusion in downstream analysis. In summary, RNA-SeQC provides quality control measures critical to experiment design, process optimization and downstream computational analysis.'),
(76882, 2012, 'bio', 'DecoyFinder: an easy-to-use python GUI application for building target-specific decoy sets', 'Cereto-Massagué, Adrià|Guasch, Laura|Valls, Cristina|Mulero, Miquel|Pujadas, Gerard|Garcia-Vallvé, Santiago', 'Grup de Recerca en Nutrigenòmica, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, C/Marcel.lí Domingo s/n, 43007 Tarragona, Spain.|Grup de Recerca en Nutrigenòmica, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, C/Marcel.lí Domingo s/n, 43007 Tarragona, Spain.|Grup de Recerca en Nutrigenòmica, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, C/Marcel.lí Domingo s/n, 43007 Tarragona, Spain.|Grup de Recerca en Nutrigenòmica, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, C/Marcel.lí Domingo s/n, 43007 Tarragona, Spain.|Grup de Recerca en Nutrigenòmica, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, C/Marcel.lí Domingo s/n, 43007 Tarragona, Spain.|Grup de Recerca en Nutrigenòmica, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Campus de Sescelades, C/Marcel.lí Domingo s/n, 43007 Tarragona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Computational Biology|Computer Graphics|Databases, Factual|Hydrogen Bonding|Ligands|Models, Molecular|Molecular Weight|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts249', '22539671', 'Decoys are molecules that are presumed to be inactive against a target (i.e. will not likely bind to the target) and are used to validate the performance of molecular docking or a virtual screening workflow. The Directory of Useful Decoys database (http://dud.docking.org/) provides a free directory of decoys for use in virtual screening, though it only contains a limited set of decoys for 40 targets.To overcome this limitation, we have developed an application called DecoyFinder that selects, for a given collection of active ligands of a target, a set of decoys from a database of compounds. Decoys are selected if they are similar to active ligands according to five physical descriptors (molecular weight, number of rotational bonds, total hydrogen bond donors, total hydrogen bond acceptors and the octanol-water partition coefficient) without being chemically similar to any of the active ligands used as an input (according to the Tanimoto coefficient between MACCS fingerprints). To the best of our knowledge, DecoyFinder is the first application designed to build target-specific decoy sets.'),
(76883, 2012, 'bio', 'e-Drug3D: 3D structure collections dedicated to drug repurposing and fragment-based drug design', 'Pihan, Emilie|Colliandre, Lionel|Guichou, Jean-François|Douguet, Dominique', 'Institut de Pharmacologie Moléculaire et Cellulaire, CNRS UMR7275, Université Nice-Sophia Antipolis, 660 route des lucioles, Valbonne, France.|Institut de Pharmacologie Moléculaire et Cellulaire, CNRS UMR7275, Université Nice-Sophia Antipolis, 660 route des lucioles, Valbonne, France.|Institut de Pharmacologie Moléculaire et Cellulaire, CNRS UMR7275, Université Nice-Sophia Antipolis, 660 route des lucioles, Valbonne, France.|Institut de Pharmacologie Moléculaire et Cellulaire, CNRS UMR7275, Université Nice-Sophia Antipolis, 660 route des lucioles, Valbonne, France.', 'France|France|France|France', 58, 'Cyclophilins|Databases, Factual|Drug Design|Drug Discovery|Drug Repositioning|Humans|Internet|Models, Chemical|Pharmaceutical Preparations', 'Journal Article', '10.1093/bioinformatics/bts186', '22539672', 'In the drug discovery field, new uses for old drugs, selective optimization of side activities and fragment-based drug design (FBDD) have proved to be successful alternatives to high-throughput screening. e-Drug3D is a database of 3D chemical structures of drugs that provides several collections of ready-to-screen SD files of drugs and commercial drug fragments. They are natural inputs in studies dedicated to drug repurposing and FBDD.'),
(76884, 2012, 'bio', 'Improving the TFold test for differential shotgun proteomics', 'Carvalho, Paulo C|Yates, John R|Barbosa, Valmir C', 'Carlos Chagas Institute, Fiocruz, Paraná, Brazil. paulo@pcarvalho.com|Carlos Chagas Institute, Fiocruz, Paraná, Brazil. paulo@pcarvalho.com|Carlos Chagas Institute, Fiocruz, Paraná, Brazil. paulo@pcarvalho.com', 'Brazil|Brazil|Brazil', 39, 'Algorithms|Cell Line, Tumor|Computational Biology|Data Interpretation, Statistical|Humans|Proteins|Proteomics|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts247', '22539673', 'We present an updated version of the TFold software for pinpointing differentially expressed proteins in shotgun proteomics experiments. Given an FDR bound, the updated approach uses a theoretical FDR estimator to maximize the number of identifications that satisfy both a fold-change cutoff that varies with the t-test P-value as a power law and a stringency criterion that aims to detect lowly abundant proteins. The new version has yielded significant improvements in sensitivity over the previous one.'),
(76885, 2012, 'bio', 'State and parameter estimation of the heat shock response system using Kalman and particle filters', 'Liu, Xin|Niranjan, Mahesan', 'School of Electronics and Computer Science, University of Southampton, Southampton, UK.|School of Electronics and Computer Science, University of Southampton, Southampton, UK.', 'United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Computer Simulation|Escherichia coli|Heat-Shock Response|Models, Biological|Models, Statistical|Regression Analysis|Saccharomycetales|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/bts161', '22539674', 'Traditional models of systems biology describe dynamic biological phenomena as solutions to ordinary differential equations, which, when parameters in them are set to correct values, faithfully mimic observations. Often parameter values are tweaked by hand until desired results are achieved, or computed from biochemical experiments carried out in vitro. Of interest in this article, is the use of probabilistic modelling tools with which parameters and unobserved variables, modelled as hidden states, can be estimated from limited noisy observations of parts of a dynamical system.'),
(76886, 2012, 'bio', 'Semantic integration of physiology phenotypes with an application to the Cellular Phenotype Ontology', 'Hoehndorf, Robert|Harris, Midori A|Herre, Heinrich|Rustici, Gabriella|Gkoutos, Georgios V', 'Department of Genetics, University of Cambridge, Downing Street, Cambridge, Cambridge CB2 3EH, UK. rh497@cam.ac.uk|Department of Genetics, University of Cambridge, Downing Street, Cambridge, Cambridge CB2 3EH, UK. rh497@cam.ac.uk|Department of Genetics, University of Cambridge, Downing Street, Cambridge, Cambridge CB2 3EH, UK. rh497@cam.ac.uk|Department of Genetics, University of Cambridge, Downing Street, Cambridge, Cambridge CB2 3EH, UK. rh497@cam.ac.uk|Department of Genetics, University of Cambridge, Downing Street, Cambridge, Cambridge CB2 3EH, UK. rh497@cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 24, 'Cell Physiological Phenomena|Phenotype|Semantics|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts250', '22539675', 'The systematic observation of phenotypes has become a crucial tool of functional genomics, and several large international projects are currently underway to identify and characterize the phenotypes that are associated with genotypes in several species. To integrate phenotype descriptions within and across species, phenotype ontologies have been developed. Applying ontologies to unify phenotype descriptions in the domain of physiology has been a particular challenge due to the high complexity of the underlying domain.'),
(76887, 2012, 'bio', 'Speeding up tandem mass spectral identification using indexes', 'Liu, Xiaowen|Mammana, Alessandro|Bafna, Vineet', 'Department of Computer Science and Engineering, University of California, San Diego, California 92093, USA. xil018@cs.ucsd.edu|Department of Computer Science and Engineering, University of California, San Diego, California 92093, USA. xil018@cs.ucsd.edu|Department of Computer Science and Engineering, University of California, San Diego, California 92093, USA. xil018@cs.ucsd.edu', 'United States|United States|United States', 0, 'Algorithms|Humans|Peptides|Protein Processing, Post-Translational|Proteins|Proteomics|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/bts244', '22543365', 'Tandem mass spectrometry (MS/MS) has been routinely used in proteomics studies. Post-translational modification (PTM) identification is a challenging problem in tandem mass spectral analysis.'),
(76888, 2012, 'bio', 'DAVID-WS: a stateful web service to facilitate gene/protein list analysis', 'Jiao, Xiaoli|Sherman, Brad T|Huang, Da Wei|Stephens, Robert|Baseler, Michael W|Lane, H Clifford|Lempicki, Richard A', 'Laboratory of Immunopathogenesis and Bioinformatics, National Cancer Institute at Frederick, Frederick, MD 21702, USA. xiaoli.jiao@nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, National Cancer Institute at Frederick, Frederick, MD 21702, USA. xiaoli.jiao@nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, National Cancer Institute at Frederick, Frederick, MD 21702, USA. xiaoli.jiao@nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, National Cancer Institute at Frederick, Frederick, MD 21702, USA. xiaoli.jiao@nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, National Cancer Institute at Frederick, Frederick, MD 21702, USA. xiaoli.jiao@nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, National Cancer Institute at Frederick, Frederick, MD 21702, USA. xiaoli.jiao@nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, National Cancer Institute at Frederick, Frederick, MD 21702, USA. xiaoli.jiao@nih.gov', 'United States|United States|United States|United States|United States|United States|United States', 347, 'Computational Biology|Databases, Genetic|Genes|Internet|Molecular Sequence Annotation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts251', '22543366', 'The database for annotation, visualization and integrated discovery (DAVID), which can be freely accessed at http://david.abcc.ncifcrf.gov/, is a web-based online bioinformatics resource that aims to provide tools for the functional interpretation of large lists of genes/proteins. It has been used by researchers from more than 5000 institutes worldwide, with a daily submission rate of xe2x88xbc1200 gene lists from xe2x88xbc400 unique researchers, and has been cited by more than 6000 scientific publications. However, the current web interface does not support programmatic access to DAVID, and the uniform resource locator (URL)-based application programming interface (API) has a limit on URL size and is stateless in nature as it uses URL request and response messages to communicate with the server, without keeping any state-related details. DAVID-WS (web service) has been developed to automate user tasks by providing stateful web services to access DAVID programmatically without the need for human interactions.');
