INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78939, 2015, 'bio', 'MicroRNA modules prefer to bind weak and unconventional target sites', 'Ding, Jun|Li, Xiaoman|Hu, Haiyan', 'Department of Electrical Engineering and Computer Science and Burnett School of Biomedical Science, College of Medicine, University of Central Florida, Orlando, FL 32816, USA.|Department of Electrical Engineering and Computer Science and Burnett School of Biomedical Science, College of Medicine, University of Central Florida, Orlando, FL 32816, USA.|Department of Electrical Engineering and Computer Science and Burnett School of Biomedical Science, College of Medicine, University of Central Florida, Orlando, FL 32816, USA.', 'United States|United States|United States', 0, 'Binding Sites|Exons|Gene Expression Regulation|HEK293 Cells|Humans|MicroRNAs|RNA, Messenger|Software', 'Journal Article', '10.1093/bioinformatics/btu833', '25527098', 'MicroRNAs (miRNAs) play critical roles in gene regulation. Although it is well known that multiple miRNAs may work as miRNA modules to synergistically regulate common target mRNAs, the understanding of miRNA modules is still in its infancy.'),
(78940, 2015, 'bio', 'Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics', 'Giacomoni, Franck|Le Corguillé, Gildas|Monsoor, Misharl|Landi, Marion|Pericard, Pierre|Pétéra, Mélanie|Duperier, Christophe|Tremblay-Franco, Marie|Martin, Jean-François|Jacob, Daniel|Goulitquer, Sophie|Thévenot, Etienne A|Caron, Christophe', 'INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.|INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.|INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.|INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.|INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.|INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.|INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.|INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.|INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.|INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.|INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.|INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.|INRA, UMR 1019, PFEM, 63122 Saint Genes Champanelle, CNRS, UPMC, FR2424, ABiMS, Station Biologique, 29680 Roscoff, INRA, UMR 1331, PF MetaToul-AXIOM, Toxalim, F-31027 Toulouse, INRA, Metabolome Facility of Bordeaux Functional Genomics Center, IBVM, 33140 Villenave dOrnon and CEA, LIST, Laboratory for Data Analysis and Smart Systems (LADIS), MetaboHUB Paris, F-91191 Gif-sur-Yvette, France.', 'France|France|France|France|France|France|France|France|France|France|France|France|France', 144, 'Algorithms|Computational Biology|Metabolomics|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btu813', '25527831', 'The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation.'),
(78941, 2015, 'bio', 'Population-based structural variation discovery with Hydra-Multi', 'Lindberg, Michael R|Hall, Ira M|Quinlan, Aaron R', 'Department of Biochemistry and Molecular Genetics, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA, Department of Medicine, The Genome Institute, Washington University School of Medicine, St. Louis MO, USA and Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA.|Department of Biochemistry and Molecular Genetics, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA, Department of Medicine, The Genome Institute, Washington University School of Medicine, St. Louis MO, USA and Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA Department of Biochemistry and Molecular Genetics, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA, Department of Medicine, The Genome Institute, Washington University School of Medicine, St. Louis MO, USA and Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA Department of Biochemistry and Molecular Genetics, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA, Department of Medicine, The Genome Institute, Washington University School of Medicine, St. Louis MO, USA and Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA Department of Biochemistry and Molecular Genetics, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA, Department of Medicine, The Genome Institute, Washington University School of Medicine, St. Louis MO, USA and Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA.|Department of Biochemistry and Molecular Genetics, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA, Department of Medicine, The Genome Institute, Washington University School of Medicine, St. Louis MO, USA and Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA Department of Biochemistry and Molecular Genetics, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA, Department of Medicine, The Genome Institute, Washington University School of Medicine, St. Louis MO, USA and Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA Department of Biochemistry and Molecular Genetics, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA, Department of Medicine, The Genome Institute, Washington University School of Medicine, St. Louis MO, USA and Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA.', 'United States|United States|United States', 0, 'Animals|Databases, Factual|Gene Deletion|Genetics, Population|Genomic Structural Variation|Genomics|Humans|Hydra|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btu771', '25527832', 'Current strategies for SNP and INDEL discovery incorporate sequence alignments from multiple individuals to maximize sensitivity and specificity. It is widely accepted that this approach also improves structural variant (SV) detection. However, multisample SV analysis has been stymied by the fundamental difficulties of SV calling, e.g. library insert size variability, SV alignment signal integration and detecting long-range genomic rearrangements involving disjoint loci. Extant tools suffer from poor scalability, which limits the number of genomes that can be co-analyzed and complicates analysis workflows. We have developed an approach that enables multisample SV analysis in hundreds to thousands of human genomes using commodity hardware. Here, we describe Hydra-Multi and measure its accuracy, speed and scalability using publicly available datasets provided by The 1000 Genomes Project and by The Cancer Genome Atlas (TCGA).'),
(78942, 2015, 'bio', 'mirPub: a database for searching microRNA publications', 'Vergoulis, Thanasis|Kanellos, Ilias|Kostoulas, Nikos|Georgakilas, Georgios|Sellis, Timos|Hatzigeorgiou, Artemis|Dalamagas, Theodore', 'School of Electrical and Computer Engineering, NTUA, Zografou 15773, IMIS Institute, Athena RC, Marousi 15125, DIANA-Lab, Institute of Molecular Oncology, BSRC Alexander Fleming, Vari 16672, Department of Computer & Communication Engineering, University of Thessaly, Volos 38221, Greece and School of Computer Science & Info Tech, RMIT University, Melbourne 3001, Australia School of Electrical and Computer Engineering, NTUA, Zografou 15773, IMIS Institute, Athena RC, Marousi 15125, DIANA-Lab, Institute of Molecular Oncology, BSRC Alexander Fleming, Vari 16672, Department of Computer & Communication Engineering, University of Thessaly, Volos 38221, Greece and School of Computer Science & Info Tech, RMIT University, Melbourne 3001, Australia.|School of Electrical and Computer Engineering, NTUA, Zografou 15773, IMIS Institute, Athena RC, Marousi 15125, DIANA-Lab, Institute of Molecular Oncology, BSRC Alexander Fleming, Vari 16672, Department of Computer & Communication Engineering, University of Thessaly, Volos 38221, Greece and School of Computer Science & Info Tech, RMIT University, Melbourne 3001, Australia School of Electrical and Computer Engineering, NTUA, Zografou 15773, IMIS Institute, Athena RC, Marousi 15125, DIANA-Lab, Institute of Molecular Oncology, BSRC Alexander Fleming, Vari 16672, Department of Computer & Communication Engineering, University of Thessaly, Volos 38221, Greece and School of Computer Science & Info Tech, RMIT University, Melbourne 3001, Australia.|School of Electrical and Computer Engineering, NTUA, Zografou 15773, IMIS Institute, Athena RC, Marousi 15125, DIANA-Lab, Institute of Molecular Oncology, BSRC Alexander Fleming, Vari 16672, Department of Computer & Communication Engineering, University of Thessaly, Volos 38221, Greece and School of Computer Science & Info Tech, RMIT University, Melbourne 3001, Australia.|School of Electrical and Computer Engineering, NTUA, Zografou 15773, IMIS Institute, Athena RC, Marousi 15125, DIANA-Lab, Institute of Molecular Oncology, BSRC Alexander Fleming, Vari 16672, Department of Computer & Communication Engineering, University of Thessaly, Volos 38221, Greece and School of Computer Science & Info Tech, RMIT University, Melbourne 3001, Australia School of Electrical and Computer Engineering, NTUA, Zografou 15773, IMIS Institute, Athena RC, Marousi 15125, DIANA-Lab, Institute of Molecular Oncology, BSRC Alexander Fleming, Vari 16672, Department of Computer & Communication Engineering, University of Thessaly, Volos 38221, Greece and School of Computer Science & Info Tech, RMIT University, Melbourne 3001, Australia.|School of Electrical and Computer Engineering, NTUA, Zografou 15773, IMIS Institute, Athena RC, Marousi 15125, DIANA-Lab, Institute of Molecular Oncology, BSRC Alexander Fleming, Vari 16672, Department of Computer & Communication Engineering, University of Thessaly, Volos 38221, Greece and School of Computer Science & Info Tech, RMIT University, Melbourne 3001, Australia.|School of Electrical and Computer Engineering, NTUA, Zografou 15773, IMIS Institute, Athena RC, Marousi 15125, DIANA-Lab, Institute of Molecular Oncology, BSRC Alexander Fleming, Vari 16672, Department of Computer & Communication Engineering, University of Thessaly, Volos 38221, Greece and School of Computer Science & Info Tech, RMIT University, Melbourne 3001, Australia School of Electrical and Computer Engineering, NTUA, Zografou 15773, IMIS Institute, Athena RC, Marousi 15125, DIANA-Lab, Institute of Molecular Oncology, BSRC Alexander Fleming, Vari 16672, Department of Computer & Communication Engineering, University of Thessaly, Volos 38221, Greece and School of Computer Science & Info Tech, RMIT University, Melbourne 3001, Australia.|School of Electrical and Computer Engineering, NTUA, Zografou 15773, IMIS Institute, Athena RC, Marousi 15125, DIANA-Lab, Institute of Molecular Oncology, BSRC Alexander Fleming, Vari 16672, Department of Computer & Communication Engineering, University of Thessaly, Volos 38221, Greece and School of Computer Science & Info Tech, RMIT University, Melbourne 3001, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Data Mining|Databases, Bibliographic|MEDLINE|MicroRNAs|Publications', 'Journal Article', '10.1093/bioinformatics/btu819', '25527833', 'Identifying, amongst millions of publications available in MEDLINE, those that are relevant to specific microRNAs (miRNAs) of interest based on keyword search faces major obstacles. References to miRNA names in the literature often deviate from standard nomenclature for various reasons, since even the official nomenclature evolves. For instance, a single miRNA name may identify two completely different molecules or two different names may refer to the same molecule. mirPub is a database with a powerful and intuitive interface, which facilitates searching for miRNA literature, addressing the aforementioned issues. To provide effective search services, mirPub applies text mining techniques on MEDLINE, integrates data from several curated databases and exploits data from its user community following a crowdsourcing approach. Other key features include an interactive visualization service that illustrates intuitively the evolution of miRNA data, tag clouds summarizing the relevance of publications to particular diseases, cell types or tissues and access to TarBase 6.0 data to oversee genes related to miRNA publications.'),
(78943, 2015, 'bio', 'CONSRANK: a server for the analysis, comparison and ranking of docking models based on inter-residue contacts', 'Chermak, Edrisse|Petta, Andrea|Serra, Luigi|Vangone, Anna|Scarano, Vittorio|Cavallo, Luigi|Oliva, Romina', 'Kaust Catalysis Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, Dipartimento di Informatica ed Applicazioni, Department of Chemistry and Biology, University of Salerno, Fisciano, SA, Italy and Department of Sciences and Technologies, University Parthenope of Naples, Naples, Italy.|Kaust Catalysis Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, Dipartimento di Informatica ed Applicazioni, Department of Chemistry and Biology, University of Salerno, Fisciano, SA, Italy and Department of Sciences and Technologies, University Parthenope of Naples, Naples, Italy.|Kaust Catalysis Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, Dipartimento di Informatica ed Applicazioni, Department of Chemistry and Biology, University of Salerno, Fisciano, SA, Italy and Department of Sciences and Technologies, University Parthenope of Naples, Naples, Italy.|Kaust Catalysis Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, Dipartimento di Informatica ed Applicazioni, Department of Chemistry and Biology, University of Salerno, Fisciano, SA, Italy and Department of Sciences and Technologies, University Parthenope of Naples, Naples, Italy.|Kaust Catalysis Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, Dipartimento di Informatica ed Applicazioni, Department of Chemistry and Biology, University of Salerno, Fisciano, SA, Italy and Department of Sciences and Technologies, University Parthenope of Naples, Naples, Italy.|Kaust Catalysis Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, Dipartimento di Informatica ed Applicazioni, Department of Chemistry and Biology, University of Salerno, Fisciano, SA, Italy and Department of Sciences and Technologies, University Parthenope of Naples, Naples, Italy.|Kaust Catalysis Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, Dipartimento di Informatica ed Applicazioni, Department of Chemistry and Biology, University of Salerno, Fisciano, SA, Italy and Department of Sciences and Technologies, University Parthenope of Naples, Naples, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'DNA|DNA-Binding Proteins|Internet|Molecular Docking Simulation|Protein Interaction Mapping|RNA|RNA-Binding Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu837', '25535242', 'Herein, we present CONSRANK, a web tool for analyzing, comparing and ranking protein-protein and protein-nucleic acid docking models, based on the conservation of inter-residue contacts and its visualization in 2D and 3D interactive contact maps.'),
(78944, 2015, 'bio', 'A Bayesian framework for de novo mutation calling in parents-offspring trios', 'Wei, Qiang|Zhan, Xiaowei|Zhong, Xue|Liu, Yongzhuang|Han, Yujun|Chen, Wei|Li, Bingshan', 'Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, Nashville, TN, USA,Center for Human Genetic Variation, Duke University, Durham, NC, USA, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, Nashville, TN, USA,Center for Human Genetic Variation, Duke University, Durham, NC, USA, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, Nashville, TN, USA,Center for Human Genetic Variation, Duke University, Durham, NC, USA, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, Nashville, TN, USA,Center for Human Genetic Variation, Duke University, Durham, NC, USA, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, Nashville, TN, USA,Center for Human Genetic Variation, Duke University, Durham, NC, USA, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, Nashville, TN, USA,Center for Human Genetic Variation, Duke University, Durham, NC, USA, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, Nashville, TN, USA,Center for Human Genetic Variation, Duke University, Durham, NC, USA, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, Nashville, TN, USA,Center for Human Genetic Variation, Duke University, Durham, NC, USA, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, Nashville, TN, USA,Center for Human Genetic Variation, Duke University, Durham, NC, USA, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.', 'China|China|China|China|China|China|China', 0, 'Algorithms|Bayes Theorem|DNA Mutational Analysis|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment', 'Evaluation Studies', '10.1093/bioinformatics/btu839', '25535243', 'Spontaneous (de novo) mutations play an important role in the disease etiology of a range of complex diseases. Identifying de novo mutations (DNMs) in sporadic cases provides an effective strategy to find genes or genomic regions implicated in the genetics of disease. High-throughput next-generation sequencing enables genome- or exome-wide detection of DNMs by sequencing parents-proband trios. It is challenging to sift true mutations through massive amount of noise due to sequencing error and alignment artifacts. One of the critical limitations of existing methods is that for all genomic regions the same pre-specified mutation rate is assumed, which has a significant impact on the DNM calling accuracy.'),
(78945, 2015, 'bio', 'PBOOST: a GPU-based tool for parallel permutation tests in genome-wide association studies', 'Yang, Guangyuan|Jiang, Wei|Yang, Qiang|Yu, Weichuan', 'Laboratory of Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering and Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China.|Laboratory of Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering and Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China.|Laboratory of Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering and Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China.|Laboratory of Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering and Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China.', 'China|China|China|China', 0, 'Genome-Wide Association Study|Humans|Likelihood Functions|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btu840', '25535244', 'The importance of testing associations allowing for interactions has been demonstrated by Marchini et al. (2005). A fast method detecting associations allowing for interactions has been proposed by Wan et al. (2010a). The method is based on likelihood ratio test with the assumption that the statistic follows the xcfx87(2) distribution. Many single nucleotide polymorphism (SNP) pairs with significant associations allowing for interactions have been detected using their method. However, the assumption of xcfx87(2) test requires the expected values in each cell of the contingency table to be at least five. This assumption is violated in some identified SNP pairs. In this case, likelihood ratio test may not be applicable any more. Permutation test is an ideal approach to checking the P-values calculated in likelihood ratio test because of its non-parametric nature. The P-values of SNP pairs having significant associations with disease are always extremely small. Thus, we need a huge number of permutations to achieve correspondingly high resolution for the P-values. In order to investigate whether the P-values from likelihood ratio tests are reliable, a fast permutation tool to accomplish large number of permutations is desirable.'),
(78946, 2015, 'bio', 'MACE: mutation-oriented profiling of chemical response and gene expression in cancers', 'Jeong, Euna|He, Ningning|Park, Hyerin|Song, Mee|Kim, Nayoung|Lee, Seongjoon|Yoon, Sukjoon', 'Center for Advanced Bioinformatics and Systems Medicine and Department of Biological Sciences, Sookmyung Womens University, Seoul 140-742, Republic of Korea.|Center for Advanced Bioinformatics and Systems Medicine and Department of Biological Sciences, Sookmyung Womens University, Seoul 140-742, Republic of Korea.|Center for Advanced Bioinformatics and Systems Medicine and Department of Biological Sciences, Sookmyung Womens University, Seoul 140-742, Republic of Korea.|Center for Advanced Bioinformatics and Systems Medicine and Department of Biological Sciences, Sookmyung Womens University, Seoul 140-742, Republic of Korea.|Center for Advanced Bioinformatics and Systems Medicine and Department of Biological Sciences, Sookmyung Womens University, Seoul 140-742, Republic of Korea.|Center for Advanced Bioinformatics and Systems Medicine and Department of Biological Sciences, Sookmyung Womens University, Seoul 140-742, Republic of Korea.|Center for Advanced Bioinformatics and Systems Medicine and Department of Biological Sciences, Sookmyung Womens University, Seoul 140-742, Republic of Korea Center for Advanced Bioinformatics and Systems Medicine and Department of Biological Sciences, Sookmyung Womens University, Seoul 140-742, Republic of Korea.', '-|-|-|-|-|-|-', 0, 'Antineoplastic Agents|Cell Line, Tumor|Databases, Chemical|Gene Expression Profiling|Humans|Mutation|Neoplasms|Oligonucleotide Array Sequence Analysis|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btu835', '25536965', 'The mutational status of specific cancer lineages can affect the sensitivity to or resistance against cancer drugs. The MACE database provides web-based interactive tools for interpreting large chemical screening and gene expression datasets of cancer cell lines in terms of mutation and lineage categories. GI50 data of chemicals against individual NCI60 cell lines were normalized and organized to statistically identify mutation- or lineage-specific chemical responses. Similarly, DNA microarray data on NCI60 cell lines were processed to analyze mutation- or lineage-specific gene expression signatures. A combined analysis of GI50 and gene expression data to find potential associations between chemicals and genes is also a capability of this system. This database will provide extensive, systematic information to identify lineage- or mutation-specific anticancer agents and related gene targets.'),
(78947, 2015, 'bio', 'Disk-based compression of data from genome sequencing', 'Grabowski, Szymon|Deorowicz, Sebastian|Roguski, xc5x81ukasz', 'Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 xc5x81xc3xb3dxc5xba, Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008 Warszawa, Poland and Centro Nacional de Anxc3xa1lisis Genxc3xb3mico (CNAG), 08-028 Barcelona, Spain.|Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 xc5x81xc3xb3dxc5xba, Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008 Warszawa, Poland and Centro Nacional de Anxc3xa1lisis Genxc3xb3mico (CNAG), 08-028 Barcelona, Spain.|Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 xc5x81xc3xb3dxc5xba, Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008 Warszawa, Poland and Centro Nacional de Anxc3xa1lisis Genxc3xb3mico (CNAG), 08-028 Barcelona, Spain Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 xc5x81xc3xb3dxc5xba, Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008 Warszawa, Poland and Centro Nacional de Anxc3xa1lisis Genxc3xb3mico (CNAG), 08-028 Barcelona, Spain.', 'Spain|Spain|Spain', 0, 'Algorithms|Animals|Chickens|Data Compression|Genome, Human|Genomics|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu844', '25536966', 'High-coverage sequencing data have significant, yet hard to exploit, redundancy. Most FASTQ compressors cannot efficiently compress the DNA stream of large datasets, since the redundancy between overlapping reads cannot be easily captured in the (relatively small) main memory. More interesting solutions for this problem are disk based, where the better of these two, from Cox et al. (2012), is based on the Burrows-Wheeler transform (BWT) and achieves 0.518 bits per base for a 134.0xe2x80x89Gbp human genome sequencing collection with almost 45-fold coverage.'),
(78948, 2015, 'bio', 'The chemical component dictionary: complete descriptions of constituent molecules in experimentally determined 3D macromolecules in the Protein Data Bank', 'Westbrook, John D|Shao, Chenghua|Feng, Zukang|Zhuravleva, Marina|Velankar, Sameer|Young, Jasmine', 'RCSB PDB, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA and Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|RCSB PDB, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA and Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|RCSB PDB, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA and Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|RCSB PDB, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA and Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|RCSB PDB, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA and Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|RCSB PDB, Department of Chemistry and Chemical Biology and Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA and Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.', 'Jersey|Jersey|Jersey|Jersey|Jersey|Jersey', 0, 'Databases, Chemical|Databases, Protein|Dictionaries, Chemical as Topic|Internet|Ligands|Macromolecular Substances|Molecular Sequence Annotation|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu789', '25540181', 'The Chemical Component Dictionary (CCD) is a chemical reference data resource that describes all residue and small molecule components found in Protein Data Bank (PDB) entries. The CCD contains detailed chemical descriptions for standard and modified amino acids/nucleotides, small molecule ligands and solvent molecules. Each chemical definition includes descriptions of chemical properties such as stereochemical assignments, chemical descriptors, systematic chemical names and idealized coordinates. The content, preparation, validation and distribution of this CCD chemical reference dataset are described.'),
(78949, 2015, 'bio', 'The QDREC web server: determining dose-response characteristics of complex macroparasites in phenotypic drug screens', 'Asarnow, Daniel|Rojo-Arreola, Liliana|Suzuki, Brian M|Caffrey, Conor R|Singh, Rahul', 'Department of Computer Science, San Francisco State University, San Francisco, CA, USA, Department of Pathology and Center for Discovery and Innovation in Parasitic Diseases, University of California, San Francisco, San Francisco, CA, USA.|Department of Computer Science, San Francisco State University, San Francisco, CA, USA, Department of Pathology and Center for Discovery and Innovation in Parasitic Diseases, University of California, San Francisco, San Francisco, CA, USA.|Department of Computer Science, San Francisco State University, San Francisco, CA, USA, Department of Pathology and Center for Discovery and Innovation in Parasitic Diseases, University of California, San Francisco, San Francisco, CA, USA Department of Computer Science, San Francisco State University, San Francisco, CA, USA, Department of Pathology and Center for Discovery and Innovation in Parasitic Diseases, University of California, San Francisco, San Francisco, CA, USA.|Department of Computer Science, San Francisco State University, San Francisco, CA, USA, Department of Pathology and Center for Discovery and Innovation in Parasitic Diseases, University of California, San Francisco, San Francisco, CA, USA Department of Computer Science, San Francisco State University, San Francisco, CA, USA, Department of Pathology and Center for Discovery and Innovation in Parasitic Diseases, University of California, San Francisco, San Francisco, CA, USA.|Department of Computer Science, San Francisco State University, San Francisco, CA, USA, Department of Pathology and Center for Discovery and Innovation in Parasitic Diseases, University of California, San Francisco, San Francisco, CA, USA Department of Computer Science, San Francisco State University, San Francisco, CA, USA, Department of Pathology and Center for Discovery and Innovation in Parasitic Diseases, University of California, San Francisco, San Francisco, CA, USA.', 'United States|United States|United States|United States|United States', 10, 'Animals|Anthelmintics|Dose-Response Relationship, Drug|Internet|Parasitic Sensitivity Tests|Phenotype|Schistosoma|Schistosomicides|Software', 'Journal Article', '10.1093/bioinformatics/btu831', '25540182', 'Neglected tropical diseases (NTDs) caused by helminths constitute some of the most common infections of the worlds poorest people. The etiological agents are complex and recalcitrant to standard techniques of molecular biology. Drug screening against helminths has often been phenotypic and typically involves manual description of drug effect and efficacy. A key challenge is to develop automated, quantitative approaches to drug screening against helminth diseases. The quantal dose-response calculator (QDREC) constitutes a significant step in this direction. It can be used to automatically determine quantitative dose-response characteristics and half-maximal effective concentration (EC50) values using image-based readouts from phenotypic screens, thereby allowing rigorous comparisons of the efficacies of drug compounds. QDREC has been developed and validated in the context of drug screening for schistosomiasis, one of the most important NTDs. However, it is equally applicable to general phenotypic screening involving helminths and other complex parasites.'),
(78950, 2015, 'bio', 'RRDistMaps: a UCSF Chimera tool for viewing and comparing protein distance maps', 'Chen, Jonathan E|Huang, Conrad C|Ferrin, Thomas E', 'Lowell High School, San Francisco, CA and Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA, USA.|Lowell High School, San Francisco, CA and Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA, USA.|Lowell High School, San Francisco, CA and Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, CA, USA.', 'United States|United States|United States', 0, 'Binding Sites|Models, Molecular|Protein Binding|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu841', '25540183', 'Contact maps are a convenient method for the structural biologists to identify structural features through two-dimensional simplification. Binary (yes/no) contact maps with a single cutoff distance can be generalized to show continuous distance ranges. We have developed a UCSF Chimera tool, RRDistMaps, to compute such generalized maps in order to analyze pairwise variations in intramolecular contacts. An interactive utility, RRDistMaps, visualizes conformational changes, both local (e.g. binding-site residues) and global (e.g. hinge motion), between unbound and bound proteins through distance patterns. Users can target residue pairs in RRDistMaps for further navigation in Chimera. The interface contains the unique features of identifying long-range residue motion and aligning sequences to simultaneously compare distance maps.'),
(78951, 2015, 'bio', 'J-Circos: an interactive Circos plotter', 'An, Jiyuan|Lai, John|Sajjanhar, Atul|Batra, Jyotsna|Wang, Chenwei|Nelson, Colleen C', 'Australian Prostate Cancer Research Centre-Queensland, Institute of Health and Biomedical Innovation, Queensland University of Technology, Princess Alexandra Hospital and Translational Research Institute, Brisbane, QLD 4102, Australia and School of Information Technology, Deakin University, Burwood, VIC 3125, Australia.|Australian Prostate Cancer Research Centre-Queensland, Institute of Health and Biomedical Innovation, Queensland University of Technology, Princess Alexandra Hospital and Translational Research Institute, Brisbane, QLD 4102, Australia and School of Information Technology, Deakin University, Burwood, VIC 3125, Australia.|Australian Prostate Cancer Research Centre-Queensland, Institute of Health and Biomedical Innovation, Queensland University of Technology, Princess Alexandra Hospital and Translational Research Institute, Brisbane, QLD 4102, Australia and School of Information Technology, Deakin University, Burwood, VIC 3125, Australia.|Australian Prostate Cancer Research Centre-Queensland, Institute of Health and Biomedical Innovation, Queensland University of Technology, Princess Alexandra Hospital and Translational Research Institute, Brisbane, QLD 4102, Australia and School of Information Technology, Deakin University, Burwood, VIC 3125, Australia.|Australian Prostate Cancer Research Centre-Queensland, Institute of Health and Biomedical Innovation, Queensland University of Technology, Princess Alexandra Hospital and Translational Research Institute, Brisbane, QLD 4102, Australia and School of Information Technology, Deakin University, Burwood, VIC 3125, Australia.|Australian Prostate Cancer Research Centre-Queensland, Institute of Health and Biomedical Innovation, Queensland University of Technology, Princess Alexandra Hospital and Translational Research Institute, Brisbane, QLD 4102, Australia and School of Information Technology, Deakin University, Burwood, VIC 3125, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia', 30, 'Chromosomes|Computer Graphics|Gene Fusion|Software', 'Journal Article', '10.1093/bioinformatics/btu842', '25540184', 'Circos plots are graphical outputs that display three dimensional chromosomal interactions and fusion transcripts. However, the Circos plot tool is not an interactive visualization tool, but rather a figure generator. For example, it does not enable data to be added dynamically nor does it provide information for specific data points interactively. Recently, an R-based Circos tool (RCircos) has been developed to integrate Circos to R, but similarly, Rcircos can only be used to generate plots. Thus, we have developed a Circos plot tool (J-Circos) that is an interactive visualization tool that can plot Circos figures, as well as being able to dynamically add data to the figure, and providing information for specific data points using mouse hover display and zoom in/out functions. J-Circos uses the Java computer language to enable, it to be used on most operating systems (Windows, MacOS, Linux). Users can input data into J-Circos using flat data formats, as well as from the Graphical user interface (GUI). J-Circos will enable biologists to better study more complex chromosomal interactions and fusion transcripts that are otherwise difficult to visualize from next-generation sequencing data.'),
(78952, 2015, 'bio', 'UProC: tools for ultra-fast protein domain classification', 'Meinicke, Peter', 'Department of Bioinformatics, Institute for Microbiology and Genetics, University of Gxc3xb6ttingen, Germany.', 'Germany', 29, 'Algorithms|Metagenome|Metagenomics|Open Reading Frames|Protein Structure, Tertiary|Software', 'Journal Article', '10.1093/bioinformatics/btu843', '25540185', 'With rapidly increasing volumes of biological sequence data the functional analysis of new sequences in terms of similarities to known protein families challenges classical bioinformatics.'),
(78953, 2015, 'bio', 'Knowledge-based modeling of peptides at protein interfaces: PiPreD', 'Oliva, Baldo|Fernandez-Fuentes, Narcis', 'Structural Bioinformatics Lab (GRIB), Departament de Ciencies Experimental i de la Salut, Universitat Pompeu Fabra, 08003 Barcelona, Spain.|Structural Bioinformatics Lab (GRIB), Departament de Ciencies Experimental i de la Salut, Universitat Pompeu Fabra, 08003 Barcelona, Spain.', 'Spain|Spain', 0, 'Algorithms|Databases, Protein|Knowledge Bases|Models, Molecular|Multiprotein Complexes|Peptides|Protein Binding|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btu838', '25540186', 'Protein-protein interactions (PPIs) underpin virtually all cellular processes both in health and disease. Modulating the interaction between proteins by means of small (chemical) agents is therefore a promising route for future novel therapeutic interventions. In this context, peptides are gaining momentum as emerging agents for the modulation of PPIs.'),
(78954, 2015, 'bio', 'Modified screening and ranking algorithm for copy number variation detection', 'Xiao, Feifei|Min, Xiaoyi|Zhang, Heping', 'Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.', 'United States|United States|United States', 0, 'Algorithms|Bayes Theorem|Cluster Analysis|DNA Copy Number Variations|Genome, Human|Genomics|Genotyping Techniques|HapMap Project|Humans|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu850', '25542927', 'Copy number variation (CNV) is a type of structural variation, usually defined as genomic segments that are 1xe2x80x89kb or larger, which present variable copy numbers when compared with a reference genome. The screening and ranking algorithm (SaRa) was recently proposed as an efficient approach for multiple change-points detection, which can be applied to CNV detection. However, some practical issues arise from application of SaRa to single nucleotide polymorphism data.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78955, 2015, 'bio', 'An automatic tool to analyze and cluster macromolecular conformations based on self-organizing maps', 'Bouvier, Guillaume|Desdouits, Nathan|Ferber, Mathias|Blondel, Arnaud|Nilges, Michael', 'Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, F-75015, Paris, France.|Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, F-75015, Paris, France.|Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, F-75015, Paris, France.|Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, F-75015, Paris, France.|Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, F-75015, Paris, France.', 'France|France|France|France|France', 0, 'Algorithms|Cluster Analysis|Molecular Dynamics Simulation|Protein Conformation|Software', 'Journal Article', '10.1093/bioinformatics/btu849', '25543048', 'Sampling the conformational space of biological macromolecules generates large sets of data with considerable complexity. Data-mining techniques, such as clustering, can extract meaningful information. Among them, the self-organizing maps (SOMs) algorithm has shown great promise, in particular since its computation time rises only linearly with the size of the data set. Whereas SOMs are generally used with few neurons, we investigate here their behavior with large numbers of neurons.'),
(78956, 2015, 'bio', 'PRSice: Polygenic Risk Score software', 'Euesden, Jack|Lewis, Cathryn M|OReilly, Paul F', 'MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, United Kingdom.|MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, United Kingdom.|MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Depressive Disorder, Major|Genome-Wide Association Study|Genotyping Techniques|Humans|Linkage Disequilibrium|Multifactorial Inheritance|Phenotype|Polymorphism, Single Nucleotide|Risk|Schizophrenia|Smoking|Software', 'Journal Article', '10.1093/bioinformatics/btu848', '25550326', 'A polygenic risk score (PRS) is a sum of trait-associated alleles across many genetic loci, typically weighted by effect sizes estimated from a genome-wide association study. The application of PRS has grown in recent years as their utility for detecting shared genetic aetiology among traits has become appreciated, PRS can also be used to establish the presence of a genetic signal in underpowered studies, to infer the genetic architecture of a trait, for screening in clinical trials, and can act as a biomarker for a phenotype. Here we present the first dedicated PRS software, PRSice (precise), for calculating, applying, evaluating and plotting the results of PRS. PRSice can calculate PRS at a large number of thresholds (high resolution) to provide the best-fit PRS, as well as provide results calculated at broad P-value thresholds, can thin Single Nucleotide Polymorphisms (SNPs) according to linkage disequilibrium and P-value or use all SNPs, handles genotyped and imputed data, can calculate and incorporate ancestry-informative variables, and can apply PRS across multiple traits in a single run. We exemplify the use of PRSice via application to data on schizophrenia, major depressive disorder and smoking, illustrate the importance of identifying the best-fit PRS and estimate a P-value significance threshold for high-resolution PRS studies.'),
(78957, 2015, 'bio', 'rbamtools: an R interface to samtools enabling fast accumulative tabulation of splicing events over multiple RNA-seq samples', 'Kaisers, Wolfgang|Schaal, Heiner|Schwender, Holger', 'Center for Bioinformatics and Biostatistics, BMFZ, Heinrich Heine University Düsseldorf, Institut für Virologie, and Mathematical Institute, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany.|Center for Bioinformatics and Biostatistics, BMFZ, Heinrich Heine University Düsseldorf, Institut für Virologie, and Mathematical Institute, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany Center for Bioinformatics and Biostatistics, BMFZ, Heinrich Heine University Düsseldorf, Institut für Virologie, and Mathematical Institute, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany.|Center for Bioinformatics and Biostatistics, BMFZ, Heinrich Heine University Düsseldorf, Institut für Virologie, and Mathematical Institute, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany Center for Bioinformatics and Biostatistics, BMFZ, Heinrich Heine University Düsseldorf, Institut für Virologie, and Mathematical Institute, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany.', 'Germany|Germany|Germany', 7, 'Algorithms|Computational Biology|Genomics|High-Throughput Nucleotide Sequencing|Humans|RNA Splicing|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu846', '25563331', 'The open source environment R isf the most widely used software to statistically explore biological data sets including sequence alignments. BAM is the de facto standard file format for sequence alignment. With rbamtools, we provide now a full spectrum of accessibility to BAM for R users such as reading, writing, extraction of subsets and plotting of alignment depth where the script syntax closely follows the SAM/BAM format. Additionally, rbamtools enables fast accumulative tabulation of splicing events over multiple BAM files.'),
(78958, 2015, 'bio', 'Co-expression analysis of high-throughput transcriptome sequencing data with Poisson mixture models', 'Rau, Andrea|Maugis-Rabusseau, Cathy|Martin-Magniette, Marie-Laure|Celeux, Gilles', 'INRA, UMR1313 Génétique animale et biologie intégrative, Jouy-en-Josas, France, AgroParisTech, UMR1313 Génétique animale et biologie intégrative, Paris 05, France, Institut de Mathématiques de Toulouse, INSA de Toulouse, Université de Toulouse, Toulouse, France, UMR AgroParisTech/INRA MIA 518, Paris, France, INRA, UMR 1165 URGV, Saclay Plant Sciences, Evry, France, UEVE, UMR URGV, Saclay Plant Sciences, Evry, France, CNRS, ERL 8196, URGV, Saclay Plant Sciences, Evry, France and Inria Saclay - Île-de-France, Orsay, France INRA, UMR1313 Génétique animale et biologie intégrative, Jouy-en-Josas, France, AgroParisTech, UMR1313 Génétique animale et biologie intégrative, Paris 05, France, Institut de Mathématiques de Toulouse, INSA de Toulouse, Université de Toulouse, Toulouse, France, UMR AgroParisTech/INRA MIA 518, Paris, France, INRA, UMR 1165 URGV, Saclay Plant Sciences, Evry, France, UEVE, UMR URGV, Saclay Plant Sciences, Evry, France, CNRS, ERL 8196, URGV, Saclay Plant Sciences, Evry, France and Inria Saclay - Île-de-France, Orsay, France.|INRA, UMR1313 Génétique animale et biologie intégrative, Jouy-en-Josas, France, AgroParisTech, UMR1313 Génétique animale et biologie intégrative, Paris 05, France, Institut de Mathématiques de Toulouse, INSA de Toulouse, Université de Toulouse, Toulouse, France, UMR AgroParisTech/INRA MIA 518, Paris, France, INRA, UMR 1165 URGV, Saclay Plant Sciences, Evry, France, UEVE, UMR URGV, Saclay Plant Sciences, Evry, France, CNRS, ERL 8196, URGV, Saclay Plant Sciences, Evry, France and Inria Saclay - Île-de-France, Orsay, France.|INRA, UMR1313 Génétique animale et biologie intégrative, Jouy-en-Josas, France, AgroParisTech, UMR1313 Génétique animale et biologie intégrative, Paris 05, France, Institut de Mathématiques de Toulouse, INSA de Toulouse, Université de Toulouse, Toulouse, France, UMR AgroParisTech/INRA MIA 518, Paris, France, INRA, UMR 1165 URGV, Saclay Plant Sciences, Evry, France, UEVE, UMR URGV, Saclay Plant Sciences, Evry, France, CNRS, ERL 8196, URGV, Saclay Plant Sciences, Evry, France and Inria Saclay - Île-de-France, Orsay, France INRA, UMR1313 Génétique animale et biologie intégrative, Jouy-en-Josas, France, AgroParisTech, UMR1313 Génétique animale et biologie intégrative, Paris 05, France, Institut de Mathématiques de Toulouse, INSA de Toulouse, Université de Toulouse, Toulouse, France, UMR AgroParisTech/INRA MIA 518, Paris, France, INRA, UMR 1165 URGV, Saclay Plant Sciences, Evry, France, UEVE, UMR URGV, Saclay Plant Sciences, Evry, France, CNRS, ERL 8196, URGV, Saclay Plant Sciences, Evry, France and Inria Saclay - Île-de-France, Orsay, France INRA, UMR1313 Génétique animale et biologie intégrative, Jouy-en-Josas, France, AgroParisTech, UMR1313 Génétique animale et biologie intégrative, Paris 05, France, Institut de Mathématiques de Toulouse, INSA de Toulouse, Université de Toulouse, Toulouse, France, UMR AgroParisTech/INRA MIA 518, Paris, France, INRA, UMR 1165 URGV, Saclay Plant Sciences, Evry, France, UEVE, UMR URGV, Saclay Plant Sciences, Evry, France, CNRS, ERL 8196, URGV, Saclay Plant Sciences, Evry, France and Inria Saclay - Île-de-France, Orsay, France INRA, UMR1313 Génétique animale et biologie intégrative, Jouy-en-Josas, France, AgroParisTech, UMR1313 Génétique animale et biologie intégrative, Paris 05, France, Institut de Mathématiques de Toulouse, INSA de Toulouse, Université de Toulouse, Toulouse, France, UMR AgroParisTech/INRA MIA 518, Paris, France, INRA, UMR 1165 URGV, Saclay Plant Sciences, Evry, France, UEVE, UMR URGV,|INRA, UMR1313 Génétique animale et biologie intégrative, Jouy-en-Josas, France, AgroParisTech, UMR1313 Génétique animale et biologie intégrative, Paris 05, France, Institut de Mathématiques de Toulouse, INSA de Toulouse, Université de Toulouse, Toulouse, France, UMR AgroParisTech/INRA MIA 518, Paris, France, INRA, UMR 1165 URGV, Saclay Plant Sciences, Evry, France, UEVE, UMR URGV, Saclay Plant Sciences, Evry, France, CNRS, ERL 8196, URGV, Saclay Plant Sciences, Evry, France and Inria Saclay - Île-de-France, Orsay, France.', 'France|France|France|France', 29, 'Animals|Cell Line|Cluster Analysis|Drosophila melanogaster|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Liver|Models, Statistical|Poisson Distribution|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btu845', '25563332', 'In recent years, gene expression studies have increasingly made use of high-throughput sequencing technology. In turn, research concerning the appropriate statistical methods for the analysis of digital gene expression (DGE) has flourished, primarily in the context of normalization and differential analysis.'),
(78959, 2015, 'bio', 'GlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome', 'Li, Fuyi|Li, Chen|Wang, Mingjun|Webb, Geoffrey I|Zhang, Yang|Whisstock, James C|Song, Jiangning', 'College of Information Engineering, Northwest A&F University, Yangling 712100, China, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia, National Engineering Laboratory for Industrial Enzymes and Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China, Centre for Research in Intelligent Systems, Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia and ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, Melbourne, VIC 3800, Australia.|College of Information Engineering, Northwest A&F University, Yangling 712100, China, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia, National Engineering Laboratory for Industrial Enzymes and Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China, Centre for Research in Intelligent Systems, Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia and ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, Melbourne, VIC 3800, Australia.|College of Information Engineering, Northwest A&F University, Yangling 712100, China, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia, National Engineering Laboratory for Industrial Enzymes and Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China, Centre for Research in Intelligent Systems, Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia and ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, Melbourne, VIC 3800, Australia.|College of Information Engineering, Northwest A&F University, Yangling 712100, China, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia, National Engineering Laboratory for Industrial Enzymes and Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China, Centre for Research in Intelligent Systems, Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia and ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, Melbourne, VIC 3800, Australia.|College of Information Engineering, Northwest A&F University, Yangling 712100, China, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia, National Engineering Laboratory for Industrial Enzymes and Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China, Centre for Research in Intelligent Systems, Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia and ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, Melbourne, VIC 3800, Australia.|College of Information Engineering, Northwest A&F University, Yangling 712100, China, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia, National Engineering Laboratory for Industrial Enzymes and Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China, Centre for Research in Intelligent Systems, Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia and ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, Melbourne, VIC 3800, Australia College of Information Engineering, Northwest A&F University, Yangling 712100, China, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia, National Engineering Laboratory for Industrial Enzymes and Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China, Centre for Research in Intelligent Systems, Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia and ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, Melbourne, VIC 3800, Australia.|College of Information Engineering, Northwest A&F University, Yangling 712100, China, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia, National Engineering Laboratory for Industrial Enzymes and Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China, Centre for Research in Intelligent Systems, Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia and ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, Melbourne, VIC 3800, Australia College of Information Engineering, Northwest A&F University, Yangling 712100, China, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia, National Engineering Laboratory for Industrial Enzymes and Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China, Centre for Research in Intelligent Systems, Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia and ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, Melbourne, VIC 3800, Australia College of Information Engineering, Northwest A&F University, Yangling 712100, China, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC 3800, Australia, National Engineering Laboratory for Industrial Enzymes and Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China, Centre for Research in Intelligent Systems, Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia and ARC Centre of Excellence in Advanced Molecular Imaging, Monash University, Melbourne, VIC 3800, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia', 77, 'Algorithms|Amino Acids|Artificial Intelligence|Glycosylation|Humans|Protein Processing, Post-Translational|Proteome|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btu852', '25568279', 'Glycosylation is a ubiquitous type of protein post-translational modification (PTM) in eukaryotic cells, which plays vital roles in various biological processes (BPs) such as cellular communication, ligand recognition and subcellular recognition. It is estimated that >50% of the entire human proteome is glycosylated. However, it is still a significant challenge to identify glycosylation sites, which requires expensive/laborious experimental research. Thus, bioinformatics approaches that can predict the glycan occupancy at specific sequons in protein sequences would be useful for understanding and utilizing this important PTM.'),
(78960, 2015, 'bio', 'The anisotropic network model web server at 2015 (ANM 20)', 'Eyal, Eran|Lum, Gengkon|Bahar, Ivet', 'Cancer Research Institute, Sheba Medical Center, 2 Sheba Rd, Ramat Gan 52621, Israel and Department of Computational and System Biology, University of Pittsburgh, 3501 Fifth Ave, Pittsburgh, PA 15213, USA.|Cancer Research Institute, Sheba Medical Center, 2 Sheba Rd, Ramat Gan 52621, Israel and Department of Computational and System Biology, University of Pittsburgh, 3501 Fifth Ave, Pittsburgh, PA 15213, USA.|Cancer Research Institute, Sheba Medical Center, 2 Sheba Rd, Ramat Gan 52621, Israel and Department of Computational and System Biology, University of Pittsburgh, 3501 Fifth Ave, Pittsburgh, PA 15213, USA.', 'Israel|Israel|Israel', 77, 'Anisotropy|DNA|DNA-Binding Proteins|Internet|Ligands|Motion|Protein Conformation|Proteins|RNA|RNA-Binding Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu847', '25568280', 'The anisotropic network model (ANM) is one of the simplest yet powerful tools for exploring protein dynamics. Its main utility is to predict and visualize the collective motions of large complexes and assemblies near their equilibrium structures. The ANM server, introduced by us in 2006 helped making this tool more accessible to non-sophisticated users. We now provide a new version (ANM 2.0), which allows inclusion of nucleic acids and ligands in the network model and thus enables the investigation of the collective motions of protein-DNA/RNA and -ligand systems. The new version offers the flexibility of defining the system nodes and the interaction types and cutoffs. It also includes extensive improvements in hardware, software and graphical interfaces.'),
(78961, 2015, 'bio', 'Selection of models for the analysis of risk-factor trees: leveraging biological knowledge to mine large sets of risk factors with application to microbiome data', 'Zhang, Qunyuan|Abel, Haley|Wells, Alan|Lenzini, Petra|Gomez, Felicia|Province, Michael A|Templeton, Alan A|Weinstock, George M|Salzman, Nita H|Borecki, Ingrid B', 'Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA, Department of Biology, Washington University, St. Louis, MO, USA, The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA and Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.|Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA, Department of Biology, Washington University, St. Louis, MO, USA, The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA and Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.|Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA, Department of Biology, Washington University, St. Louis, MO, USA, The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA and Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.|Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA, Department of Biology, Washington University, St. Louis, MO, USA, The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA and Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.|Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA, Department of Biology, Washington University, St. Louis, MO, USA, The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA and Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.|Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA, Department of Biology, Washington University, St. Louis, MO, USA, The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA and Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.|Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA, Department of Biology, Washington University, St. Louis, MO, USA, The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA and Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA, Department of Biology, Washington University, St. Louis, MO, USA, The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA and Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.|Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA, Department of Biology, Washington University, St. Louis, MO, USA, The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA and Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.|Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA, Department of Biology, Washington University, St. Louis, MO, USA, The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA and Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.|Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA, Department of Biology, Washington University, St. Louis, MO, USA, The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA and Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 8, 'Animals|Cercopithecus aethiops|Decision Trees|Gastrointestinal Tract|Humans|Logistic Models|Microbiota|Models, Statistical|Phenotype|RNA, Ribosomal|Risk Assessment|Risk Factors', 'Journal Article', '10.1093/bioinformatics/btu855', '25568281', 'Establishment of a statistical association between microbiome features and clinical outcomes is of growing interest because of the potential for yielding insights into biological mechanisms and pathogenesis. Extracting microbiome features that are relevant for a disease is challenging and existing variable selection methods are limited due to large number of risk factor variables from microbiome sequence data and their complex biological structure.'),
(78962, 2015, 'bio', 'A haplotype-based framework for group-wise transmission/disequilibrium tests for rare variant association analysis', 'Chen, Rui|Wei, Qiang|Zhan, Xiaowei|Zhong, Xue|Sutcliffe, James S|Cox, Nancy J|Cook, Edwin H|Li, Chun|Chen, Wei|Li, Bingshan', 'Department of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA Department of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 7, 'Autistic Disorder|Computer Simulation|Data Interpretation, Statistical|Exome|Genetic Association Studies|Genetic Variation|Haplotypes|Humans|Linkage Disequilibrium|Models, Genetic|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu860', '25568282', 'A major focus of current sequencing studies for human genetics is to identify rare variants associated with complex diseases. Aside from reduced power of detecting associated rare variants, controlling for population stratification is particularly challenging for rare variants. Transmission/disequilibrium tests (TDT) based on family designs are robust to population stratification and admixture, and therefore provide an effective approach to rare variant association studies to eliminate spurious associations. To increase power of rare variant association analysis, gene-based collapsing methods become standard approaches for analyzing rare variants. Existing methods that extend this strategy to rare variants in families usually combine TDT statistics at individual variants and therefore lack the flexibility of incorporating other genetic models.'),
(78963, 2015, 'bio', 'Clonality inference in multiple tumor samples using phylogeny', 'Malikic, Salem|McPherson, Andrew W|Donmez, Nilgun|Sahinalp, Cenk S', 'School of Computing Science, Simon Fraser University, Burnaby, BC, Canada, BC Cancer Agency, Vancouver, BC, Canada, Vancouver Prostate Center, Vancouver, BC, Canada and School of Informatics and Computing, Indiana University, Bloomington, IN, USA.|School of Computing Science, Simon Fraser University, Burnaby, BC, Canada, BC Cancer Agency, Vancouver, BC, Canada, Vancouver Prostate Center, Vancouver, BC, Canada and School of Informatics and Computing, Indiana University, Bloomington, IN, USA.|School of Computing Science, Simon Fraser University, Burnaby, BC, Canada, BC Cancer Agency, Vancouver, BC, Canada, Vancouver Prostate Center, Vancouver, BC, Canada and School of Informatics and Computing, Indiana University, Bloomington, IN, USA.|School of Computing Science, Simon Fraser University, Burnaby, BC, Canada, BC Cancer Agency, Vancouver, BC, Canada, Vancouver Prostate Center, Vancouver, BC, Canada and School of Informatics and Computing, Indiana University, Bloomington, IN, USA School of Computing Science, Simon Fraser University, Burnaby, BC, Canada, BC Cancer Agency, Vancouver, BC, Canada, Vancouver Prostate Center, Vancouver, BC, Canada and School of Informatics and Computing, Indiana University, Bloomington, IN, USA.', 'Canada|Canada|Canada|Canada', 85, 'Algorithms|Clonal Evolution|DNA Mutational Analysis|High-Throughput Nucleotide Sequencing|Humans|Leukemia, Lymphocytic, Chronic, B-Cell|Leukemia, Myeloid, Acute|Mutation|Neoplasms|Phylogeny', 'Evaluation Studies', '10.1093/bioinformatics/btv003', '25568283', 'Intra-tumor heterogeneity presents itself through the evolution of subclones during cancer progression. Although recent research suggests that this heterogeneity has clinical implications, in silico determination of the clonal subpopulations remains a challenge.'),
(78964, 2015, 'bio', 'Integrating alignment-based and alignment-free sequence similarity measures for biological sequence classification', 'Borozan, Ivan|Watt, Stuart|Ferretti, Vincent', 'Department of Informatics and Bio-computing, Ontario Institute for Cancer Research, MaRS Centre, South Tower, 101 College Street, Suite 800, Toronto, Ontario, Canada.|Department of Informatics and Bio-computing, Ontario Institute for Cancer Research, MaRS Centre, South Tower, 101 College Street, Suite 800, Toronto, Ontario, Canada.|Department of Informatics and Bio-computing, Ontario Institute for Cancer Research, MaRS Centre, South Tower, 101 College Street, Suite 800, Toronto, Ontario, Canada.', 'Canada|Canada|Canada', 20, 'Algorithms|Classification|DNA, Viral|Metagenomics|Models, Theoretical|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Viruses', 'Evaluation Studies', '10.1093/bioinformatics/btv006', '25573913', 'Alignment-based sequence similarity searches, while accurate for some type of sequences, can produce incorrect results when used on more divergent but functionally related sequences that have undergone the sequence rearrangements observed in many bacterial and viral genomes. Here, we propose a classification model that exploits the complementary nature of alignment-based and alignment-free similarity measures with the aim to improve the accuracy with which DNA and protein sequences are characterized.'),
(78965, 2015, 'bio', 'Inferring single-cell gene expression mechanisms using stochastic simulation', 'Daigle, Bernie J|Soltani, Mohammad|Petzold, Linda R|Singh, Abhyudai', 'Institute for Collaborative Biotechnologies, University of California, Santa Barbara, CA 93106, Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716 and Department of Computer Science, University of California, Santa Barbara, CA 93106, USA.|Institute for Collaborative Biotechnologies, University of California, Santa Barbara, CA 93106, Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716 and Department of Computer Science, University of California, Santa Barbara, CA 93106, USA.|Institute for Collaborative Biotechnologies, University of California, Santa Barbara, CA 93106, Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716 and Department of Computer Science, University of California, Santa Barbara, CA 93106, USA.|Institute for Collaborative Biotechnologies, University of California, Santa Barbara, CA 93106, Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716 and Department of Computer Science, University of California, Santa Barbara, CA 93106, USA.', 'United States|United States|United States|United States', 23, 'Animals|Computer Simulation|Gene Expression|Glutaminase|Mice|Models, Genetic|Monte Carlo Method|Promoter Regions, Genetic|Single-Cell Analysis|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btv007', '25573914', 'Stochastic promoter switching between transcriptionally active (ON) and inactive (OFF) states is a major source of noise in gene expression. It is often implicitly assumed that transitions between promoter states are memoryless, i.e. promoters spend an exponentially distributed time interval in each of the two states. However, increasing evidence suggests that promoter ON/OFF times can be non-exponential, hinting at more complex transcriptional regulatory architectures. Given the essential role of gene expression in all cellular functions, efficient computational techniques for characterizing promoter architectures are critically needed.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78966, 2015, 'bio', 'DDIG-in: detecting disease-causing genetic variations due to frameshifting indels and nonsense mutations employing sequence and structural properties at nucleotide and protein levels', 'Folkman, Lukas|Yang, Yuedong|Li, Zhixiu|Stantic, Bela|Sattar, Abdul|Mort, Matthew|Cooper, David N|Liu, Yunlong|Zhou, Yaoqi', 'School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardif|School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardif|School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardif|School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA.|School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardif|School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA.|School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA.|School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA.|School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK and Department of Medical and Molecular Genetics, Indiana University School of Medicine, 975 West Walnut Street, MRL Bldg IB130, Indianapolis, IN 46202, USA School of Information and Communication Technology, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia, Queensland Research Laboratory, NICTA - National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia, Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia, Institute of Medical Genetics, Cardiff University, Heath Park, Cardif', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 30, 'Algorithms|Artificial Intelligence|Codon, Nonsense|Conserved Sequence|Databases, Genetic|Disease|Frameshift Mutation|Humans|INDEL Mutation|Nucleotides|Proteins', 'Journal Article', '10.1093/bioinformatics/btu862', '25573915', 'Frameshifting (FS) indels and nonsense (NS) variants disrupt the protein-coding sequence downstream of the mutation site by changing the reading frame or introducing a premature termination codon, respectively. Despite such drastic changes to the protein sequence, FS indels and NS variants have been discovered in healthy individuals. How to discriminate disease-causing from neutral FS indels and NS variants is an understudied problem.'),
(78967, 2015, 'bio', 'Combining tree-based and dynamical systems for the inference of gene regulatory networks', 'Huynh-Thu, Vân Anh|Sanguinetti, Guido', 'School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, and SynthSys - Systems and Synthetic Biology, University of Edinburgh, Edinburgh EH9 3JD, UK.|School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, and SynthSys - Systems and Synthetic Biology, University of Edinburgh, Edinburgh EH9 3JD, UK School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, and SynthSys - Systems and Synthetic Biology, University of Edinburgh, Edinburgh EH9 3JD, UK.', 'United Kingdom|United Kingdom', 50, 'Algorithms|Animals|Computational Biology|Databases, Factual|Decision Trees|Gene Expression Regulation|Gene Regulatory Networks|Macrophages|Mice|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Systems Biology|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btu863', '25573916', 'Reconstructing the topology of gene regulatory networks (GRNs) from time series of gene expression data remains an important open problem in computational systems biology. Existing GRN inference algorithms face one of two limitations: model-free methods are scalable but suffer from a lack of interpretability and cannot in general be used for out of sample predictions. On the other hand, model-based methods focus on identifying a dynamical model of the system. These are clearly interpretable and can be used for predictions, however, they rely on strong assumptions and are typically very demanding computationally.'),
(78968, 2015, 'bio', 'PVAAS: identify variants associated with aberrant splicing from RNA-seq', 'Wang, Liguo|Nie, Jinfu J|Kocher, Jean-Pierre A', 'Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.|Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.', 'United States|United States|United States', 1, 'Alternative Splicing|Gene Expression Profiling|Genetic Variation|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btv001', '25573917', 'RNA-seq has been widely used to study the transcriptome. Comparing to microarray, sequencing-based RNA-seq is able to identify splicing variants and single nucleotide variants in one experiment simultaneously. This provides unique opportunity to detect variants that associated with aberrant splicing. Despite the popularity of RNA-seq, no bioinformatics tool has been developed to leverage this advantage to identify variants associated with aberrant splicing.'),
(78969, 2015, 'bio', 'LINKPHASE3: an improved pedigree-based phasing algorithm robust to genotyping and map errors', 'Druet, Tom|Georges, Michel', 'Unit of Animal Genomics, GIGA-R, University of Liège (B34), 1 avenue de lHôpital, B-4000, Liège, Belgium.|Unit of Animal Genomics, GIGA-R, University of Liège (B34), 1 avenue de lHôpital, B-4000, Liège, Belgium.', 'Belgium|Belgium', 14, 'Algorithms|Animals|Chromosome Mapping|Genotyping Techniques|Haplotypes|Pedigree|Software', 'Journal Article', '10.1093/bioinformatics/btu859', '25573918', 'Many applications in genetics require haplotype reconstruction. We present a phasing program designed for large half-sibs families (as observed in plant and animals) that is robust to genotyping and map errors. We demonstrate that it is more efficient than previous versions and other programs, particularly in the presence of genotyping errors.'),
(78970, 2015, 'bio', 'RNA-Rocket: an RNA-Seq analysis resource for infectious disease research', 'Warren, Andrew S|Aurrecoechea, Cristina|Brunk, Brian|Desai, Prerak|Emrich, Scott|Giraldo-Calderón, Gloria I|Harb, Omar|Hix, Deborah|Lawson, Daniel|Machi, Dustin|Mao, Chunhong|McClelland, Michael|Nordberg, Eric|Shukla, Maulik|Vosshall, Leslie B|Wattam, Alice R|Will, Rebecca|Yoo, Hyun Seung|Sobral, Bruno', 'Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Center for Tropical & Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA, Penn Center for Bioinformatics and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA, Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46656-0369, USA, University of California, Department of Microbiology and Molecular Genetics, Irvine, California, USA and The Rockefeller University, Howard Hughes Medical Institute, New York, NY 10065, USA.', 'Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Geor', 10, 'Animals|Bacteria|Disease Vectors|Gene Expression Profiling|Genomics|High-Throughput Screening Assays|Parasites|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btv002', '25573919', 'RNA-Seq is a method for profiling transcription using high-throughput sequencing and is an important component of many research projects that wish to study transcript isoforms, condition specific expression and transcriptional structure. The methods, tools and technologies used to perform RNA-Seq analysis continue to change, creating a bioinformatics challenge for researchers who wish to exploit these data. Resources that bring together genomic data, analysis tools, educational material and computational infrastructure can minimize the overhead required of life science researchers.'),
(78971, 2015, 'bio', 'Acquire: an open-source comprehensive cancer biobanking system', 'Dowst, Heidi|Pew, Benjamin|Watkins, Chris|McOwiti, Apollo|Barney, Jonathan|Qu, Shijing|Becnel, Lauren B', 'Dan L. Duncan Cancer Center, Department of Medicine, Section of Hematology and Oncology and Department of Molecular and Cellular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA.|Dan L. Duncan Cancer Center, Department of Medicine, Section of Hematology and Oncology and Department of Molecular and Cellular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA.|Dan L. Duncan Cancer Center, Department of Medicine, Section of Hematology and Oncology and Department of Molecular and Cellular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA.|Dan L. Duncan Cancer Center, Department of Medicine, Section of Hematology and Oncology and Department of Molecular and Cellular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA.|Dan L. Duncan Cancer Center, Department of Medicine, Section of Hematology and Oncology and Department of Molecular and Cellular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA.|Dan L. Duncan Cancer Center, Department of Medicine, Section of Hematology and Oncology and Department of Molecular and Cellular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA.|Dan L. Duncan Cancer Center, Department of Medicine, Section of Hematology and Oncology and Department of Molecular and Cellular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA Dan L. Duncan Cancer Center, Department of Medicine, Section of Hematology and Oncology and Department of Molecular and Cellular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA Dan L. Duncan Cancer Center, Department of Medicine, Section of Hematology and Oncology and Department of Molecular and Cellular Biology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA.', 'United States|United States|United States|United States|United States|United States|United States', 7, 'Biological Specimen Banks|Computational Biology|Data Mining|Database Management Systems|Databases, Factual|Genomics|Humans|Information Storage and Retrieval|Neoplasms|Quality Control|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btv012', '25573920', 'The probability of effective treatment of cancer with a targeted therapeutic can be improved for patients with defined genotypes containing actionable mutations. To this end, many human cancer biobanks are integrating more tightly with genomic sequencing facilities and with those creating and maintaining patient-derived xenografts (PDX) and cell lines to provide renewable resources for translational research.'),
(78972, 2015, 'bio', 'Using isoelectric point to determine the pH for initial protein crystallization trials', 'Kirkwood, Jobie|Hargreaves, David|OKeefe, Simon|Wilson, Julie', 'Department of Chemistry, University of York, YO10 5DD, UK, Discovery Sciences, Structure & Biophysics, AstraZeneca Darwin Building, Cambridge, Science Park, Milton Road, Cambridge, CB4 0WG, UK, Department of Computer Science, University of York, YO10 5GH, UK and Department of Mathematics, University of York, YO10 5DD, UK.|Department of Chemistry, University of York, YO10 5DD, UK, Discovery Sciences, Structure & Biophysics, AstraZeneca Darwin Building, Cambridge, Science Park, Milton Road, Cambridge, CB4 0WG, UK, Department of Computer Science, University of York, YO10 5GH, UK and Department of Mathematics, University of York, YO10 5DD, UK.|Department of Chemistry, University of York, YO10 5DD, UK, Discovery Sciences, Structure & Biophysics, AstraZeneca Darwin Building, Cambridge, Science Park, Milton Road, Cambridge, CB4 0WG, UK, Department of Computer Science, University of York, YO10 5GH, UK and Department of Mathematics, University of York, YO10 5DD, UK.|Department of Chemistry, University of York, YO10 5DD, UK, Discovery Sciences, Structure & Biophysics, AstraZeneca Darwin Building, Cambridge, Science Park, Milton Road, Cambridge, CB4 0WG, UK, Department of Computer Science, University of York, YO10 5GH, UK and Department of Mathematics, University of York, YO10 5DD, UK Department of Chemistry, University of York, YO10 5DD, UK, Discovery Sciences, Structure & Biophysics, AstraZeneca Darwin Building, Cambridge, Science Park, Milton Road, Cambridge, CB4 0WG, UK, Department of Computer Science, University of York, YO10 5GH, UK and Department of Mathematics, University of York, YO10 5DD, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 24, 'Crystallization|Hydrogen-Ion Concentration|Isoelectric Point|Proteins', 'Journal Article', '10.1093/bioinformatics/btv011', '25573921', 'The identification of suitable conditions for crystallization is a rate-limiting step in protein structure determination. The pH of an experiment is an important parameter and has the potential to be used in data-mining studies to help reduce the number of crystallization trials required. However, the pH is usually recorded as that of the buffer solution, which can be highly inaccurate.'),
(78973, 2015, 'bio', 'MADGiC: a model-based approach for identifying driver genes in cancer', 'Korthauer, Keegan D|Kendziorski, Christina', 'Department of Statistics and Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison WI 53706, USA.|Department of Statistics and Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison WI 53706, USA.', 'United States|United States', 0, 'Carcinoma, Squamous Cell|Computational Biology|Computer Simulation|DNA Mutational Analysis|Data Interpretation, Statistical|Female|Genome, Human|Humans|Lung Neoplasms|Models, Statistical|Mutation|Neoplasm Proteins|Ovarian Neoplasms', 'Journal Article', '10.1093/bioinformatics/btu858', '25573922', 'Identifying and prioritizing somatic mutations is an important and challenging area of cancer research that can provide new insights into gene function as well as new targets for drug development. Most methods for prioritizing mutations rely primarily on frequency-based criteria, where a gene is identified as having a driver mutation if it is altered in significantly more samples than expected according to a background model. Although useful, frequency-based methods are limited in that all mutations are treated equally. It is well known, however, that some mutations have no functional consequence, while others may have a major deleterious impact. The spatial pattern of mutations within a gene provides further insight into their functional consequence. Properly accounting for these factors improves both the power and accuracy of inference. Also important is an accurate background model.'),
(78974, 2015, 'bio', 'Shifted Hamming distance: a fast and accurate SIMD-friendly filter to accelerate alignment verification in read mapping', 'Xin, Hongyi|Greth, John|Emmons, John|Pekhimenko, Gennady|Kingsford, Carl|Alkan, Can|Mutlu, Onur', 'Computer Science Department, Department of Electrical and Computer Engineering, Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA and Department of Computer Engineering, Bilkent University, Bilkent, Ankara 06800, Turkey.|Computer Science Department, Department of Electrical and Computer Engineering, Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA and Department of Computer Engineering, Bilkent University, Bilkent, Ankara 06800, Turkey.|Computer Science Department, Department of Electrical and Computer Engineering, Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA and Department of Computer Engineering, Bilkent University, Bilkent, Ankara 06800, Turkey.|Computer Science Department, Department of Electrical and Computer Engineering, Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA and Department of Computer Engineering, Bilkent University, Bilkent, Ankara 06800, Turkey.|Computer Science Department, Department of Electrical and Computer Engineering, Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA and Department of Computer Engineering, Bilkent University, Bilkent, Ankara 06800, Turkey.|Computer Science Department, Department of Electrical and Computer Engineering, Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA and Department of Computer Engineering, Bilkent University, Bilkent, Ankara 06800, Turkey.|Computer Science Department, Department of Electrical and Computer Engineering, Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA and Department of Computer Engineering, Bilkent University, Bilkent, Ankara 06800, Turkey.', 'Turkey|Turkey|Turkey|Turkey|Turkey|Turkey|Turkey', 18, 'Algorithms|Base Sequence|Computational Biology|Humans|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/btu856', '25577434', 'Calculating the edit-distance (i.e. minimum number of insertions, deletions and substitutions) between short DNA sequences is the primary task performed by seed-and-extend based mappers, which compare billions of sequences. In practice, only sequence pairs with a small edit-distance provide useful scientific data. However, the majority of sequence pairs analyzed by seed-and-extend based mappers differ by significantly more errors than what is typically allowed. Such error-abundant sequence pairs needlessly waste resources and severely hinder the performance of read mappers. Therefore, it is crucial to develop a fast and accurate filter that can rapidly and efficiently detect error-abundant string pairs and remove them from consideration before more computationally expensive methods are used.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78975, 2015, 'bio', 'ENViz: a Cytoscape App for integrated statistical analysis and visualization of sample-matched data with multiple data types', 'Steinfeld, Israel|Navon, Roy|Creech, Michael L|Yakhini, Zohar|Tsalenko, Anya', 'Agilent Laboratories, Tel-Aviv, Israel, Technion - Israel Institute of Technology, Haifa, Israel, Blue Oak Software and Agilent Laboratories, Santa Clara, CA, USA Agilent Laboratories, Tel-Aviv, Israel, Technion - Israel Institute of Technology, Haifa, Israel, Blue Oak Software and Agilent Laboratories, Santa Clara, CA, USA.|Agilent Laboratories, Tel-Aviv, Israel, Technion - Israel Institute of Technology, Haifa, Israel, Blue Oak Software and Agilent Laboratories, Santa Clara, CA, USA.|Agilent Laboratories, Tel-Aviv, Israel, Technion - Israel Institute of Technology, Haifa, Israel, Blue Oak Software and Agilent Laboratories, Santa Clara, CA, USA.|Agilent Laboratories, Tel-Aviv, Israel, Technion - Israel Institute of Technology, Haifa, Israel, Blue Oak Software and Agilent Laboratories, Santa Clara, CA, USA Agilent Laboratories, Tel-Aviv, Israel, Technion - Israel Institute of Technology, Haifa, Israel, Blue Oak Software and Agilent Laboratories, Santa Clara, CA, USA.|Agilent Laboratories, Tel-Aviv, Israel, Technion - Israel Institute of Technology, Haifa, Israel, Blue Oak Software and Agilent Laboratories, Santa Clara, CA, USA.', 'Israel|Israel|Israel|Israel|Israel', 8, 'Breast Neoplasms|Cell Cycle|Computer Graphics|Data Interpretation, Statistical|Female|Gene Expression Profiling|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btu853', '25577435', 'ENViz (Enrichment Analysis and Visualization) is a Cytoscape app that performs joint enrichment analysis of two types of sample matched datasets in the context of systematic annotations. Such datasets may be gene expression or any other high-throughput data collected in the same set of samples. The enrichment analysis is done in the context of pathway information, gene ontology or any custom annotation of the data. The results of the analysis consist of significant associations between profiled elements of one of the datasets to the annotation terms (e.g. miR-19 was associated to the cell-cycle process in breast cancer samples). The results of the enrichment analysis are visualized as an interactive Cytoscape network.'),
(78976, 2015, 'bio', 'PASPA: a web server for mRNA poly(A) site predictions in plants and algae', 'Ji, Guoli|Li, Lei|Li, Qingshun Q|Wu, Xiangdong|Fu, Jingyi|Chen, Gong|Wu, Xiaohui', 'Department of Automation, Innovation Center for Cell Biology and Key Laboratory of the Ministry of Education on Costal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China, Department of Biology, Miami University, Oxford, OH, USA and Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China Department of Automation, Innovation Center for Cell Biology and Key Laboratory of the Ministry of Education on Costal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China, Department of Biology, Miami University, Oxford, OH, USA and Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China.|Department of Automation, Innovation Center for Cell Biology and Key Laboratory of the Ministry of Education on Costal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China, Department of Biology, Miami University, Oxford, OH, USA and Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China.|Department of Automation, Innovation Center for Cell Biology and Key Laboratory of the Ministry of Education on Costal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China, Department of Biology, Miami University, Oxford, OH, USA and Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China Department of Automation, Innovation Center for Cell Biology and Key Laboratory of the Ministry of Education on Costal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China, Department of Biology, Miami University, Oxford, OH, USA and Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China Department of Automation, Innovation Center for Cell Biology and Key Laboratory of the Ministry of Education on Costal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China, Department of Biology, Miami University, Oxford, OH, USA and Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China.|Department of Automation, Innovation Center for Cell Biology and Key Laboratory of the Ministry of Education on Costal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China, Department of Biology, Miami University, Oxford, OH, USA and Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China.|Department of Automation, Innovation Center for Cell Biology and Key Laboratory of the Ministry of Education on Costal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China, Department of Biology, Miami University, Oxford, OH, USA and Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China.|Department of Automation, Innovation Center for Cell Biology and Key Laboratory of the Ministry of Education on Costal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China, Department of Biology, Miami University, Oxford, OH, USA and Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China.|Department of Automation, Innovation Center for Cell Biology and Key Laboratory of the Ministry of Education on Costal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China, Department of Biology, Miami University, Oxford, OH, USA and Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China.', 'China|China|China|China|China|China|China', 0, '3 Untranslated Regions|Algorithms|Chlorophyta|Diatoms|Internet|Poly A|Polyadenylation|RNA, Plant|Rhodophyta|Software', 'Journal Article', '10.1093/bioinformatics/btv004', '25583118', 'Polyadenylation is an essential process during eukaryotic gene expression. Prediction of poly(A) sites helps to define the 3 end of genes, which is important for gene annotation and elucidating gene regulation mechanisms. However, due to limited knowledge of poly(A) signals, it is still challenging to predict poly(A) sites in plants and algae. PASPA is a web server for P: oly( A: ) S: ite prediction in P: lants and A: lgae, which integrates many in-house tools as add-ons to facilitate poly(A) site prediction, visualization and mining. This server can predict poly(A) sites for ten species, including seven previously poly(A) signal non-characterized species, with sensitivity and specificity in a range between 0.80 and 0.95.'),
(78977, 2015, 'bio', 'An integrative approach to predicting the functional effects of non-coding and coding sequence variation', 'Shihab, Hashem A|Rogers, Mark F|Gough, Julian|Mort, Matthew|Cooper, David N|Day, Ian N M|Gaunt, Tom R|Campbell, Colin', 'MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK, Bristol Centre for Systems Biomedicine, University of Bristol, Bristol BS8 2BN, UK, Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK and Institute of Medical Genetics, Cardiff University, Cardiff CF14 4XN, UK MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK, Bristol Centre for Systems Biomedicine, University of Bristol, Bristol BS8 2BN, UK, Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK and Institute of Medical Genetics, Cardiff University, Cardiff CF14 4XN, UK.|MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK, Bristol Centre for Systems Biomedicine, University of Bristol, Bristol BS8 2BN, UK, Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK and Institute of Medical Genetics, Cardiff University, Cardiff CF14 4XN, UK.|MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK, Bristol Centre for Systems Biomedicine, University of Bristol, Bristol BS8 2BN, UK, Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK and Institute of Medical Genetics, Cardiff University, Cardiff CF14 4XN, UK.|MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK, Bristol Centre for Systems Biomedicine, University of Bristol, Bristol BS8 2BN, UK, Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK and Institute of Medical Genetics, Cardiff University, Cardiff CF14 4XN, UK.|MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK, Bristol Centre for Systems Biomedicine, University of Bristol, Bristol BS8 2BN, UK, Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK and Institute of Medical Genetics, Cardiff University, Cardiff CF14 4XN, UK.|MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK, Bristol Centre for Systems Biomedicine, University of Bristol, Bristol BS8 2BN, UK, Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK and Institute of Medical Genetics, Cardiff University, Cardiff CF14 4XN, UK.|MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK, Bristol Centre for Systems Biomedicine, University of Bristol, Bristol BS8 2BN, UK, Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK and Institute of Medical Genetics, Cardiff University, Cardiff CF14 4XN, UK MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK, Bristol Centre for Systems Biomedicine, University of Bristol, Bristol BS8 2BN, UK, Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK and Institute of Medical Genetics, Cardiff University, Cardiff CF14 4XN, UK.|MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK, Bristol Centre for Systems Biomedicine, University of Bristol, Bristol BS8 2BN, UK, Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK and Institute of Medical Genetics, Cardiff University, Cardiff CF14 4XN, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Genetic Variation|Genome, Human|Genome-Wide Association Study|Genomics|Humans|Molecular Sequence Annotation|Open Reading Frames|Phenotype|Untranslated Regions', 'Journal Article', '10.1093/bioinformatics/btv009', '25583119', 'Technological advances have enabled the identification of an increasingly large spectrum of single nucleotide variants within the human genome, many of which may be associated with monogenic disease or complex traits. Here, we propose an integrative approach, named FATHMM-MKL, to predict the functional consequences of both coding and non-coding sequence variants. Our method utilizes various genomic annotations, which have recently become available, and learns to weight the significance of each component annotation source.'),
(78978, 2015, 'bio', 'Repulsive parallel MCMC algorithm for discovering diverse motifs from large sequence sets', 'Ikebata, Hisaki|Yoshida, Ryo', 'Department of Statistical Science, The Graduate University for Advanced Studies (Sokendai), 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, Department of Statistical Modeling, The Institute of Statistical Mathematics, Research Organization of Information and Systems, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, JST-CREST, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, JST-ERATO Sato Live Bio-Forecasting Project, 2-2-2 Hikaridai Seika-cho, Soraku-gun, Khoto-fu 619-0288, Japan and The Thomas N. Sato BioMEC-X Laboratories, Advanced Telecommunications Research Institute International, 2-2-2 Hikaridai Seika-cho, Soraku-gun, Khoto-fu 619-0288, Japan.|Department of Statistical Science, The Graduate University for Advanced Studies (Sokendai), 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, Department of Statistical Modeling, The Institute of Statistical Mathematics, Research Organization of Information and Systems, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, JST-CREST, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, JST-ERATO Sato Live Bio-Forecasting Project, 2-2-2 Hikaridai Seika-cho, Soraku-gun, Khoto-fu 619-0288, Japan and The Thomas N. Sato BioMEC-X Laboratories, Advanced Telecommunications Research Institute International, 2-2-2 Hikaridai Seika-cho, Soraku-gun, Khoto-fu 619-0288, Japan Department of Statistical Science, The Graduate University for Advanced Studies (Sokendai), 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, Department of Statistical Modeling, The Institute of Statistical Mathematics, Research Organization of Information and Systems, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, JST-CREST, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, JST-ERATO Sato Live Bio-Forecasting Project, 2-2-2 Hikaridai Seika-cho, Soraku-gun, Khoto-fu 619-0288, Japan and The Thomas N. Sato BioMEC-X Laboratories, Advanced Telecommunications Research Institute International, 2-2-2 Hikaridai Seika-cho, Soraku-gun, Khoto-fu 619-0288, Japan Department of Statistical Science, The Graduate University for Advanced Studies (Sokendai), 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, Department of Statistical Modeling, The Institute of Statistical Mathematics, Research Organization of Information and Systems, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, JST-CREST, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, JST-ERATO Sato Live Bio-Forecasting Project, 2-2-2 Hikaridai Seika-cho, Soraku-gun, Khoto-fu 619-0288, Japan and The Thomas N. Sato BioMEC-X Laboratories, Advanced Telecommunications Research Institute International, 2-2-2 Hikaridai Seika-cho, Soraku-gun, Khoto-fu 619-0288, Japan Depar', 'Japan|Japan', 0, 'Algorithms|Chromatin Immunoprecipitation|Humans|Markov Chains|Monte Carlo Method|Nucleotide Motifs|Promoter Regions, Genetic|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btv017', '25583120', 'The motif discovery problem consists of finding recurring patterns of short strings in a set of nucleotide sequences. This classical problem is receiving renewed attention as most early motif discovery methods lack the ability to handle large data of recent genome-wide ChIP studies. New ChIP-tailored methods focus on reducing computation time and pay little regard to the accuracy of motif detection. Unlike such methods, our method focuses on increasing the detection accuracy while maintaining the computation efficiency at an acceptable level. The major advantage of our method is that it can mine diverse multiple motifs undetectable by current methods.'),
(78979, 2015, 'bio', 'CellCODE: a robust latent variable approach to differential expression analysis for heterogeneous cell populations', 'Chikina, Maria|Zaslavsky, Elena|Sealfon, Stuart C', 'Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15217, USA and Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.|Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15217, USA and Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.|Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15217, USA and Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.', 'United States|United States|United States', 36, 'B-Lymphocytes|Cell Lineage|Computational Biology|Data Interpretation, Statistical|Gene Expression Regulation|High-Throughput Nucleotide Sequencing|Humans|Influenza Vaccines|Models, Statistical|Neutrophils|Sequence Analysis, RNA|Software|T-Lymphocytes|Time Factors', 'Journal Article', '10.1093/bioinformatics/btv015', '25583121', 'Identifying alterations in gene expression associated with different clinical states is important for the study of human biology. However, clinical samples used in gene expression studies are often derived from heterogeneous mixtures with variable cell-type composition, complicating statistical analysis. Considerable effort has been devoted to modeling sample heterogeneity, and presently, there are many methods that can estimate cell proportions or pure cell-type expression from mixture data. However, there is no method that comprehensively addresses mixture analysis in the context of differential expression without relying on additional proportion information, which can be inaccurate and is frequently unavailable.'),
(78980, 2015, 'bio', 'More challenges for machine-learning protein interactions', 'Hamp, Tobias|Rost, Burkhard', 'Department of Informatics, Bioinformatics and Computational Biology I12, Technische Universität München, 85748 Garching/Munich, Germany.|Department of Informatics, Bioinformatics and Computational Biology I12, Technische Universität München, 85748 Garching/Munich, Germany.', 'Germany|Germany', 24, 'Artificial Intelligence|Computational Biology|Humans|Protein Interaction Mapping|Proteins|Saccharomyces cerevisiae Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btu857', '25586513', 'Machine learning may be the most popular computational tool in molecular biology. Providing sustained performance estimates is challenging. The standard cross-validation protocols usually fail in biology. Park and Marcotte found that even refined protocols fail for protein-protein interactions (PPIs).'),
(78981, 2015, 'bio', 'NLR-parser: rapid annotation of plant NLR complements', 'Steuernagel, Burkhard|Jupe, Florian|Witek, Kamil|Jones, Jonathan D G|Wulff, Brande B H', 'Department of Crop Genetics, John Innes Centre, Norwich, UK and The Sainsbury Laboratory, Norwich, UK.|Department of Crop Genetics, John Innes Centre, Norwich, UK and The Sainsbury Laboratory, Norwich, UK.|Department of Crop Genetics, John Innes Centre, Norwich, UK and The Sainsbury Laboratory, Norwich, UK.|Department of Crop Genetics, John Innes Centre, Norwich, UK and The Sainsbury Laboratory, Norwich, UK.|Department of Crop Genetics, John Innes Centre, Norwich, UK and The Sainsbury Laboratory, Norwich, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Arabidopsis|Arabidopsis Proteins|Gene Expression Regulation, Plant|Genome, Plant|Immunity, Innate|Molecular Sequence Annotation|Plant Diseases|Proteins|Repetitive Sequences, Amino Acid|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btv005', '25586514', 'The repetitive nature of plant disease resistance genes encoding for nucleotide-binding leucine-rich repeat (NLR) proteins hampers their prediction with standard gene annotation software. Motif alignment and search tool (MAST) has previously been reported as a tool to support annotation of NLR-encoding genes. However, the decision if a motif combination represents an NLR protein was entirely manual.'),
(78982, 2015, 'bio', 'QTLMiner: QTL database curation by mining tables in literature', 'Peng, Jing|Shi, Xinyi|Sun, Yiming|Li, Dongye|Liu, Baohui|Kong, Fanjiang|Yuan, Xiaohui', 'College of Electronic and Information, Northeast Agricultural University, Harbin, China, School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China and The Key Lab of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, China College of Electronic and Information, Northeast Agricultural University, Harbin, China, School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China and The Key Lab of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, China.|College of Electronic and Information, Northeast Agricultural University, Harbin, China, School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China and The Key Lab of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, China.|College of Electronic and Information, Northeast Agricultural University, Harbin, China, School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China and The Key Lab of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, China.|College of Electronic and Information, Northeast Agricultural University, Harbin, China, School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China and The Key Lab of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, China.|College of Electronic and Information, Northeast Agricultural University, Harbin, China, School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China and The Key Lab of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, China.|College of Electronic and Information, Northeast Agricultural University, Harbin, China, School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China and The Key Lab of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, China.|College of Electronic and Information, Northeast Agricultural University, Harbin, China, School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China and The Key Lab of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, China.', 'China|China|China|China|China|China|China', 5, 'Data Mining|Databases, Nucleic Acid|Publications|Quantitative Trait Loci|Software|Soybeans', 'Journal Article', '10.1093/bioinformatics/btv016', '25586515', 'Figures and tables in biomedical literature record vast amounts of important experiment results. In scientific papers, for example, quantitative trait locus (QTL) information is usually presented in tables. However, most of the popular text-mining methods focus on extracting knowledge from unstructured free text. As far as we know, there are no published works on mining tables in biomedical literature. In this article, we propose a method to extract QTL information from tables and plain text found in literature. Heterogeneous and complex tables were converted into a structured database, combined with information extracted from plain text. Our method could greatly reduce labor burdens involved with database curation.'),
(78983, 2014, 'bio', 'Proceedings of the 13th European Conference on Computational Biology (ECCB’14), September 7-10, 2014, Strasbourg, France', '-', '-', '-', 0, 'Animals|Computational Biology|Humans|Molecular Biology', 'Congress', '10.1093/bioinformatics/btu511', '25590052', '-'),
(78984, 2015, 'bio', 'scrm: efficiently simulating long sequences using the approximated coalescent with recombination', 'Staab, Paul R|Zhu, Sha|Metzler, Dirk|Lunter, Gerton', 'Department of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany and Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.|Department of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany and Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.|Department of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany and Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.|Department of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany and Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.', 'Germany|Germany|Germany|Germany', 43, 'Algorithms|Computer Simulation|Genetic Linkage|Genomics|High-Throughput Nucleotide Sequencing|Models, Genetic|Recombination, Genetic|Software', 'Journal Article', '10.1093/bioinformatics/btu861', '25596205', 'Coalescent-based simulation software for genomic sequences allows the efficient in silico generation of short- and medium-sized genetic sequences. However, the simulation of genome-size datasets as produced by next-generation sequencing is currently only possible using fairly crude approximations.'),
(78985, 2015, 'bio', 'Functional Gene Networks: R/Bioc package to generate and analyse gene networks derived from functional enrichment and clustering', 'Aibar, Sara|Fontanillo, Celia|Droste, Conrad|De Las Rivas, Javier', 'Bioinformatics and Functional Genomics Research Group, Cancer Research Center (Consejo Superior de Investigaciones Científicas, Universidad de Salamanca and Instituto de Investigación Biomédica de Salamanca, CSIC/USAL/IBSAL), Salamanca, Spain.|Bioinformatics and Functional Genomics Research Group, Cancer Research Center (Consejo Superior de Investigaciones Científicas, Universidad de Salamanca and Instituto de Investigación Biomédica de Salamanca, CSIC/USAL/IBSAL), Salamanca, Spain.|Bioinformatics and Functional Genomics Research Group, Cancer Research Center (Consejo Superior de Investigaciones Científicas, Universidad de Salamanca and Instituto de Investigación Biomédica de Salamanca, CSIC/USAL/IBSAL), Salamanca, Spain.|Bioinformatics and Functional Genomics Research Group, Cancer Research Center (Consejo Superior de Investigaciones Científicas, Universidad de Salamanca and Instituto de Investigación Biomédica de Salamanca, CSIC/USAL/IBSAL), Salamanca, Spain.', 'Spain|Spain|Spain|Spain', 27, 'Alzheimer Disease|Cluster Analysis|Entorhinal Cortex|Gene Expression Profiling|Gene Regulatory Networks|Humans|Neurons|Software', 'Journal Article', '10.1093/bioinformatics/btu864', '25600944', 'Functional Gene Networks (FGNet) is an R/Bioconductor package that generates gene networks derived from the results of functional enrichment analysis (FEA) and annotation clustering. The sets of genes enriched with specific biological terms (obtained from a FEA platform) are transformed into a network by establishing links between genes based on common functional annotations and common clusters. The network provides a new view of FEA results revealing gene modules with similar functions and genes that are related to multiple functions. In addition to building the functional network, FGNet analyses the similarity between the groups of genes and provides a distance heatmap and a bipartite network of functionally overlapping genes. The application includes an interface to directly perform FEA queries using different external tools: DAVID, GeneTerm Linker, TopGO or GAGE, and a graphical interface to facilitate the use.'),
(78986, 2015, 'bio', 'WALTZ-DB: a benchmark database of amyloidogenic hexapeptides', 'Beerten, Jacinte|Van Durme, Joost|Gallardo, Rodrigo|Capriotti, Emidio|Serpell, Louise|Rousseau, Frederic|Schymkowitz, Joost', 'VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK.|VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK.|VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK.|VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK.|VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK.|VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK.|VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK VIB Switch Laboratory, Leuven, Belgium, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49 Box 802, Leuven, Belgium, Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35249, USA and School of Life Sciences, University of Sussex, Falmer, East Sussex BN1 9QG, UK.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 34, 'Algorithms|Amino Acid Sequence|Amyloid|Databases, Protein|Oligopeptides', 'Journal Article', '10.1093/bioinformatics/btv027', '25600945', 'Accurate prediction of amyloid-forming amino acid sequences remains an important challenge. We here present an online database that provides open access to the largest set of experimentally characterized amyloid forming hexapeptides. To this end, we expanded our previous set of 280 hexapeptides used to develop the Waltz algorithm with 89 peptides from literature review and by systematic experimental characterisation of the aggregation of 720 hexapeptides by transmission electron microscopy, dye binding and Fourier transform infrared spectroscopy. This brings the total number of experimentally characterized hexapeptides in the WALTZ-DB database to 1089, of which 244 are annotated as positive for amyloid formation.'),
(78987, 2015, 'bio', 'drexplorer: A tool to explore dose-response relationships and drug-drug interactions', 'Tong, Pan|Coombes, Kevin R|Johnson, Faye M|Byers, Lauren A|Diao, Lixia|Liu, Diane D|Lee, J Jack|Heymach, John V|Wang, Jing', 'Departments of Bioinformatics and Computational Biology, Houston, TX 77030, Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, Thoracic and Head and Neck Medical Oncology and Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Departments of Bioinformatics and Computational Biology, Houston, TX 77030, Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, Thoracic and Head and Neck Medical Oncology and Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Departments of Bioinformatics and Computational Biology, Houston, TX 77030, Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, Thoracic and Head and Neck Medical Oncology and Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Departments of Bioinformatics and Computational Biology, Houston, TX 77030, Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, Thoracic and Head and Neck Medical Oncology and Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Departments of Bioinformatics and Computational Biology, Houston, TX 77030, Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, Thoracic and Head and Neck Medical Oncology and Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Departments of Bioinformatics and Computational Biology, Houston, TX 77030, Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, Thoracic and Head and Neck Medical Oncology and Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Departments of Bioinformatics and Computational Biology, Houston, TX 77030, Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, Thoracic and Head and Neck Medical Oncology and Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Departments of Bioinformatics and Computational Biology, Houston, TX 77030, Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, Thoracic and Head and Neck Medical Oncology and Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Departments of Bioinformatics and Computational Biology, Houston, TX 77030, Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, Thoracic and Head and Neck Medical Oncology and Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 16, 'Algorithms|Antineoplastic Agents|Dose-Response Relationship, Drug|Drug Interactions|Drug Screening Assays, Antitumor|Inhibitory Concentration 50|Nonlinear Dynamics|Reproducibility of Results|Software', 'Journal Article', '10.1093/bioinformatics/btv028', '25600946', 'Nonlinear dose-response models are primary tools for estimating the potency [e.g. half-maximum inhibitory concentration (IC) known as IC50] of anti-cancer drugs. We present drexplorer software, which enables biologists to evaluate replicate reproducibility, detect outlier data points, fit different models, select the best model, estimate IC values at different percentiles and assess drug-drug interactions. drexplorer serves as a computation engine within the R environment and a graphical interface for users who do not have programming backgrounds.'),
(78988, 2015, 'bio', 'Deep profiling of multitube flow cytometry data', 'ONeill, Kieran|Aghaeepour, Nima|Parker, Jeremy|Hogge, Donna|Karsan, Aly|Dalal, Bakul|Brinkman, Ryan R', 'Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada.|Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada.|Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada.|Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada.|Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada.|Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada.|Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 5, 'Biomarkers, Tumor|Case-Control Studies|Cell Lineage|Cell Separation|Flow Cytometry|Humans|Immunophenotyping|Leukemia, Myeloid, Acute|Leukocytes, Mononuclear|Mutation|Nuclear Proteins|Software', 'Comparative Study', '10.1093/bioinformatics/btv008', '25600947', 'Deep profiling the phenotypic landscape of tissues using high-throughput flow cytometry (FCM) can provide important new insights into the interplay of cells in both healthy and diseased tissue. But often, especially in clinical settings, the cytometer cannot measure all the desired markers in a single aliquot. In these cases, tissue is separated into independently analysed samples, leaving a need to electronically recombine these to increase dimensionality. Nearest-neighbour (NN) based imputation fulfils this need but can produce artificial subpopulations. Clustering-based NNs can reduce these, but requires prior domain knowledge to be able to parameterize the clustering, so is unsuited to discovery settings.'),
(78989, 2015, 'bio', 'Ultrafast SNP analysis using the Burrows-Wheeler transform of short-read data', 'Kimura, Kouichi|Koike, Asako', 'Biosystems Research Department, Central Research Laboratory, Hitachi, Ltd., 1-280 Higashi-Koigakubo, Kokubunji, Tokyo 185-8601, Japan.|Biosystems Research Department, Central Research Laboratory, Hitachi, Ltd., 1-280 Higashi-Koigakubo, Kokubunji, Tokyo 185-8601, Japan.', 'Japan|Japan', 15, 'Algorithms|Computational Biology|Exome|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btv024', '25609790', 'Sequence-variation analysis is conventionally performed on mapping results that are highly redundant and occasionally contain undesirable heuristic biases. A straightforward approach to single-nucleotide polymorphism (SNP) analysis, using the Burrows-Wheeler transform (BWT) of short-read data, is proposed.'),
(78990, 2015, 'bio', 'Bias in microRNA functional enrichment analysis', 'Bleazard, Thomas|Lamb, Janine A|Griffiths-Jones, Sam', 'Faculty of Medical and Human Sciences, and Faculty of Life Sciences, University of Manchester, UK.|Faculty of Medical and Human Sciences, and Faculty of Life Sciences, University of Manchester, UK.|Faculty of Medical and Human Sciences, and Faculty of Life Sciences, University of Manchester, UK.', 'United Kingdom|United Kingdom|United Kingdom', 61, 'Algorithms|Computational Biology|Gene Expression Regulation|Humans|MicroRNAs|Molecular Sequence Annotation|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btv023', '25609791', 'Many studies have investigated the differential expression of microRNAs (miRNAs) in disease states and between different treatments, tissues and developmental stages. Given a list of perturbed miRNAs, it is common to predict the shared pathways on which they act. The standard test for functional enrichment typically yields dozens of significantly enriched functional categories, many of which appear frequently in the analysis of apparently unrelated diseases and conditions.'),
(78991, 2015, 'bio', 'GrammR: graphical representation and modeling of count data with application in metagenomics', 'Ayyala, Deepak Nag|Lin, Shili', 'Department of Statistics, The Ohio State University, Columbus, OH 43210, USA.|Department of Statistics, The Ohio State University, Columbus, OH 43210, USA.', 'United States|United States', 6, 'Algorithms|Bacteria|Cluster Analysis|Computational Biology|Computer Graphics|Gastrointestinal Tract|Humans|Information Storage and Retrieval|Metagenomics|Models, Statistical|Multivariate Analysis|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btv032', '25609792', 'Microbiota compositions have great implications in human health, such as obesity and other conditions. As such, it is of great importance to cluster samples or taxa to visualize and discover community substructures. Graphical representation of metagenomic count data relies on two aspects, measure of dissimilarity between samples/taxa and algorithm used to estimate coordinates to study microbiota communities. UniFrac is a dissimilarity measure commonly used in metagenomic research, but it requires a phylogenetic tree. Principal coordinate analysis (PCoA) is a popular algorithm for estimating two-dimensional (2D) coordinates for graphical representation, although alternative and higher-dimensional representations may reveal underlying community substructures invisible in 2D representations.'),
(78992, 2015, 'bio', 'MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph', 'Li, Dinghua|Liu, Chi-Man|Luo, Ruibang|Sadakane, Kunihiko|Lam, Tak-Wah', 'HKU-BGI Bioinformatics Algorithms Research Laboratory & Department of Computer Science, University of Hong Kong, Hong Kong, L3 Bioinformatics Limited, Hong Kong and National Institute of Informatics, Chiyoda-ku, Tokyo, Japan.|HKU-BGI Bioinformatics Algorithms Research Laboratory & Department of Computer Science, University of Hong Kong, Hong Kong, L3 Bioinformatics Limited, Hong Kong and National Institute of Informatics, Chiyoda-ku, Tokyo, Japan.|HKU-BGI Bioinformatics Algorithms Research Laboratory & Department of Computer Science, University of Hong Kong, Hong Kong, L3 Bioinformatics Limited, Hong Kong and National Institute of Informatics, Chiyoda-ku, Tokyo, Japan.|HKU-BGI Bioinformatics Algorithms Research Laboratory & Department of Computer Science, University of Hong Kong, Hong Kong, L3 Bioinformatics Limited, Hong Kong and National Institute of Informatics, Chiyoda-ku, Tokyo, Japan.|HKU-BGI Bioinformatics Algorithms Research Laboratory & Department of Computer Science, University of Hong Kong, Hong Kong, L3 Bioinformatics Limited, Hong Kong and National Institute of Informatics, Chiyoda-ku, Tokyo, Japan HKU-BGI Bioinformatics Algorithms Research Laboratory & Department of Computer Science, University of Hong Kong, Hong Kong, L3 Bioinformatics Limited, Hong Kong and National Institute of Informatics, Chiyoda-ku, Tokyo, Japan.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong', 0, 'Algorithms|High-Throughput Nucleotide Sequencing|Metagenomics|Software|Soil', 'Journal Article', '10.1093/bioinformatics/btv033', '25609793', 'MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252xe2x80x89Gbps in 44.1 and 99.6xe2x80x89h on a single computing node with and without a graphics processing unit, respectively. MEGAHIT assembles the data as a whole, i.e. no pre-processing like partitioning and normalization was needed. When compared with previous methods on assembling the soil data, MEGAHIT generated a three-time larger assembly, with longer contig N50 and average contig length, furthermore, 55.8% of the reads were aligned to the assembly, giving a fourfold improvement.'),
(78993, 2015, 'bio', 'MethylMix: an R package for identifying DNA methylation-driven genes', 'Gevaert, Olivier', 'Department of Medicine, Stanford Center for Biomedical Informatics, Stanford, CA 94305-5479, USA.', 'United States', 0, 'Algorithms|DNA Methylation|Disease|Gene Expression Regulation|Humans|Software|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btv020', '25609794', 'DNA methylation is an important mechanism regulating gene transcription, and its role in carcinogenesis has been extensively studied. Hyper and hypomethylation of genes is an alternative mechanism to deregulate gene expression in a wide range of diseases. At the same time, high-throughput DNA methylation assays have been developed generating vast amounts of genome wide DNA methylation measurements. Yet, few tools exist that can formally identify hypo and hypermethylated genes that are predictive of transcription and thus functionally relevant for a particular disease. To accommodate this lack of tools, we developed MethylMix, an algorithm implemented in R to identify disease specific hyper and hypomethylated genes. MethylMix is based on a beta mixture model to identify methylation states and compares them with the normal DNA methylation state. MethylMix introduces a novel metric, the Differential Methylation value or DM-value defined as the difference of a methylation state with the normal methylation state. Finally, matched gene expression data are used to identify, besides differential, transcriptionally predictive methylation states by focusing on methylation changes that effect gene expression.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78994, 2015, 'bio', 'Large-scale extraction of brain connectivity from the neuroscientific literature', 'Richardet, Renaud|Chappelier, Jean-Cxc3xa9dric|Telefont, Martin|Hill, Sean', 'Blue Brain Project, Brain Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fxc3xa9dxc3xa9rale de Lausanne (EPFL), Lausanne, Switzerland.|Blue Brain Project, Brain Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fxc3xa9dxc3xa9rale de Lausanne (EPFL), Lausanne, Switzerland.|Blue Brain Project, Brain Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fxc3xa9dxc3xa9rale de Lausanne (EPFL), Lausanne, Switzerland.|Blue Brain Project, Brain Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fxc3xa9dxc3xa9rale de Lausanne (EPFL), Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Animals|Artificial Intelligence|Atlases as Topic|Brain|Brain Mapping|Data Mining|Databases, Factual|Mice|Neuroanatomy|Periodicals as Topic|Software|Terminology as Topic', 'Journal Article', '10.1093/bioinformatics/btv025', '25609795', 'In neuroscience, as in many other scientific domains, the primary form of knowledge dissemination is through published articles. One challenge for modern neuroinformatics is finding methods to make the knowledge from the tremendous backlog of publications accessible for search, analysis and the integration of such data into computational models. A key example of this is metascale brain connectivity, where results are not reported in a normalized repository. Instead, these experimental results are published in natural language, scattered among individual scientific publications. This lack of normalization and centralization hinders the large-scale integration of brain connectivity results. In this article, we present text-mining models to extract and aggregate brain connectivity results from 13.2 million PubMed abstracts and 630xe2x80x89216 full-text publications related to neuroscience. The brain regions are identified with three different named entity recognizers (NERs) and then normalized against two atlases: the Allen Brain Atlas (ABA) and the atlas from the Brain Architecture Management System (BAMS). We then use three different extractors to assess inter-region connectivity.'),
(78995, 2015, 'bio', 'dslice: an R package for nonparametric testing of associations with application in QTL and gene set analysis', 'Ye, Chao|Jiang, Bo|Zhang, Xuegong|Liu, Jun S', 'MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China, Department of Statistics, Harvard University, Cambridge, MA 02138, USA, School of Life Sciences, Tsinghua University, Beijing 100084, China and Center of Statistics, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China, Department of Statistics, Harvard University, Cambridge, MA 02138, USA, School of Life Sciences, Tsinghua University, Beijing 100084, China and Center of Statistics, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China, Department of Statistics, Harvard University, Cambridge, MA 02138, USA, School of Life Sciences, Tsinghua University, Beijing 100084, China and Center of Statistics, Tsinghua University, Beijing 100084, China MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China, Department of Statistics, Harvard University, Cambridge, MA 02138, USA, School of Life Sciences, Tsinghua University, Beijing 100084, China and Center of Statistics, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China, Department of Statistics, Harvard University, Cambridge, MA 02138, USA, School of Life Sciences, Tsinghua University, Beijing 100084, China and Center of Statistics, Tsinghua University, Beijing 100084, China MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China, Department of Statistics, Harvard University, Cambridge, MA 02138, USA, School of Life Sciences, Tsinghua University, Beijing 100084, China and Center of Statistics, Tsinghua University, Beijing 100084, China.', 'China|China|China|China', 0, 'Animals|Computational Biology|Gene Expression|Genetic Variation|Humans|Mice|Phenotype|Quantitative Trait Loci|Software|Statistics, Nonparametric', 'Journal Article', '10.1093/bioinformatics/btv021', '25609796', 'Many statistical problems in bioinformatics and genetics can be formulated as the testing of associations between a categorical variable and a continuous variable. A dynamic slicing method was proposed for non-parametric dependence testing, which has been demonstrated to have higher powers compared with traditional methods such as Kolmogorov-Smirnov test. We introduce an R package dslice to facilitate the use of dynamic slicing method in bioinformatic applications such as quantitative trait loci study and gene set enrichment analysis.'),
(78996, 2015, 'bio', 'Topology-function conservation in protein-protein interaction networks', 'Davis, Darren|Yaveroxc4x9flu, xc3x96mer Nebil|Malod-Dognin, Noxc3xabl|Stojmirovic, Aleksandar|Prxc5xbeulj, Nataxc5xa1a', 'California Institute of Telecommunications and Technology (Calit2), University of California Irvine, Irvine, CA, USA, Department of Computing, Imperial College London, London, UK, National Center for Biotechnology Information (NCBI), Bethesda, MD, USA and Janssen Research and Development, LLC, Spring House, PA, USA.|California Institute of Telecommunications and Technology (Calit2), University of California Irvine, Irvine, CA, USA, Department of Computing, Imperial College London, London, UK, National Center for Biotechnology Information (NCBI), Bethesda, MD, USA and Janssen Research and Development, LLC, Spring House, PA, USA California Institute of Telecommunications and Technology (Calit2), University of California Irvine, Irvine, CA, USA, Department of Computing, Imperial College London, London, UK, National Center for Biotechnology Information (NCBI), Bethesda, MD, USA and Janssen Research and Development, LLC, Spring House, PA, USA.|California Institute of Telecommunications and Technology (Calit2), University of California Irvine, Irvine, CA, USA, Department of Computing, Imperial College London, London, UK, National Center for Biotechnology Information (NCBI), Bethesda, MD, USA and Janssen Research and Development, LLC, Spring House, PA, USA.|California Institute of Telecommunications and Technology (Calit2), University of California Irvine, Irvine, CA, USA, Department of Computing, Imperial College London, London, UK, National Center for Biotechnology Information (NCBI), Bethesda, MD, USA and Janssen Research and Development, LLC, Spring House, PA, USA California Institute of Telecommunications and Technology (Calit2), University of California Irvine, Irvine, CA, USA, Department of Computing, Imperial College London, London, UK, National Center for Biotechnology Information (NCBI), Bethesda, MD, USA and Janssen Research and Development, LLC, Spring House, PA, USA.|California Institute of Telecommunications and Technology (Calit2), University of California Irvine, Irvine, CA, USA, Department of Computing, Imperial College London, London, UK, National Center for Biotechnology Information (NCBI), Bethesda, MD, USA and Janssen Research and Development, LLC, Spring House, PA, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Computational Biology|Conserved Sequence|Gene Ontology|Gene Regulatory Networks|Humans|Molecular Sequence Annotation|Protein Interaction Mapping|Proteins|Saccharomyces cerevisiae', 'Comparative Study', '10.1093/bioinformatics/btv026', '25609797', 'Proteins underlay the functioning of a cell and the wiring of proteins in protein-protein interaction network (PIN) relates to their biological functions. Proteins with similar wiring in the PIN (topology around them) have been shown to have similar functions. This property has been successfully exploited for predicting protein functions. Topological similarity is also used to guide network alignment algorithms that find similarly wired proteins between PINs of different species, these similarities are used to transfer annotation across PINs, e.g. from model organisms to human. To refine these functional predictions and annotation transfers, we need to gain insight into the variability of the topology-function relationships. For example, a function may be significantly associated with specific topologies, while another function may be weakly associated with several different topologies. Also, the topology-function relationships may differ between different species.'),
(78997, 2015, 'bio', 'KMC 2: fast and resource-frugal k-mer counting', 'Deorowicz, Sebastian|Kokot, Marek|Grabowski, Szymon|Debudaj-Grabysz, Agnieszka', 'Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 xc5x81xc3xb3dxc5xba, Poland.|Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 xc5x81xc3xb3dxc5xba, Poland.|Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 xc5x81xc3xb3dxc5xba, Poland.|Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 xc5x81xc3xb3dxc5xba, Poland.', 'Poland|Poland|Poland|Poland', 0, 'Algorithms|Animals|Computational Biology|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btv022', '25609798', 'Building the histogram of occurrences of every k-symbol long substring of nucleotide data is a standard step in many bioinformatics applications, known under the name of k-mer counting. Its applications include developing de Bruijn graph genome assemblers, fast multiple sequence alignment and repeat detection. The tremendous amounts of NGS data require fast algorithms for k-mer counting, preferably using moderate amounts of memory.'),
(78998, 2015, 'bio', 'Gaussian process test for high-throughput sequencing time series: application to experimental evolution', 'Topa, Hande|Jónás, Ágnes|Kofler, Robert|Kosiol, Carolin|Honkela, Antti', 'Helsinki Institute for Information Technology (HIIT), Department of Information and Computer Science, Aalto University, Espoo, Finland, Institut für Populationsgenetik, Vetmeduni Vienna, 1210 Wien, Austria, Vienna Graduate School of Population Genetics, Wien, Austria and Helsinki Institute for Information Technology (HIIT), Department of Computer Science, University of Helsinki, Helsinki, Finland.|Helsinki Institute for Information Technology (HIIT), Department of Information and Computer Science, Aalto University, Espoo, Finland, Institut für Populationsgenetik, Vetmeduni Vienna, 1210 Wien, Austria, Vienna Graduate School of Population Genetics, Wien, Austria and Helsinki Institute for Information Technology (HIIT), Department of Computer Science, University of Helsinki, Helsinki, Finland Helsinki Institute for Information Technology (HIIT), Department of Information and Computer Science, Aalto University, Espoo, Finland, Institut für Populationsgenetik, Vetmeduni Vienna, 1210 Wien, Austria, Vienna Graduate School of Population Genetics, Wien, Austria and Helsinki Institute for Information Technology (HIIT), Department of Computer Science, University of Helsinki, Helsinki, Finland.|Helsinki Institute for Information Technology (HIIT), Department of Information and Computer Science, Aalto University, Espoo, Finland, Institut für Populationsgenetik, Vetmeduni Vienna, 1210 Wien, Austria, Vienna Graduate School of Population Genetics, Wien, Austria and Helsinki Institute for Information Technology (HIIT), Department of Computer Science, University of Helsinki, Helsinki, Finland.|Helsinki Institute for Information Technology (HIIT), Department of Information and Computer Science, Aalto University, Espoo, Finland, Institut für Populationsgenetik, Vetmeduni Vienna, 1210 Wien, Austria, Vienna Graduate School of Population Genetics, Wien, Austria and Helsinki Institute for Information Technology (HIIT), Department of Computer Science, University of Helsinki, Helsinki, Finland.|Helsinki Institute for Information Technology (HIIT), Department of Information and Computer Science, Aalto University, Espoo, Finland, Institut für Populationsgenetik, Vetmeduni Vienna, 1210 Wien, Austria, Vienna Graduate School of Population Genetics, Wien, Austria and Helsinki Institute for Information Technology (HIIT), Department of Computer Science, University of Helsinki, Helsinki, Finland.', 'Austria|Austria|Austria|Austria|Austria', 22, 'Alleles|Animals|Drosophila|Evolution, Molecular|Gene Frequency|Genomics|High-Throughput Nucleotide Sequencing|Models, Statistical|Normal Distribution|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btv014', '25614471', 'Recent advances in high-throughput sequencing (HTS) have made it possible to monitor genomes in great detail. New experiments not only use HTS to measure genomic features at one time point but also monitor them changing over time with the aim of identifying significant changes in their abundance. In population genetics, for example, allele frequencies are monitored over time to detect significant frequency changes that indicate selection pressures. Previous attempts at analyzing data from HTS experiments have been limited as they could not simultaneously include data at intermediate time points, replicate experiments and sources of uncertainty specific to HTS such as sequencing depth.'),
(78999, 2015, 'bio', 'CypRules: a rule-based P450 inhibition prediction server', 'Shao, Chi-Yu|Su, Bo-Han|Tu, Yi-Shu|Lin, Chieh|Lin, Olivia A|Tseng, Yufeng J', 'Graduate Institute of Biomedical Electronics and Bioinformatics and Department of Computer Science and Information Engineering, National Taiwan University, No.1 Sec.4, Roosevelt Road, Taipei, Taiwan 106.|Graduate Institute of Biomedical Electronics and Bioinformatics and Department of Computer Science and Information Engineering, National Taiwan University, No.1 Sec.4, Roosevelt Road, Taipei, Taiwan 106.|Graduate Institute of Biomedical Electronics and Bioinformatics and Department of Computer Science and Information Engineering, National Taiwan University, No.1 Sec.4, Roosevelt Road, Taipei, Taiwan 106.|Graduate Institute of Biomedical Electronics and Bioinformatics and Department of Computer Science and Information Engineering, National Taiwan University, No.1 Sec.4, Roosevelt Road, Taipei, Taiwan 106.|Graduate Institute of Biomedical Electronics and Bioinformatics and Department of Computer Science and Information Engineering, National Taiwan University, No.1 Sec.4, Roosevelt Road, Taipei, Taiwan 106.|Graduate Institute of Biomedical Electronics and Bioinformatics and Department of Computer Science and Information Engineering, National Taiwan University, No.1 Sec.4, Roosevelt Road, Taipei, Taiwan 106 Graduate Institute of Biomedical Electronics and Bioinformatics and Department of Computer Science and Information Engineering, National Taiwan University, No.1 Sec.4, Roosevelt Road, Taipei, Taiwan 106.', '-|-|-|-|-|-', 17, 'Algorithms|Cytochrome P-450 Enzyme Inhibitors|Cytochrome P-450 Enzyme System|High-Throughput Screening Assays|Humans|Liver|Software', 'Journal Article', '10.1093/bioinformatics/btv043', '25617412', 'Cytochrome P450 (CYPs) are the major enzymes involved in drug metabolism and bioactivation. Inhibition models were constructed for five of the most popular enzymes from the CYP superfamily in human liver. The five enzymes chosen for this study, namely CYP1A2, CYP2D6, CYP2C19, CYP2C9 and CYP3A4, account for 90% of the xenobiotic and drug metabolism in human body. CYP enzymes can be inhibited or induced by various drugs or chemical compounds. In this work, a rule-based CYP inhibition prediction online server, CypRules, was created based on predictive models generated by the rule-based C5.0 algorithm. CypRules can predict and provide structural rulesets for CYP inhibition for each compound uploaded to the server. Capable of fast execution performance, it can be used for virtual high-throughput screening (VHTS) of a large set of testing compounds.'),
(79000, 2015, 'bio', '3USS: a web server for detecting alternative 3UTRs from RNA-seq experiments', 'Le Pera, Loredana|Mazzapioda, Mariagiovanna|Tramontano, Anna', 'Center for Life Nano Science@Sapienza, Istituto Italiano di Tecnologia, Rome, Italy, Department of Physics, Sapienza University, Rome, Italy and Istituto Pasteur - Fondazione Cenci Bolognetti, Sapienza University, Rome, Italy Center for Life Nano Science@Sapienza, Istituto Italiano di Tecnologia, Rome, Italy, Department of Physics, Sapienza University, Rome, Italy and Istituto Pasteur - Fondazione Cenci Bolognetti, Sapienza University, Rome, Italy.|Center for Life Nano Science@Sapienza, Istituto Italiano di Tecnologia, Rome, Italy, Department of Physics, Sapienza University, Rome, Italy and Istituto Pasteur - Fondazione Cenci Bolognetti, Sapienza University, Rome, Italy.|Center for Life Nano Science@Sapienza, Istituto Italiano di Tecnologia, Rome, Italy, Department of Physics, Sapienza University, Rome, Italy and Istituto Pasteur - Fondazione Cenci Bolognetti, Sapienza University, Rome, Italy Center for Life Nano Science@Sapienza, Istituto Italiano di Tecnologia, Rome, Italy, Department of Physics, Sapienza University, Rome, Italy and Istituto Pasteur - Fondazione Cenci Bolognetti, Sapienza University, Rome, Italy Center for Life Nano Science@Sapienza, Istituto Italiano di Tecnologia, Rome, Italy, Department of Physics, Sapienza University, Rome, Italy and Istituto Pasteur - Fondazione Cenci Bolognetti, Sapienza University, Rome, Italy.', 'Italy|Italy|Italy', 0, '3 Untranslated Regions|Gene Expression Profiling|Internet|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btv035', '25617413', 'Protein-coding genes with multiple alternative polyadenylation sites can generate mRNA 3UTR sequences of different lengths, thereby causing the loss or gain of regulatory elements, which can affect stability, localization and translation efficiency. 3USS is a web-server developed with the aim of giving experimentalists the possibility to automatically identify alternative 3 : UTRs (shorter or longer with respect to a reference transcriptome), an option that is not available in standard RNA-seq data analysis procedures. The tool reports as putative novel the 3 : UTRs not annotated in available databases. Furthermore, if data from two related samples are uploaded, common and specific alternative 3 : UTRs are identified and reported by the server.'),
(79001, 2015, 'bio', 'Plant photosynthesis phenomics data quality control', 'Xu, Lei|Cruz, Jeffrey A|Savage, Linda J|Kramer, David M|Chen, Jin', 'Department of Computer Science and Engineering, Department of Energy Plant Research Laboratory and Department of Biochemistry and Molecular Biology, Michigan State University, MI, East Lansing 48824, USA.|Department of Computer Science and Engineering, Department of Energy Plant Research Laboratory and Department of Biochemistry and Molecular Biology, Michigan State University, MI, East Lansing 48824, USA.|Department of Computer Science and Engineering, Department of Energy Plant Research Laboratory and Department of Biochemistry and Molecular Biology, Michigan State University, MI, East Lansing 48824, USA.|Department of Computer Science and Engineering, Department of Energy Plant Research Laboratory and Department of Biochemistry and Molecular Biology, Michigan State University, MI, East Lansing 48824, USA Department of Computer Science and Engineering, Department of Energy Plant Research Laboratory and Department of Biochemistry and Molecular Biology, Michigan State University, MI, East Lansing 48824, USA.|Department of Computer Science and Engineering, Department of Energy Plant Research Laboratory and Department of Biochemistry and Molecular Biology, Michigan State University, MI, East Lansing 48824, USA Department of Computer Science and Engineering, Department of Energy Plant Research Laboratory and Department of Biochemistry and Molecular Biology, Michigan State University, MI, East Lansing 48824, USA.', 'United States|United States|United States|United States|United States', 8, 'Algorithms|Models, Biological|Phenotype|Photosynthesis|Plants|Quality Control', 'Journal Article', '10.1093/bioinformatics/btu854', '25617414', 'Plant phenomics, the collection of large-scale plant phenotype data, is growing exponentially. The resources have become essential component of modern plant science. Such complex datasets are critical for understanding the mechanisms governing energy intake and storage in plants, and this is essential for improving crop productivity. However, a major issue facing these efforts is the determination of the quality of phenotypic data. Automated methods are needed to identify and characterize alterations caused by system errors, all of which are difficult to remove in the data collection step and distinguish them from more interesting cases of altered biological responses.'),
(79002, 2015, 'bio', 'ASSIGN: context-specific genomic profiling of multiple heterogeneous biological pathways', 'Shen, Ying|Rahman, Mumtahena|Piccolo, Stephen R|Gusenleitner, Daniel|El-Chaar, Nader N|Cheng, Luis|Monti, Stefano|Bild, Andrea H|Johnson, W Evan', 'Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA 02118 USA, Department of Biomedical Informatics and Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112 USA.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA 02118 USA, Department of Biomedical Informatics and Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112 USA.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA 02118 USA, Department of Biomedical Informatics and Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112 USA Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA 02118 USA, Department of Biomedical Informatics and Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112 USA.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA 02118 USA, Department of Biomedical Informatics and Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112 USA.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA 02118 USA, Department of Biomedical Informatics and Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112 USA.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA 02118 USA, Department of Biomedical Informatics and Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112 USA.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA 02118 USA, Department of Biomedical Informatics and Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112 USA.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA 02118 USA, Department of Biomedical Informatics and Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112 USA Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA 02118 USA, Department of Biomedical Informatics and Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112 USA.|Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA 02118 USA, Department of Biomedical Informatics and Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112 USA Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA 02118 USA, Department of Biomedical Informatics and Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112 USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 21, 'Animals|Bayes Theorem|Breast Neoplasms|Female|Gene Expression Profiling|Genomics|Humans|Rats|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btv031', '25617415', 'Although gene-expression signature-based biomarkers are often developed for clinical diagnosis, many promising signatures fail to replicate during validation. One major challenge is that biological samples used to generate and validate the signature are often from heterogeneous biological contexts-controlled or in vitro samples may be used to generate the signature, but patient samples may be used for validation. In addition, systematic technical biases from multiple genome-profiling platforms often mask true biological variation. Addressing such challenges will enable us to better elucidate disease mechanisms and provide improved guidance for personalized therapeutics.'),
(79003, 2015, 'bio', 'Quantitative visualization of alternative exon expression from RNA-seq data', 'Katz, Yarden|Wang, Eric T|Silterra, Jacob|Schwartz, Schraga|Wong, Bang|Thorvaldsdóttir, Helga|Robinson, James T|Mesirov, Jill P|Airoldi, Edoardo M|Burge, Christopher B', 'Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, Department of Biology, MIT, Cambridge, MA.|Department of Biology, MIT, Cambridge, MA.|The Broad Institute of Harvard, MIT, Cambridge, MA, USA.|The Broad Institute of Harvard, MIT, Cambridge, MA, USA.|The Broad Institute of Harvard, MIT, Cambridge, MA, USA.|The Broad Institute of Harvard, MIT, Cambridge, MA, USA.|The Broad Institute of Harvard, MIT, Cambridge, MA, USA.|The Broad Institute of Harvard, MIT, Cambridge, MA, USA.|The Broad Institute of Harvard, MIT, Cambridge, MA, USA, Department of Statistics, Harvard University, Cambridge, MA, USA and.|Department of Biology, MIT, Cambridge, MA, Department of Biological Engineering, MIT, Cambridge, MA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Alternative Splicing|Computer Graphics|Exons|Gene Expression Profiling|Humans|RNA Isoforms|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btv034', '25617416', 'Analysis of RNA sequencing (RNA-Seq) data revealed that the vast majority of human genes express multiple mRNA isoforms, produced by alternative pre-mRNA splicing and other mechanisms, and that most alternative isoforms vary in expression between human tissues. As RNA-Seq datasets grow in size, it remains challenging to visualize isoform expression across multiple samples.'),
(79004, 2015, 'bio', 'bbcontacts: prediction of xcexb2-strand pairing from direct coupling patterns', 'Andreani, Jessica|Sxc3xb6ding, Johannes', 'Gene Center, LMU Munich, Feodor-Lynen-Strasse 25, 81377 Munich, Germany and Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Gxc3xb6ttingen, Germany Gene Center, LMU Munich, Feodor-Lynen-Strasse 25, 81377 Munich, Germany and Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Gxc3xb6ttingen, Germany.|Gene Center, LMU Munich, Feodor-Lynen-Strasse 25, 81377 Munich, Germany and Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Gxc3xb6ttingen, Germany Gene Center, LMU Munich, Feodor-Lynen-Strasse 25, 81377 Munich, Germany and Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Gxc3xb6ttingen, Germany.', 'Germany|Germany', 24, 'Markov Chains|Protein Structure, Secondary|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btv041', '25618863', 'It has recently become possible to build reliable de novo models of proteins if a multiple sequence alignment (MSA) of at least 1000 homologous sequences can be built. Methods of global statistical network analysis can explain the observed correlations between columns in the MSA by a small set of directly coupled pairs of columns. Strong couplings are indicative of residue-residue contacts, and from the predicted contacts a structure can be computed. Here, we exploit the structural regularity of paired xcexb2-strands that leads to characteristic patterns in the noisy matrices of couplings. The xcexb2-xcexb2 contacts should be detected more reliably than single contacts, reducing the required number of sequences in the MSAs.'),
(79005, 2015, 'bio', 'Prediction of potential disease-associated microRNAs based on random walk', 'Xuan, Ping|Han, Ke|Guo, Yahong|Li, Jin|Li, Xia|Zhong, Yingli|Zhang, Zhaogong|Ding, Jian', 'School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China, School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China, School of Information Science and Technology, Heilongjiang University, Harbin 150080, China and College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.|School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China, School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China, School of Information Science and Technology, Heilongjiang University, Harbin 150080, China and College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.|School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China, School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China, School of Information Science and Technology, Heilongjiang University, Harbin 150080, China and College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.|School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China, School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China, School of Information Science and Technology, Heilongjiang University, Harbin 150080, China and College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.|School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China, School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China, School of Information Science and Technology, Heilongjiang University, Harbin 150080, China and College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.|School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China, School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China, School of Information Science and Technology, Heilongjiang University, Harbin 150080, China and College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.|School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China, School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China, School of Information Science and Technology, Heilongjiang University, Harbin 150080, China and College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.|School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China, School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China, School of Information Science and Technology, Heilongjiang University, Harbin 150080, China and College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.', 'China|China|China|China|China|China|China|China', 0, 'Disease|Gene Regulatory Networks|Humans|MicroRNAs|Models, Statistical|Neoplasms', 'Journal Article', '10.1093/bioinformatics/btv039', '25618864', 'Identifying microRNAs associated with diseases (disease miRNAs) is helpful for exploring the pathogenesis of diseases. Because miRNAs fulfill function via the regulation of their target genes and because the current number of experimentally validated targets is insufficient, some existing methods have inferred potential disease miRNAs based on the predicted targets. It is difficult for these methods to achieve excellent performance due to the high false-positive and false-negative rates for the target prediction results. Alternatively, several methods have constructed a network composed of miRNAs based on their associated diseases and have exploited the information within the network to predict the disease miRNAs. However, these methods have failed to take into account the prior information regarding the network nodes and the respective local topological structures of the different categories of nodes. Therefore, it is essential to develop a method that exploits the more useful information to predict reliable disease miRNA candidates.'),
(79006, 2015, 'bio', 'Context-specific metabolic network reconstruction of a naphthalene-degrading bacterial community guided by metaproteomic data', 'Tobalina, Luis|Bargiela, Rafael|Pey, Jon|Herbst, Florian-Alexander|Lores, Iván|Rojo, David|Barbas, Coral|Peláez, Ana I|Sánchez, Jesús|von Bergen, Martin|Seifert, Jana|Ferrer, Manuel|Planes, Francisco J', 'CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.|CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.|CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.|CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.|CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.|CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.|CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.|CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.|CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.|CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.|CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.|CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.|CEIT and Tecnun (University of Navarra), San Sebastián, Spain, CSIC, Institute of Catalysis, Madrid, Spain, Helmholtz Centre for Environmental Research, Department of Proteomics, Leipzig, Germany, Área de Microbiología, IUBA, Universidad de Oviedo, Oviedo, Spain, Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Madrid, Spain, Department of Metabolomics, UFZ-Helmholtz-Zentrum für Umweltforschung GmbH, Leipzig, Germany and Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 16, 'Bacteria|Metabolic Networks and Pathways|Naphthalenes|Proteomics|Soil Pollutants', 'Journal Article', '10.1093/bioinformatics/btv036', '25618865', 'With the advent of meta-omics data, the use of metabolic networks for the functional analysis of microbial communities became possible. However, while network-based methods are widely developed for single organisms, their application to bacterial communities is currently limited.'),
(79007, 2015, 'bio', 'The assembly of miRNA-mRNA-protein regulatory networks using high-throughput expression data', 'Chu, Tianjiao|Mouillet, Jean-Francois|Hood, Brian L|Conrads, Thomas P|Sadovsky, Yoel', 'Magee-Womens Research Institute, Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, 15213 USA, Womens Health Integrated Research Center at Inova Health System, Annandale, VA, 22003 USA and Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, PA, 15213 USA.|Magee-Womens Research Institute, Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, 15213 USA, Womens Health Integrated Research Center at Inova Health System, Annandale, VA, 22003 USA and Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, PA, 15213 USA.|Magee-Womens Research Institute, Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, 15213 USA, Womens Health Integrated Research Center at Inova Health System, Annandale, VA, 22003 USA and Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, PA, 15213 USA.|Magee-Womens Research Institute, Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, 15213 USA, Womens Health Integrated Research Center at Inova Health System, Annandale, VA, 22003 USA and Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, PA, 15213 USA.|Magee-Womens Research Institute, Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, 15213 USA, Womens Health Integrated Research Center at Inova Health System, Annandale, VA, 22003 USA and Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, PA, 15213 USA Magee-Womens Research Institute, Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, 15213 USA, Womens Health Integrated Research Center at Inova Health System, Annandale, VA, 22003 USA and Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, PA, 15213 USA.', 'United States|United States|United States|United States|United States', 7, 'Algorithms|Gene Expression Profiling|Gene Regulatory Networks|High-Throughput Nucleotide Sequencing|Humans|MicroRNAs|Proteins|RNA, Messenger|Transcription Factors|Trophoblasts', 'Journal Article', '10.1093/bioinformatics/btv038', '25619993', 'Inference of gene regulatory networks from high throughput measurement of gene and protein expression is particularly attractive because it allows the simultaneous discovery of interactive molecular signals for numerous genes and proteins at a relatively low cost.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(79008, 2015, 'bio', 'ENVIRONMENTS and EOL: identification of Environment Ontology terms in text and the annotation of the Encyclopedia of Life', 'Pafilis, Evangelos|Frankild, Sune P|Schnetzer, Julia|Fanini, Lucia|Faulwetter, Sarah|Pavloudi, Christina|Vasileiadou, Katerina|Leary, Patrick|Hammock, Jennifer|Schulz, Katja|Parr, Cynthia Sims|Arvanitidis, Christos|Jensen, Lars Juhl', 'Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.|Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.|Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.|Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.|Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.|Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.|Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.|Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.|Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.|Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.|Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.|Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.|Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 0, 'Animals|Biodiversity|Biological Ontologies|Data Mining|Ecosystem|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btv045', '25619994', 'The association of organisms to their environments is a key issue in exploring biodiversity patterns. This knowledge has traditionally been scattered, but textual descriptions of taxa and their habitats are now being consolidated in centralized resources. However, structured annotations are needed to facilitate large-scale analyses. Therefore, we developed ENVIRONMENTS, a fast dictionary-based tagger capable of identifying Environment Ontology (ENVO) terms in text. We evaluate the accuracy of the tagger on a new manually curated corpus of 600 Encyclopedia of Life (EOL) species pages. We use the tagger to associate taxa with environments by tagging EOL text content monthly, and integrate the results into the EOL to disseminate them to a broad audience of users.'),
(79009, 2015, 'bio', 'Bayesian feature selection for high-dimensional linear regression via the Ising approximation with applications to genomics', 'Fisher, Charles K|Mehta, Pankaj', 'Department of Physics, Boston University, Boston, MA 02215, USA.|Department of Physics, Boston University, Boston, MA 02215, USA.', 'United States|United States', 5, 'Adipose Tissue|Algorithms|Artificial Intelligence|Bayes Theorem|Gene Expression Profiling|Genomics|Humans|Linear Models|Male|Probability|Soybeans', 'Journal Article', '10.1093/bioinformatics/btv037', '25619995', 'Feature selection, identifying a subset of variables that are relevant for predicting a response, is an important and challenging component of many methods in statistics and machine learning. Feature selection is especially difficult and computationally intensive when the number of variables approaches or exceeds the number of samples, as is often the case for many genomic datasets.'),
(79010, 2015, 'bio', 'protr/ProtrWeb: R package and web server for generating various numerical representation schemes of protein sequences', 'Xiao, Nan|Cao, Dong-Sheng|Zhu, Min-Feng|Xu, Qing-Song', 'School of Mathematics and Statistics and School of Pharmaceutical Sciences, Central South University, Changsha 410083, Peoples Republic of China.|School of Mathematics and Statistics and School of Pharmaceutical Sciences, Central South University, Changsha 410083, Peoples Republic of China.|School of Mathematics and Statistics and School of Pharmaceutical Sciences, Central South University, Changsha 410083, Peoples Republic of China.|School of Mathematics and Statistics and School of Pharmaceutical Sciences, Central South University, Changsha 410083, Peoples Republic of China.', 'China|China|China|China', 0, 'Amino Acids|Internet|Peptides|Position-Specific Scoring Matrices|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btv042', '25619996', 'Amino acid sequence-derived structural and physiochemical descriptors are extensively utilized for the research of structural, functional, expression and interaction profiles of proteins and peptides. We developed protr, a comprehensive R package for generating various numerical representation schemes of proteins and peptides from amino acid sequence. The package calculates eight descriptor groups composed of 22 types of commonly used descriptors that include about 22 700 descriptor values. It allows users to select amino acid properties from the AAindex database, and use self-defined properties to construct customized descriptors. For proteochemometric modeling, it calculates six types of scales-based descriptors derived by various dimensionality reduction methods. The protr package also integrates the functionality of similarity score computation derived by protein sequence alignment and Gene Ontology semantic similarity measures within a list of proteins, and calculates profile-based protein features based on position-specific scoring matrix. We also developed ProtrWeb, a user-friendly web server for calculating descriptors presented in the protr package.'),
(79011, 2015, 'bio', 'Cooperative development of logical modelling standards and tools with CoLoMoTo', 'Naldi, Aurélien|Monteiro, Pedro T|Müssel, Christoph|Consortium for Logical Models and Tools|Kestler, Hans A|Thieffry, Denis|Xenarios, Ioannis|Saez-Rodriguez, Julio|Helikar, Tomas|Chaouiya, Claudine', 'Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA.|Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA.|Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA.|Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA.|Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Res|Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA.|Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA.|Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA.|Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA.|Center for Integrative Genomics (CIG), University of Lausanne, Lausanne, Switzerland, Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal, Instituto Gulbenkian de Ciência (IGC), Oeiras, Portugal, Medical Systems Biology, Ulm University, Germany, Friedrich-Schiller University Jena, Jena, Germany, Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany, Institut de Biologie de lÉcole Normale Supérieure (IBENS)-UMR CNRS 8197-INSERM 1024, Paris, France, Swiss-Prot & Vital-IT group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom and Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 0, 'Animals|Cells|Computer Simulation|Humans|Metabolic Networks and Pathways|Models, Theoretical|Societies, Scientific|Software|Systems Biology', 'Letter', '10.1093/bioinformatics/btv013', '25619997', 'The identification of large regulatory and signalling networks involved in the control of crucial cellular processes calls for proper modelling approaches. Indeed, models can help elucidate properties of these networks, understand their behaviour and provide (testable) predictions by performing in silico experiments. In this context, qualitative, logical frameworks have emerged as relevant approaches, as demonstrated by a growing number of published models, along with new methodologies and software tools. This productive activity now requires a concerted effort to ensure model reusability and interoperability between tools. Following an outline of the logical modelling framework, we present the most important achievements of the Consortium for Logical Models and Tools, along with future objectives. Our aim is to advertise this open community, which welcomes contributions from all researchers interested in logical modelling or in related mathematical and computational developments.'),
(79012, 2015, 'bio', 'Deterministic identification of specific individuals from GWAS results', 'Cai, Ruichu|Hao, Zhifeng|Winslett, Marianne|Xiao, Xiaokui|Yang, Yin|Zhang, Zhenjie|Zhou, Shuigeng', 'School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China, 510000, Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd., Singapore, 138632, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, 61801-2302, School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, College of Science, Engineering and Technology, Hamad Bin Khalifa University, Doha, Qatar and School of Computing, Fudan University, Shanghai, China, 200433 School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China, 510000, Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd., Singapore, 138632, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, 61801-2302, School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, College of Science, Engineering and Technology, Hamad Bin Khalifa University, Doha, Qatar and School of Computing, Fudan University, Shanghai, China, 200433.|School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China, 510000, Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd., Singapore, 138632, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, 61801-2302, School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, College of Science, Engineering and Technology, Hamad Bin Khalifa University, Doha, Qatar and School of Computing, Fudan University, Shanghai, China, 200433.|School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China, 510000, Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd., Singapore, 138632, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, 61801-2302, School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, College of Science, Engineering and Technology, Hamad Bin Khalifa University, Doha, Qatar and School of Computing, Fudan University, Shanghai, China, 200433 School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China, 510000, Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd., Singapore, 138632, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, 61801-2302, School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, College of Science, Engineering and Technology, Hamad Bin Khalifa University, Doha, Qatar and School of Computing, Fudan University, Shanghai, China, 200433.|School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China, 510000, Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd., Singapore, 138632, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, 61801-2302, School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, College of Science, Engineering and Technology, Hamad Bin Khalifa University, Doha, Qatar and School of Computing, Fudan University, Shanghai, China, 200433.|School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China, 510000, Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd., Singapore, 138632, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, 61801-2302, School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, College of Science, Engineering and Technology, Hamad Bin Khalifa University, Doha, Qatar and School of Computing, Fudan University, Shanghai, China, 200433.|School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China, 510000, Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd., Singapore, 138632, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, 61801-2302, School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, College of Science, Engineering and Technology, Hamad Bin Khalifa University, Doha, Qatar and School of Computing, Fudan University, Shanghai, China, 200433.|School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China, 510000, Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd., Singapore, 138632, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, 61801-2302, School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, College of Science, Engineering and Technology, Hamad Bin Khalifa University, Doha, Qatar and School of Computing, Fudan University, Shanghai, China, 200433.', 'China|China|China|China|China|China|China', 16, 'Algorithms|Genetic Privacy|Genome, Human|Genome-Wide Association Study|Genotype|Humans|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btv018', '25630377', 'Genome-wide association studies (GWASs) are commonly applied on human genomic data to understand the causal gene combinations statistically connected to certain diseases. Patients involved in these GWASs could be re-identified when the studies release statistical information on a large number of single-nucleotide polymorphisms. Subsequent work, however, found that such privacy attacks are theoretically possible but unsuccessful and unconvincing in real settings.'),
(79013, 2015, 'bio', 'MetAmp: combining amplicon data from multiple markers for OTU analysis', 'Zhbannikov, Ilya Y|Foster, James A', 'Graduate Program in Bioinformatics and Computational Biology, University of Idaho and Institute of Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA.|Graduate Program in Bioinformatics and Computational Biology, University of Idaho and Institute of Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA Graduate Program in Bioinformatics and Computational Biology, University of Idaho and Institute of Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA.', 'United States|United States', 0, 'Algorithms|Classification|Genetic Markers|Humans|Metagenomics|Microbiota|RNA, Ribosomal, 16S|Software', 'Journal Article', '10.1093/bioinformatics/btv049', '25630378', 'We present a novel method and corresponding application, MetAmp, to combine amplicon data from multiple genomic markers into Operational Taxonomic Units (OTUs) for microbial community analysis, calibrating the markers using data from known microbial genomes. When amplicons for multiple markers such as the 16S rRNA gene hypervariable regions are available, MetAmp improves the accuracy of OTU-based methods for characterizing bacterial composition and community structure. MetAmp works best with at least three markers, and is applicable to non-bacterial analyses and to non 16S markers. Our application and testing have been limited to 16S analysis of microbial communities.'),
(79014, 2015, 'bio', 'RAMPART: a workflow management system for de novo genome assembly', 'Mapleson, Daniel|Drou, Nizar|Swarbreck, David', 'The Genome Analysis Centre, Norwich Research Park, Norwich NR4 7UH, UK.|The Genome Analysis Centre, Norwich Research Park, Norwich NR4 7UH, UK.|The Genome Analysis Centre, Norwich Research Park, Norwich NR4 7UH, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Genome|Genomics|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btv056', '25637556', 'The de novo assembly of genomes from whole- genome shotgun sequence data is a computationally intensive, multi-stage task and it is not known a priori which methods and parameter settings will produce optimal results. In current de novo assembly projects, a popular strategy involves trying many approaches, using different tools and settings, and then comparing and contrasting the results in order to select a final assembly for publication.'),
(79015, 2015, 'bio', 'GenoExp: a web tool for predicting gene expression levels from single nucleotide polymorphisms', 'Manor, Ohad|Segal, Eran', 'Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.|Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel Department of Computer Science and Applied Mathematics and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.', 'Israel|Israel', 5, 'Cell Line|Gene Expression Profiling|Humans|Internet|Models, Genetic|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btv050', '25637557', 'Understanding the effect of single nucleotide polymorphisms (SNPs) on the expression level of genes is an important goal. We recently published a study in which we devised a multi-SNP predictive model for gene expression in Lymphoblastoid cell lines (LCL), and showed that it can robustly predict the expression of a small number of genes in test individuals. Here, we validate the generality of our models by predicting expression profiles for genes in LCL in an independent study, and extend the pool of predictable genes for which we are able to explain more than 25% of their expression variability to 232 genes across 14 different cell types. As the number of people who obtained their SNP profiles through companies such as 23andMe is rising rapidly, we developed GenoExp, a web-based tool in which users can upload their individual SNP data and obtain predicted expression levels for the set of predictable genes across the 14 different cell types. Our tool thus allows users with biological knowledge to study the possible effects that their set of SNPs might have on these genes and predict their cell-specific expression levels relative to the population average.'),
(79016, 2015, 'bio', 'Dizzy-Beats: a Bayesian evidence analysis tool for systems biology', 'Aitken, Stuart|Kilpatrick, Alastair M|Akman, Ozgur E', 'MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA, Centre for Systems, Dynamics and Control, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter EX4 4QF, UK.|MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA, Centre for Systems, Dynamics and Control, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter EX4 4QF, UK MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA, Centre for Systems, Dynamics and Control, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter EX4 4QF, UK.|MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA, Centre for Systems, Dynamics and Control, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter EX4 4QF, UK.', 'United Kingdom|United Kingdom|United Kingdom', 3, 'Algorithms|Bayes Theorem|Likelihood Functions|Models, Biological|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btv062', '25637558', 'Model selection and parameter inference are complex problems of long-standing interest in systems biology. Selecting between competing models arises commonly as underlying biochemical mechanisms are often not fully known, hence alternative models must be considered. Parameter inference yields important information on the extent to which the data and the model constrain parameter values.'),
(79017, 2015, 'bio', 'NetExplore: a web server for modeling small network motifs', 'Papatsenko, Dmitri|Lemischka, Ihor R', 'Department of Regenerative and Developmental Biology, Black Family Stem Cell Institute andDepartment of Pharmacology and System Therapeutics, Icahn School of Medicine at Mount Sinai, Systems Biology Center New York, One Gustave L. Levy Place, New York, NY 10029, USA Department of Regenerative and Developmental Biology, Black Family Stem Cell Institute andDepartment of Pharmacology and System Therapeutics, Icahn School of Medicine at Mount Sinai, Systems Biology Center New York, One Gustave L. Levy Place, New York, NY 10029, USA.|Department of Regenerative and Developmental Biology, Black Family Stem Cell Institute andDepartment of Pharmacology and System Therapeutics, Icahn School of Medicine at Mount Sinai, Systems Biology Center New York, One Gustave L. Levy Place, New York, NY 10029, USA Department of Regenerative and Developmental Biology, Black Family Stem Cell Institute andDepartment of Pharmacology and System Therapeutics, Icahn School of Medicine at Mount Sinai, Systems Biology Center New York, One Gustave L. Levy Place, New York, NY 10029, USA Department of Regenerative and Developmental Biology, Black Family Stem Cell Institute andDepartment of Pharmacology and System Therapeutics, Icahn School of Medicine at Mount Sinai, Systems Biology Center New York, One Gustave L. Levy Place, New York, NY 10029, USA.', 'United States|United States', 0, 'Algorithms|Gene Regulatory Networks|Internet|Models, Genetic|Software', 'Journal Article', '10.1093/bioinformatics/btv058', '25637559', 'Quantitative and qualitative assessment of biological data often produces small essential recurrent networks, containing 3-5 components called network motifs. In this context, model solutions for small network motifs represent very high interest.'),
(79018, 2015, 'bio', 'Omics Pipe: a community-based framework for reproducible multi-omics data analysis', 'Fisch, Kathleen M|Meißner, Tobias|Gioia, Louis|Ducom, Jean-Christophe|Carland, Tristan M|Loguercio, Salvatore|Su, Andrew I', 'Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA and Department of Human Biology, J. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA 92037, USA.|Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA and Department of Human Biology, J. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA 92037, USA.|Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA and Department of Human Biology, J. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA 92037, USA.|Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA and Department of Human Biology, J. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA 92037, USA.|Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA and Department of Human Biology, J. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA 92037, USA.|Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA and Department of Human Biology, J. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA 92037, USA.|Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA and Department of Human Biology, J. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA 92037, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Breast Neoplasms|Cluster Analysis|Databases, Factual|Exome|Female|Genomics|High-Throughput Nucleotide Sequencing|Humans|Reproducibility of Results|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btv061', '25637560', 'Omics Pipe (http://sulab.scripps.edu/omicspipe) is a computational framework that automates multi-omics data analysis pipelines on high performance compute clusters and in the cloud. It supports best practice published pipelines for RNA-seq, miRNA-seq, Exome-seq, Whole-Genome sequencing, ChIP-seq analyses and automatic processing of data from The Cancer Genome Atlas (TCGA). Omics Pipe provides researchers with a tool for reproducible, open source and extensible next generation sequencing analysis. The goal of Omics Pipe is to democratize next-generation sequencing analysis by dramatically increasing the accessibility and reproducibility of best practice computational pipelines, which will enable researchers to generate biologically meaningful and interpretable results.'),
(79019, 2015, 'bio', 'SFA-SPA: a suffix array based short peptide assembler for metagenomic data', 'Yang, Youngik|Zhong, Cuncong|Yooseph, Shibu', 'Informatics Department, J. Craig Venter Institute, La Jolla, CA 92037, USA.|Informatics Department, J. Craig Venter Institute, La Jolla, CA 92037, USA.|Informatics Department, J. Craig Venter Institute, La Jolla, CA 92037, USA.', 'United States|United States|United States', 6, 'Algorithms|Metagenomics|Peptides|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btv052', '25637561', 'The determination of protein sequences from a metagenomic dataset enables the study of metabolism and functional roles of the organisms that are present in the sampled microbial community. We had previously introduced algorithm and software for the accurate reconstruction of protein sequences from short peptides identified on nucleotide reads in a metagenomic dataset. Here, we present significant computational improvements to the short peptide assembly algorithm that make it practical to reconstruct proteins from large metagenomic datasets containing several hundred million reads, while maintaining accuracy. The improved computational efficiency is achieved using a suffix array data structure that allows for fast querying during the assembly process, and a significant redesign of assembly steps that enables multi-threaded execution.'),
(79020, 2015, 'bio', 'Computational identification of MoRFs in protein sequences', 'Malhis, Nawar|Gsponer, Jörg', 'Centre for High-Throughput Biology and Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.|Centre for High-Throughput Biology and Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada Centre for High-Throughput Biology and Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.', 'Canada|Canada', 0, 'Algorithms|Amino Acids|Computational Biology|Intrinsically Disordered Proteins|Protein Structure, Tertiary|Sequence Analysis, Protein|Software|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btv060', '25637562', 'Intrinsically disordered regions of proteins play an essential role in the regulation of various biological processes. Key to their regulatory function is the binding of molecular recognition features (MoRFs) to globular protein domains in a process known as a disorder-to-order transition. Predicting the location of MoRFs in protein sequences with high accuracy remains an important computational challenge.'),
(79021, 2015, 'bio', 'TIMMA-R: an R package for predicting synergistic multi-targeted drug combinations in cancer cell lines or patient-derived samples', 'He, Liye|Wennerberg, Krister|Aittokallio, Tero|Tang, Jing', 'Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, FI-00290, Helsinki, Finland.|Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, FI-00290, Helsinki, Finland.|Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, FI-00290, Helsinki, Finland.|Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, FI-00290, Helsinki, Finland.', 'Finland|Finland|Finland|Finland', 10, 'Algorithms|Antineoplastic Combined Chemotherapy Protocols|Cell Line, Tumor|Drug Discovery|Drug Synergism|Humans|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btv067', '25638808', 'Network pharmacology-based prediction of multi-targeted drug combinations is becoming a promising strategy to improve anticancer efficacy and safety. We developed a logic-based network algorithm, called Target Inhibition Interaction using Maximization and Minimization Averaging (TIMMA), which predicts the effects of drug combinations based on their binary drug-target interactions and single-drug sensitivity profiles in a given cancer sample. Here, we report the R implementation of the algorithm (TIMMA-R), which is much faster than the original MATLAB code. The major extensions include modeling of multiclass drug-target profiles and network visualization. We also show that the TIMMA-R predictions are robust to the intrinsic noise in the experimental data, thus making it a promising high-throughput tool to prioritize drug combinations in various cancer types for follow-up experimentation or clinical applications.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(79022, 2015, 'bio', 'SPARQL-enabled identifier conversion with Identifiersorg', 'Wimalaratne, Sarala M|Bolleman, Jerven|Juty, Nick|Katayama, Toshiaki|Dumontier, Michel|Redaschi, Nicole|Le Novère, Nicolas|Hermjakob, Henning|Laibe, Camille', 'European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss-Prot group, Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1211 Geneve, Switzerland, Database Center for Life Science (DCLS), Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba 277-0871, Japan, Stanford Center for Biomedical Informatics Research, Stanford University, CA 94305-5479, USA and Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss-Prot group, Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1211 Geneve, Switzerland, Database Center for Life Science (DCLS), Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba 277-0871, Japan, Stanford Center for Biomedical Informatics Research, Stanford University, CA 94305-5479, USA and Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss-Prot group, Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1211 Geneve, Switzerland, Database Center for Life Science (DCLS), Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba 277-0871, Japan, Stanford Center for Biomedical Informatics Research, Stanford University, CA 94305-5479, USA and Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss-Prot group, Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1211 Geneve, Switzerland, Database Center for Life Science (DCLS), Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba 277-0871, Japan, Stanford Center for Biomedical Informatics Research, Stanford University, CA 94305-5479, USA and Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss-Prot group, Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1211 Geneve, Switzerland, Database Center for Life Science (DCLS), Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba 277-0871, Japan, Stanford Center for Biomedical Informatics Research, Stanford University, CA 94305-5479, USA and Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss-Prot group, Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1211 Geneve, Switzerland, Database Center for Life Science (DCLS), Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba 277-0871, Japan, Stanford Center for Biomedical Informatics Research, Stanford University, CA 94305-5479, USA and Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss-Prot group, Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1211 Geneve, Switzerland, Database Center for Life Science (DCLS), Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba 277-0871, Japan, Stanford Center for Biomedical Informatics Research, Stanford University, CA 94305-5479, USA and Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss-Prot group, Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1211 Geneve, Switzerland, Database Center for Life Science (DCLS), Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba 277-0871, Japan, Stanford Center for Biomedical Informatics Research, Stanford University, CA 94305-5479, USA and Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss-Prot group, Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1211 Geneve, Switzerland, Database Center for Life Science (DCLS), Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba 277-0871, Japan, Stanford Center for Biomedical Informatics Research, Stanford University, CA 94305-5479, USA and Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss-Prot group, Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1211 Geneve, Switzerland, Database Center for Life Science (DCLS), Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba 277-0871, Japan, Stanford Center for Biomedical Informatics Research, Stanford University, CA 94305-5479, USA and Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 9, 'Biological Science Disciplines|Databases, Factual|Internet|Semantics|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btv064', '25638809', 'On the semantic web, in life sciences in particular, data is often distributed via multiple resources. Each of these sources is likely to use their own International Resource Identifier for conceptually the same resource or database record. The lack of correspondence between identifiers introduces a barrier when executing federated SPARQL queries across life science data.'),
(79023, 2015, 'bio', 'Similarity-based prediction for Anatomical Therapeutic Chemical classification of drugs by integrating multiple data sources', 'Liu, Zhongyang|Guo, Feifei|Gu, Jiangyong|Wang, Yong|Li, Yang|Wang, Dan|Lu, Liang|Li, Dong|He, Fuchu', 'State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China.|State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China.|State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China.|State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China.|State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China.|State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China.|State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China.|State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China.|State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China, National Center for Protein Sciences Beijing, Beijing 102206, China, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China, Beijing National Laboratory for Molecular Sciences, State Key Lab of Rare Earth Material Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China and Preclinical School, Beijing University of Chinese Medicine, Beijing 100029, China.', 'China|China|China|China|China|China|China|China|China', 0, 'Computational Biology|Databases, Factual|Drug Discovery|Drug Repositioning|Drug Therapy|Drug-Related Side Effects and Adverse Reactions|Internet|Models, Theoretical|Pharmaceutical Preparations|Software|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btv055', '25638810', 'Anatomical Therapeutic Chemical (ATC) classification system, widely applied in almost all drug utilization studies, is currently the most widely recognized classification system for drugs. Currently, new drug entries are added into the system only on users requests, which leads to seriously incomplete drug coverage of the system, and bioinformatics prediction is helpful during this process.'),
(79024, 2015, 'bio', 'Learning HMMs for nucleotide sequences from amino acid alignments', 'Fischer, Carlos N|Carareto, Claudia M A|dos Santos, Renato A C|Cerri, Ricardo|Costa, Eduardo|Schietgat, Leander|Vens, Celine', 'Department of Statistics, Applied Maths, and Computer Science, UNESP - São Paulo State University, Rio Claro, SP, Brazil, Department of Biology, UNESP-São Paulo State University, São José do Rio Preto, SP, Brazil, Institute of Biosciences, UNESP-São Paulo State University, Rio Claro, SP, Brazil, Department of Computer Science, UFSCar-Federal University of São Carlos, São Carlos, SP, Brazil, Department of Computer Science, USP-University of São Paulo, São Carlos, SP, Brazil, Department of Computer Science, KU Leuven, Leuven, Belgium and Department of Public Health and Primary Care, KU Leuven Kulak, Kortrijk, Belgium.|Department of Statistics, Applied Maths, and Computer Science, UNESP - São Paulo State University, Rio Claro, SP, Brazil, Department of Biology, UNESP-São Paulo State University, São José do Rio Preto, SP, Brazil, Institute of Biosciences, UNESP-São Paulo State University, Rio Claro, SP, Brazil, Department of Computer Science, UFSCar-Federal University of São Carlos, São Carlos, SP, Brazil, Department of Computer Science, USP-University of São Paulo, São Carlos, SP, Brazil, Department of Computer Science, KU Leuven, Leuven, Belgium and Department of Public Health and Primary Care, KU Leuven Kulak, Kortrijk, Belgium.|Department of Statistics, Applied Maths, and Computer Science, UNESP - São Paulo State University, Rio Claro, SP, Brazil, Department of Biology, UNESP-São Paulo State University, São José do Rio Preto, SP, Brazil, Institute of Biosciences, UNESP-São Paulo State University, Rio Claro, SP, Brazil, Department of Computer Science, UFSCar-Federal University of São Carlos, São Carlos, SP, Brazil, Department of Computer Science, USP-University of São Paulo, São Carlos, SP, Brazil, Department of Computer Science, KU Leuven, Leuven, Belgium and Department of Public Health and Primary Care, KU Leuven Kulak, Kortrijk, Belgium.|Department of Statistics, Applied Maths, and Computer Science, UNESP - São Paulo State University, Rio Claro, SP, Brazil, Department of Biology, UNESP-São Paulo State University, São José do Rio Preto, SP, Brazil, Institute of Biosciences, UNESP-São Paulo State University, Rio Claro, SP, Brazil, Department of Computer Science, UFSCar-Federal University of São Carlos, São Carlos, SP, Brazil, Department of Computer Science, USP-University of São Paulo, São Carlos, SP, Brazil, Department of Computer Science, KU Leuven, Leuven, Belgium and Department of Public Health and Primary Care, KU Leuven Kulak, Kortrijk, Belgium.|Department of Statistics, Applied Maths, and Computer Science, UNESP - São Paulo State University, Rio Claro, SP, Brazil, Department of Biology, UNESP-São Paulo State University, São José do Rio Preto, SP, Brazil, Institute of Biosciences, UNESP-São Paulo State University, Rio Claro, SP, Brazil, Department of Computer Science, UFSCar-Federal University of São Carlos, São Carlos, SP, Brazil, Department of Computer Science, USP-University of São Paulo, São Carlos, SP, Brazil, Department of Computer Science, KU Leuven, Leuven, Belgium and Department of Public Health and Primary Care, KU Leuven Kulak, Kortrijk, Belgium.|Department of Statistics, Applied Maths, and Computer Science, UNESP - São Paulo State University, Rio Claro, SP, Brazil, Department of Biology, UNESP-São Paulo State University, São José do Rio Preto, SP, Brazil, Institute of Biosciences, UNESP-São Paulo State University, Rio Claro, SP, Brazil, Department of Computer Science, UFSCar-Federal University of São Carlos, São Carlos, SP, Brazil, Department of Computer Science, USP-University of São Paulo, São Carlos, SP, Brazil, Department of Computer Science, KU Leuven, Leuven, Belgium and Department of Public Health and Primary Care, KU Leuven Kulak, Kortrijk, Belgium.|Department of Statistics, Applied Maths, and Computer Science, UNESP - São Paulo State University, Rio Claro, SP, Brazil, Department of Biology, UNESP-São Paulo State University, São José do Rio Preto, SP, Brazil, Institute of Biosciences, UNESP-São Paulo State University, Rio Claro, SP, Brazil, Department of Computer Science, UFSCar-Federal University of São Carlos, São Carlos, SP, Brazil, Department of Computer Science, USP-University of São Paulo, São Carlos, SP, Brazil, Department of Computer Science, KU Leuven, Leuven, Belgium and Department of Public Health and Primary Care, KU Leuven Kulak, Kortrijk, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Animals|Bacteria|Fungal Proteins|Genomics|Markov Chains|Phosphoric Monoester Hydrolases|Protein Structure, Tertiary|Ribonuclease H|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btv054', '25638811', 'Profile hidden Markov models (profile HMMs) are known to efficiently predict whether an amino acid (AA) sequence belongs to a specific protein family. Profile HMMs can also be used to search for protein domains in genome sequences. In this case, HMMs are typically learned from AA sequences and then used to search on the six-frame translation of nucleotide (NT) sequences. However, this approach demands additional processing of the original data and search results. Here, we propose an alternative and more direct method which converts an AA alignment into an NT one, after which an NT-based HMM is trained to be applied directly on a genome.'),
(79025, 2015, 'bio', 'KAPPA, a simple algorithm for discovery and clustering of proteins defined by a key amino acid pattern: a case study of the cysteine-rich proteins', 'Joly, Valentin|Matton, Daniel P', 'Institut de Recherche en Biologie Vxc3xa9gxc3xa9tale, Dxc3xa9partement de Sciences biologiques, Universitxc3xa9 de Montrxc3xa9al, 4101 rue Sherbrooke Est, Montrxc3xa9al, QC H1X 2B2, Canada.|Institut de Recherche en Biologie Vxc3xa9gxc3xa9tale, Dxc3xa9partement de Sciences biologiques, Universitxc3xa9 de Montrxc3xa9al, 4101 rue Sherbrooke Est, Montrxc3xa9al, QC H1X 2B2, Canada.', 'Canada|Canada', 4, 'Algorithms|Amino Acids|Animals|Cluster Analysis|Cysteine|Humans|Plant Proteins|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btv047', '25638812', 'Proteins defined by a key amino acid pattern are key players in the exchange of signals between bacteria, animals and plants, as well as important mediators for cell-cell communication within a single organism. Their description and characterization open the way to a better knowledge of molecular signalling in a broad range of organisms, and to possible application in medical and agricultural research. The contrasted pattern of evolution in these proteins makes it difficult to detect and cluster them with classical sequence-based search tools. Here, we introduce Key Aminoacid Pattern-based Protein Analyzer (KAPPA), a new multi-platform program to detect them in a given set of proteins, analyze their pattern and cluster them by comparison to reference patterns (ab initio search) or internal pairwise comparison (de novo search).'),
(79026, 2015, 'bio', 'Where are we at regarding species translation? A review of the sbv IMPROVER challenge', 'Hoeng, J|Peitsch, M C|Meyer, P|Jurisica, I', 'Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, USA, Department of Computer Science and Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.|Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, USA, Department of Computer Science and Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.|Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, USA, Department of Computer Science and Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.|Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, USA, Department of Computer Science and Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland IBM T.J. Watson Research Center, Computational Biology, Yorktown Heights, NY 10598, USA, Department of Computer Science and Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Canada', 1, 'Animals|Disease Models, Animal|Humans|Models, Genetic|Software|Species Specificity|Systems Biology|Translational Medical Research', 'Editorial', '10.1093/bioinformatics/btv065', '25638813', '-'),
(79027, 2015, 'bio', 'Factor graph analysis of live cell-imaging data reveals mechanisms of cell fate decisions', 'Niederberger, Theresa|Failmezger, Henrik|Uskat, Diana|Poron, Don|Glauche, Ingmar|Scherf, Nico|Roeder, Ingo|Schroeder, Timm|Tresch, Achim', 'Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.|Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.|Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.|Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.|Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.|Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.|Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.|Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.|Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland Gene Center, Department of Chemistry and Biochemistry, Ludwig-Maximilians-University München, Germany, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany Department of Biology, Albertus-Magnus University, Cologne, Germany, Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany and Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 8, 'Algorithms|Animals|Cell Differentiation|Cell Lineage|Granulocyte-Macrophage Progenitor Cells|Mice|Models, Statistical|Monocytes|Neutrophils|Single-Cell Analysis|Time-Lapse Imaging', 'Journal Article', '10.1093/bioinformatics/btv040', '25638814', 'Cell fate decisions have a strong stochastic component. The identification of the underlying mechanisms therefore requires a rigorous statistical analysis of large ensembles of single cells that were tracked and phenotyped over time.'),
(79028, 2015, 'bio', 'Starcode: sequence clustering based on all-pairs search', 'Zorita, Eduard|Cuscó, Pol|Filion, Guillaume J', 'Genome Architecture, Gene Regulation, Stem Cells and Cancer Programme, Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003 Barcelona and Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain Genome Architecture, Gene Regulation, Stem Cells and Cancer Programme, Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003 Barcelona and Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain.|Genome Architecture, Gene Regulation, Stem Cells and Cancer Programme, Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003 Barcelona and Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain Genome Architecture, Gene Regulation, Stem Cells and Cancer Programme, Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003 Barcelona and Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain.|Genome Architecture, Gene Regulation, Stem Cells and Cancer Programme, Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003 Barcelona and Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain Genome Architecture, Gene Regulation, Stem Cells and Cancer Programme, Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003 Barcelona and Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain.', 'Spain|Spain|Spain', 35, 'Algorithms|Cluster Analysis|Computational Biology|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btv053', '25638815', 'The increasing throughput of sequencing technologies offers new applications and challenges for computational biology. In many of those applications, sequencing errors need to be corrected. This is particularly important when sequencing reads from an unknown reference such as random DNA barcodes. In this case, error correction can be done by performing a pairwise comparison of all the barcodes, which is a computationally complex problem.'),
(79029, 2015, 'bio', 'CNOGpro: detection and quantification of CNVs in prokaryotic whole-genome sequencing data', 'Brynildsrud, Ola|Snipen, Lars-Gustav|Bohlin, Jon', 'Section for Biostatistics and Epidemiology, Norwegian University of Life Sciences (NMBU), Oslo, Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences (NMBU), Ås and Norwegian Institute of Public Health, Division of Epidemiology, 0403 Oslo, Norway.|Section for Biostatistics and Epidemiology, Norwegian University of Life Sciences (NMBU), Oslo, Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences (NMBU), Ås and Norwegian Institute of Public Health, Division of Epidemiology, 0403 Oslo, Norway.|Section for Biostatistics and Epidemiology, Norwegian University of Life Sciences (NMBU), Oslo, Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences (NMBU), Ås and Norwegian Institute of Public Health, Division of Epidemiology, 0403 Oslo, Norway.', 'Norway|Norway|Norway', 0, 'Base Composition|DNA Copy Number Variations|Genome, Archaeal|Genome, Bacterial|Genomics|High-Throughput Nucleotide Sequencing|Internet|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btv070', '25644268', 'The explosion of whole-genome sequencing (WGS) as a tool in the mapping and understanding of genomes has been accompanied by an equally massive report of tools and pipelines for the analysis of DNA copy number variation (CNV). Most currently available tools are designed specifically for human genomes, with comparatively little literature devoted to CNVs in prokaryotic organisms. However, there are several idiosyncrasies in prokaryotic WGS data. This work proposes a step-by-step approach for detection and quantification of copy number variants specifically aimed at prokaryotes.'),
(79030, 2015, 'bio', 'ClassifyR: an R package for performance assessment of classification with applications to transcriptomics', 'Strbenac, Dario|Mann, Graham J|Ormerod, John T|Yang, Jean Y H', 'School of Mathematics and Statistics, University of Sydney, New South Wales, Australia and Melanoma Institute Australia, Sydney, New South Wales, Australia.|School of Mathematics and Statistics, University of Sydney, New South Wales, Australia and Melanoma Institute Australia, Sydney, New South Wales, Australia.|School of Mathematics and Statistics, University of Sydney, New South Wales, Australia and Melanoma Institute Australia, Sydney, New South Wales, Australia.|School of Mathematics and Statistics, University of Sydney, New South Wales, Australia and Melanoma Institute Australia, Sydney, New South Wales, Australia.', 'Australia|Australia|Australia|Australia', 6, 'Classification|Gene Expression Profiling|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btv066', '25644269', 'Although a large collection of classification software packages exist in R, a new generic framework for linking custom classification functions with classification performance measures is needed. A generic classification framework has been designed and implemented as an R package in an object oriented style. Its design places emphasis on parallel processing, reproducibility and extensibility. Finally, a comprehensive set of performance measures are available to ease post-processing. Taken together, these important characteristics enable rapid and reproducible benchmarking of alternative classifiers.'),
(79031, 2015, 'bio', 'Expitope: a web server for epitope expression', 'Haase, Kerstin|Raffegerst, Silke|Schendel, Dolores J|Frishman, Dmitrij', 'Department of Genome Oriented Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München, 85354 Freising, Germany, Immune Monitoring Group, Helmholtz Zentrum Munich, Institute of Molecular Immunology, 81377 München, Germany, Medigene Immunotherapies GmbH a Subsidiary of Medigene AG, 82152 Planegg, Germany, Helmholtz Zentrum Munich, Institute of Bioinformatics and Systems Biology, 85764 Neuherberg, Germany and St Petersburg State Polytechnical University, St Petersburg, 195251, Russia.|Department of Genome Oriented Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München, 85354 Freising, Germany, Immune Monitoring Group, Helmholtz Zentrum Munich, Institute of Molecular Immunology, 81377 München, Germany, Medigene Immunotherapies GmbH a Subsidiary of Medigene AG, 82152 Planegg, Germany, Helmholtz Zentrum Munich, Institute of Bioinformatics and Systems Biology, 85764 Neuherberg, Germany and St Petersburg State Polytechnical University, St Petersburg, 195251, Russia Department of Genome Oriented Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München, 85354 Freising, Germany, Immune Monitoring Group, Helmholtz Zentrum Munich, Institute of Molecular Immunology, 81377 München, Germany, Medigene Immunotherapies GmbH a Subsidiary of Medigene AG, 82152 Planegg, Germany, Helmholtz Zentrum Munich, Institute of Bioinformatics and Systems Biology, 85764 Neuherberg, Germany and St Petersburg State Polytechnical University, St Petersburg, 195251, Russia.|Department of Genome Oriented Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München, 85354 Freising, Germany, Immune Monitoring Group, Helmholtz Zentrum Munich, Institute of Molecular Immunology, 81377 München, Germany, Medigene Immunotherapies GmbH a Subsidiary of Medigene AG, 82152 Planegg, Germany, Helmholtz Zentrum Munich, Institute of Bioinformatics and Systems Biology, 85764 Neuherberg, Germany and St Petersburg State Polytechnical University, St Petersburg, 195251, Russia Department of Genome Oriented Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München, 85354 Freising, Germany, Immune Monitoring Group, Helmholtz Zentrum Munich, Institute of Molecular Immunology, 81377 München, Germany, Medigene Immunotherapies GmbH a Subsidiary of Medigene AG, 82152 Planegg, Germany, Helmholtz Zentrum Munich, Institute of Bioinformatics and Systems Biology, 85764 Neuherberg, Germany and St Petersburg State Polytechnical University, St Petersburg, 195251, Russia.|Department of Genome Oriented Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München, 85354 Freising, Germany, Immune Monitoring Group, Helmholtz Zentrum Munich, Institute of Molecular Immunology, 81377 München, Germany, Medigene Immunotherapies GmbH a Subsidiary of Medigene AG, 82152 Planegg, Germany, Helmholtz Zentrum Munich, Institute of Bioinformatics and Systems Biology, 85764 Neuherberg, Germany and St Petersburg State Polytechnical University, St Petersburg, 195251, Russia Department of Genome Oriented Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München, 85354 Freising, Germany, Immune Monitoring Group, Helmholtz Zentrum Munich, Institute of Molecular Immunology, 81377 München, Germany, Medigene Immunotherapies GmbH a Subsidiary of Medigene AG, 82152 Planegg, Germany, Helmholtz Zentrum Munich, Institute of Bioinformatics and Systems Biology, 85764 Neuherberg, Germany and St Petersburg State Polytechnical University, St Petersburg, 195251, Russia Department of Genome Oriented Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München, 85354 Freising, Germany, Immune Monitoring Group, Helmholtz Zentrum Munich, Institute of Molecular Immunology, 81377 München, Germany, Medigene Immunotherapies GmbH a Subsidiary of Medigene AG, 82152 Planegg, Germany, Helmholtz Zentrum Munich, Institute of Bioinformatics and Systems Biology, 85764 Neuherberg, Germany and St Petersburg State Polytechnical University, St Petersburg, 195251, Russia.', 'Germany|Germany|Germany|Germany', 0, 'Antigen Presentation|Cross Reactions|Databases, Protein|Epitopes, T-Lymphocyte|Gene Expression Profiling|Histocompatibility Antigens Class I|Humans|Internet|Peptides|Proteins|Receptors, Antigen, T-Cell|Sequence Analysis, RNA|Software|T-Lymphocytes', 'Journal Article', '10.1093/bioinformatics/btv068', '25644270', 'Adoptive T cell therapies based on introduction of new T cell receptors (TCRs) into patient recipient T cells is a promising new treatment for various kinds of cancers. A major challenge, however, is the choice of target antigens. If an engineered TCR can cross-react with self-antigens in healthy tissue, the side-effects can be devastating. We present the first web server for assessing epitope sharing when designing new potential lead targets. We enable the users to find all known proteins containing their peptide of interest. The web server returns not only exact matches, but also approximate ones, allowing a number of mismatches of the users choice. For the identified candidate proteins the expression values in various healthy tissues, representing all vital human organs, are extracted from RNA Sequencing (RNA-Seq) data as well as from some cancer tissues as control. All results are returned to the user sorted by a score, which is calculated using well-established methods and tools for immunological predictions. It depends on the probability that the epitope is created by proteasomal cleavage and its affinities to the transporter associated with antigen processing and the major histocompatibility complex class I alleles. With this framework, we hope to provide a helpful tool to exclude potential cross-reactivity in the early stage of TCR selection for use in design of adoptive T cell immunotherapy.'),
(79032, 2015, 'bio', 'Transposome: a toolkit for annotation of transposable element families from unassembled sequence reads', 'Staton, S Evan|Burke, John M', 'Department of Genetics and Department of Plant Biology, University of Georgia, Athens, GA 30602, USA.|Department of Genetics and Department of Plant Biology, University of Georgia, Athens, GA 30602, USA.', 'Georgia|Georgia', 11, 'DNA Transposable Elements|Genome, Plant|Genomics|High-Throughput Nucleotide Sequencing|Molecular Sequence Annotation|Sequence Analysis, DNA|Software|Zea mays', 'Journal Article', '10.1093/bioinformatics/btv059', '25644271', 'Transposable elements (TEs) can be found in virtually all eukaryotic genomes and have the potential to produce evolutionary novelty. Despite the broad taxonomic distribution of TEs, the evolutionary history of these sequences is largely unknown for many taxa due to a lack of genomic resources and identification methods. Given that most TE annotation methods are designed to work on genome assemblies, we sought to develop a method to provide a fine-grained classification of TEs from DNA sequence reads. Here, we present a toolkit for the efficient annotation of TE families from low-coverage whole-genome shotgun (WGS) data, enabling the rapid identification of TEs in a large number of taxa. We compared our software, Transposome, with other approaches for annotating repeats from WGS data, and we show that it offers significant improvements in run time and produces more precise estimates of genomic repeat abundance. Transposome may also be used as a general toolkit for working with Next Generation Sequencing (NGS) data, and for constructing custom genome analysis pipelines.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(79033, 2015, 'bio', 'Message from the ISCB: ISCB Ebola award for important future research on the computational biology of Ebola virus', 'Karp, Peter D|Berger, Bonnie|Kovats, Diane|Lengauer, Thomas|Linial, Michal|Sabeti, Pardis|Hide, Winston|Rost, Burkhard', 'International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA.|International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA.|International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA.|International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA.|International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA.|International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department o|International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA.|International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany, Hebrew University & Institute of Advanced Studies, Jerusalem, Israel, Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA, Department of Immunology and Infectious Disease, Harvard School of Public Health, Cambridge, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, USA, Sheffield Institute for Translational Neuroscience, Harvard School of Public Health, Boston, MA, USA, Department of Informatics, Bioinformatics & Computational Biology, TUM, Munich, Germany and Department of Biochemistry & Molecular Biophysics, Columbia University, New York, NY, USA International Society for Computational Biology, La Jolla, CA, USA, SRI International, Menlo Park, CA, USA, Department o', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Awards and Prizes|Biomedical Research|Computational Biology|Databases, Factual|Ebolavirus|Hemorrhagic Fever, Ebola|Humans|International Agencies|Societies, Scientific', 'Journal Article', '10.1093/bioinformatics/btv019', '25644272', 'Speed is of the essence in combating Ebola, thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains and three-dimensional protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology 2016, Orlando, FL).'),
(79034, 2015, 'bio', 'GenoMetric Query Language: a novel approach to large-scale genomic data management', 'Masseroli, Marco|Pinoli, Pietro|Venco, Francesco|Kaitoua, Abdulrahman|Jalili, Vahid|Palluzzi, Fernando|Muller, Heiko|Ceri, Stefano', 'Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan and Center for Genomic Science of IIT@SEMM, Istituto Italiano di Tecnologia (IIT), 20139 Milan, Italy.|Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan and Center for Genomic Science of IIT@SEMM, Istituto Italiano di Tecnologia (IIT), 20139 Milan, Italy.|Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan and Center for Genomic Science of IIT@SEMM, Istituto Italiano di Tecnologia (IIT), 20139 Milan, Italy.|Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan and Center for Genomic Science of IIT@SEMM, Istituto Italiano di Tecnologia (IIT), 20139 Milan, Italy.|Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan and Center for Genomic Science of IIT@SEMM, Istituto Italiano di Tecnologia (IIT), 20139 Milan, Italy.|Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan and Center for Genomic Science of IIT@SEMM, Istituto Italiano di Tecnologia (IIT), 20139 Milan, Italy.|Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan and Center for Genomic Science of IIT@SEMM, Istituto Italiano di Tecnologia (IIT), 20139 Milan, Italy.|Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan and Center for Genomic Science of IIT@SEMM, Istituto Italiano di Tecnologia (IIT), 20139 Milan, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 54, 'Abstracting and Indexing as Topic|Chromatin Immunoprecipitation|Computational Biology|Databases, Factual|Epigenomics|Genomics|High-Throughput Screening Assays|Histones|Humans|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btv048', '25649616', 'Improvement of sequencing technologies and data processing pipelines is rapidly providing sequencing data, with associated high-level features, of many individual genomes in multiple biological and clinical conditions. They allow for data-driven genomic, transcriptomic and epigenomic characterizations, but require state-of-the-art big data computing strategies, with abstraction levels beyond available tool capabilities.'),
(79035, 2015, 'bio', 'Analysis of nanopore data using hidden Markov models', 'Schreiber, Jacob|Karplus, Kevin', 'Nanopore Group, Department of Biomolecular Engineering, University of California Santa Cruz, CA 95064, USA.|Nanopore Group, Department of Biomolecular Engineering, University of California Santa Cruz, CA 95064, USA.', 'United States|United States', 0, '5-Methylcytosine|Algorithms|Cytosine|DNA Methylation|Epigenomics|High-Throughput Nucleotide Sequencing|Humans|Markov Chains|Nanopores|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btv046', '25649617', 'Nanopore-based sequencing techniques can reconstruct properties of biosequences by analyzing the sequence-dependent ionic current steps produced as biomolecules pass through a pore. Typically this involves alignment of new data to a reference, where both reference construction and alignment have been performed by hand.'),
(79036, 2015, 'bio', 'PolyMarker: A fast polyploid primer design pipeline', 'Ramirez-Gonzalez, Ricardo H|Uauy, Cristobal|Caccamo, Mario', 'The Genome Analysis Centre (TGAC), Norwich Research Park, Norwich NR4 7UH, UK, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK and National Institute of Agricultural Botany (NIAB), Cambridge CB3 0LE, UK.|The Genome Analysis Centre (TGAC), Norwich Research Park, Norwich NR4 7UH, UK, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK and National Institute of Agricultural Botany (NIAB), Cambridge CB3 0LE, UK The Genome Analysis Centre (TGAC), Norwich Research Park, Norwich NR4 7UH, UK, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK and National Institute of Agricultural Botany (NIAB), Cambridge CB3 0LE, UK.|The Genome Analysis Centre (TGAC), Norwich Research Park, Norwich NR4 7UH, UK, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK and National Institute of Agricultural Botany (NIAB), Cambridge CB3 0LE, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'DNA Primers|Genetic Markers|Polymorphism, Single Nucleotide|Polyploidy|Sequence Analysis, DNA|Software|Triticum', 'Journal Article', '10.1093/bioinformatics/btv069', '25649618', 'The design of genetic markers is of particular relevance in crop breeding programs. Despite many economically important crops being polyploid organisms, the current primer design tools are tailored for diploid species. Bread wheat, for instance, is a hexaploid comprising of three related genomes and the performance of genetic markers is diminished if the primers are not genome specific. PolyMarker is a pipeline that generates SNP markers by selecting candidate primers for a specified genome using local alignments and standard primer design tools to test the viability of the primers. A command line tool and a web interface are available to the community.'),
(79037, 2015, 'bio', 'mFASD: a structure-based algorithm for discriminating different types of metal-binding sites', 'He, Wei|Liang, Zhi|Teng, Maikun|Niu, Liwen', 'Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, China.|Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, China.|Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, China.|Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, China.', 'China|China|China|China', 0, 'Algorithms|Binding Sites|Computer Simulation|Discriminant Analysis|Humans|Metals|Models, Molecular|Protein Conformation|Proteins', 'Journal Article', '10.1093/bioinformatics/btv044', '25649619', 'A large number of proteins contain metal ions that are essential for their stability and biological activity. Identifying and characterizing metal-binding sites through computational methods is necessary when experimental clues are lacking. Almost all published computational methods are designed to distinguish metal-binding sites from non-metal-binding sites. However, discrimination between different types of metal-binding sites is also needed to make more accurate predictions.'),
(79038, 2015, 'bio', 'Methods for the detection and assembly of novel sequence in high-throughput sequencing data', 'Holtgrewe, Manuel|Kuchenbecker, Leon|Reinert, Knut', 'Department of Computer Science, Freie Universität Berlin and Max Planck Institute for Molecular Genetics, Berlin, Germany.|Department of Computer Science, Freie Universität Berlin and Max Planck Institute for Molecular Genetics, Berlin, Germany Department of Computer Science, Freie Universität Berlin and Max Planck Institute for Molecular Genetics, Berlin, Germany.|Department of Computer Science, Freie Universität Berlin and Max Planck Institute for Molecular Genetics, Berlin, Germany.', 'Germany|Germany|Germany', 0, 'Computational Biology|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btv051', '25649620', 'Large insertions of novel sequence are an important type of structural variants. Previous studies used traditional de novo assemblers for assembling non-mapping high-throughput sequencing (HTS) or capillary reads and then tried to anchor them in the reference using paired read information.'),
(79039, 2015, 'bio', 'Incorporating peak grouping information for alignment of multiple liquid chromatography-mass spectrometry datasets', 'Wandy, Joe|Daly, Rónán|Breitling, Rainer|Rogers, Simon', 'School of Computing Science, University of Glasgow, Glasgow, UK, School of Computing and Mathematical Sciences, Liverpool John Moores University, Merseyside, UK and Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, University of Manchester, Manchester, UK.|School of Computing Science, University of Glasgow, Glasgow, UK, School of Computing and Mathematical Sciences, Liverpool John Moores University, Merseyside, UK and Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, University of Manchester, Manchester, UK.|School of Computing Science, University of Glasgow, Glasgow, UK, School of Computing and Mathematical Sciences, Liverpool John Moores University, Merseyside, UK and Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, University of Manchester, Manchester, UK.|School of Computing Science, University of Glasgow, Glasgow, UK, School of Computing and Mathematical Sciences, Liverpool John Moores University, Merseyside, UK and Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, University of Manchester, Manchester, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Chromatography, Liquid|Glycomics|Humans|Mass Spectrometry|Metabolomics|Peptide Fragments|Proteomics', 'Journal Article', '10.1093/bioinformatics/btv072', '25649621', 'The combination of liquid chromatography and mass spectrometry (LC/MS) has been widely used for large-scale comparative studies in systems biology, including proteomics, glycomics and metabolomics. In almost all experimental design, it is necessary to compare chromatograms across biological or technical replicates and across sample groups. Central to this is the peak alignment step, which is one of the most important but challenging preprocessing steps. Existing alignment tools do not take into account the structural dependencies between related peaks that coelute and are derived from the same metabolite or peptide. We propose a direct matching peak alignment method for LC/MS data that incorporates related peaks information (within each LC/MS run) and investigate its effect on alignment performance (across runs). The groupings of related peaks necessary for our method can be obtained from any peak clustering method and are built into a pair-wise peak similarity score function. The similarity score matrix produced is used by an approximation algorithm for the weighted matching problem to produce the actual alignment result.'),
(79040, 2015, 'bio', 'Reference-based compression of short-read sequences using path encoding', 'Kingsford, Carl|Patro, Rob', 'Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA and Department of Computer Science, Stony Brook University, Stony Brook, NY 11794-4400, USA.|Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA and Department of Computer Science, Stony Brook University, Stony Brook, NY 11794-4400, USA.', 'United States|United States', 23, 'Algorithms|Animals|Computational Biology|Data Compression|Genomics|High-Throughput Nucleotide Sequencing|Humans|Mice|Programming Languages|Pseudomonas aeruginosa|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btv071', '25649622', 'Storing, transmitting and archiving data produced by next-generation sequencing is a significant computational burden. New compression techniques tailored to short-read sequence data are needed.'),
(79041, 2015, 'bio', 'PANNZER: high-throughput functional annotation of uncharacterized proteins in an error-prone environment', 'Koskinen, Patrik|Törönen, Petri|Nokso-Koivisto, Jussi|Holm, Liisa', 'Department of Biosciences, University of Helsinki, 00014 Helsinki, Finland and Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland.|Department of Biosciences, University of Helsinki, 00014 Helsinki, Finland and Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland.|Department of Biosciences, University of Helsinki, 00014 Helsinki, Finland and Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland.|Department of Biosciences, University of Helsinki, 00014 Helsinki, Finland and Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland Department of Biosciences, University of Helsinki, 00014 Helsinki, Finland and Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland.', 'Finland|Finland|Finland|Finland', 0, 'Cluster Analysis|Computational Biology|Data Interpretation, Statistical|Data Mining|Databases, Genetic|Databases, Protein|Gene Ontology|Humans|Molecular Sequence Annotation|Proteins|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btu851', '25653249', 'The last decade has seen a remarkable growth in protein databases. This growth comes at a price: a growing number of submitted protein sequences lack functional annotation. Approximately 32% of sequences submitted to the most comprehensive protein database UniProtKB are labelled as Unknown protein or alike. Also the functionally annotated parts are reported to contain 30-40% of errors. Here, we introduce a high-throughput tool for more reliable functional annotation called Protein ANNotation with Z-score (PANNZER). PANNZER predicts Gene Ontology (GO) classes and free text descriptions about protein functionality. PANNZER uses weighted k-nearest neighbour methods with statistical testing to maximize the reliability of a functional annotation.'),
(79042, 2015, 'bio', 'Evolutionary profiles improve protein-protein interaction prediction from sequence', 'Hamp, Tobias|Rost, Burkhard', 'Department of Informatics, Bioinformatics & Computational Biology, TUM (Technische Universität München)-I12, Boltzmannstr. 3, 85748 Garching/Munich, Germany.|Department of Informatics, Bioinformatics & Computational Biology, TUM (Technische Universität München)-I12, Boltzmannstr. 3, 85748 Garching/Munich, Germany.', 'Germany|Germany', 0, 'Computational Biology|Humans|Models, Molecular|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Proteins|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btv077', '25657331', 'Many methods predict the physical interaction between two proteins (protein-protein interactions, PPIs) from sequence alone. Their performance drops substantially for proteins not used for training.'),
(79043, 2015, 'bio', 'Application of clinical text data for phenome-wide association studies (PheWASs)', 'Hebbring, Scott J|Rastegar-Mojarad, Majid|Ye, Zhan|Mayer, John|Jacobson, Crystal|Lin, Simon', 'Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA and Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA.|Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA and Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA.|Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA and Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA.|Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA and Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA.|Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA and Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA.|Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA and Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA.', 'United States|United States|United States|United States|United States|United States', 23, 'Computational Biology|Disease|Genetic Predisposition to Disease|Genome-Wide Association Study|Genotype|Humans|Phenotype|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btv076', '25657332', 'Genome-wide association studies (GWASs) are effective for describing genetic complexities of common diseases. Phenome-wide association studies (PheWASs) offer an alternative and complementary approach to GWAS using data embedded in the electronic health record (EHR) to define the phenome. International Classification of Disease version 9 (ICD9) codes are used frequently to define the phenome, but using ICD9 codes alone misses other clinically relevant information from the EHR that can be used for PheWAS analyses and discovery.'),
(79044, 2015, 'bio', 'Whiteboard: a framework for the programmatic visualization of complex biological analyses', 'Sundström, Görel|Zamani, Neda|Grabherr, Manfred G|Mauceli, Evan', 'Department of Medical Biochemistry and Microbiology, Bioinformatics Infrastructure for Life Sciences, Uppsala University, 75123 Uppsala, Sweden, Department of Plant Physiology, Umeå University, 901 87 Umeå, Sweden and Parabase Genomics, 27 Drydock Avenue, Boston MA 02210, USA.|Department of Medical Biochemistry and Microbiology, Bioinformatics Infrastructure for Life Sciences, Uppsala University, 75123 Uppsala, Sweden, Department of Plant Physiology, Umeå University, 901 87 Umeå, Sweden and Parabase Genomics, 27 Drydock Avenue, Boston MA 02210, USA Department of Medical Biochemistry and Microbiology, Bioinformatics Infrastructure for Life Sciences, Uppsala University, 75123 Uppsala, Sweden, Department of Plant Physiology, Umeå University, 901 87 Umeå, Sweden and Parabase Genomics, 27 Drydock Avenue, Boston MA 02210, USA.|Department of Medical Biochemistry and Microbiology, Bioinformatics Infrastructure for Life Sciences, Uppsala University, 75123 Uppsala, Sweden, Department of Plant Physiology, Umeå University, 901 87 Umeå, Sweden and Parabase Genomics, 27 Drydock Avenue, Boston MA 02210, USA.|Department of Medical Biochemistry and Microbiology, Bioinformatics Infrastructure for Life Sciences, Uppsala University, 75123 Uppsala, Sweden, Department of Plant Physiology, Umeå University, 901 87 Umeå, Sweden and Parabase Genomics, 27 Drydock Avenue, Boston MA 02210, USA.', 'Sweden|Sweden|Sweden|Sweden', 0, 'Computational Biology|Computer Graphics|Databases, Factual|Humans|Information Storage and Retrieval|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btv078', '25661541', 'Whiteboard is a class library implemented in C++ that enables visualization to be tightly coupled with computation when analyzing large and complex datasets.'),
(79045, 2015, 'bio', 'NxTrim: optimized trimming of Illumina mate pair reads', 'OConnell, Jared|Schulz-Trieglaff, Ole|Carlson, Emma|Hims, Matthew M|Gormley, Niall A|Cox, Anthony J', 'Computational Biology Group and Technology Development, Illumina Cambridge Ltd., Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK.|Computational Biology Group and Technology Development, Illumina Cambridge Ltd., Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK.|Computational Biology Group and Technology Development, Illumina Cambridge Ltd., Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK.|Computational Biology Group and Technology Development, Illumina Cambridge Ltd., Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK.|Computational Biology Group and Technology Development, Illumina Cambridge Ltd., Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK.|Computational Biology Group and Technology Development, Illumina Cambridge Ltd., Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Bacteria|Computational Biology|Gene Library|Genome, Bacterial|High-Throughput Nucleotide Sequencing|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btv057', '25661542', 'Mate pair protocols add to the utility of paired-end sequencing by boosting the genomic distance spanned by each pair of reads, potentially allowing larger repeats to be bridged and resolved. The Illumina Nextera Mate Pair (NMP) protocol uses a circularization-based strategy that leaves behind 38-bp adapter sequences, which must be computationally removed from the data. While adapter trimming is a well-studied area of bioinformatics, existing tools do not fully exploit the particular properties of NMP data and discard more data than is necessary.'),
(79046, 2015, 'bio', 'Large-scale exploration and analysis of drug combinations', 'Li, Peng|Huang, Chao|Fu, Yingxue|Wang, Jinan|Wu, Ziyin|Ru, Jinlong|Zheng, Chunli|Guo, Zihu|Chen, Xuetong|Zhou, Wei|Zhang, Wenjuan|Li, Yan|Chen, Jianxin|Lu, Aiping|Wang, Yonghua', 'Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.', 'China|China|China|China|China|China|China|China|China|China|China|China|China|China|China', 0, 'Algorithms|Bayes Theorem|Computational Biology|Databases, Pharmaceutical|Drug Combinations|Drug Interactions|Drug Synergism|Drug-Related Side Effects and Adverse Reactions|Humans|Models, Theoretical|Probability', 'Journal Article', '10.1093/bioinformatics/btv080', '25667546', 'Drug combinations are a promising strategy for combating complex diseases by improving the efficacy and reducing corresponding side effects. Currently, a widely studied problem in pharmacology is to predict effective drug combinations, either through empirically screening in clinic or pure experimental trials. However, the large-scale prediction of drug combination by a systems method is rarely considered.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(79047, 2015, 'bio', 'FUN-L: gene prioritization for RNAi screens', 'Lees, Jonathan G|Hériché, Jean-Karim|Morilla, Ian|Fernández, José M|Adler, Priit|Krallinger, Martin|Vilo, Jaak|Valencia, Alfonso|Ellenberg, Jan|Ranea, Juan A|Orengo, Christine', 'Research Department of Structural & Molecular Biology, University College London, London, UK, Cell Biology/Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, Inflamex-Laboratoire Analyse Géométrie et Applications, Université Paris Nord-Sorbonne, France, Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO) and Spanish National Bioinformatics Institute (INB), Madrid, Spain, Institute of Molecular and Cell Biology, and Institute of Computer Science, University of Tartu, Tartu, Estonia and Department of Molecular Biology and Biochemistry-CIBER de Enfermedades Raras, University of Malaga, Malaga, Spain.|Research Department of Structural & Molecular Biology, University College London, London, UK, Cell Biology/Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, Inflamex-Laboratoire Analyse Géométrie et Applications, Université Paris Nord-Sorbonne, France, Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO) and Spanish National Bioinformatics Institute (INB), Madrid, Spain, Institute of Molecular and Cell Biology, and Institute of Computer Science, University of Tartu, Tartu, Estonia and Department of Molecular Biology and Biochemistry-CIBER de Enfermedades Raras, University of Malaga, Malaga, Spain.|Research Department of Structural & Molecular Biology, University College London, London, UK, Cell Biology/Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, Inflamex-Laboratoire Analyse Géométrie et Applications, Université Paris Nord-Sorbonne, France, Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO) and Spanish National Bioinformatics Institute (INB), Madrid, Spain, Institute of Molecular and Cell Biology, and Institute of Computer Science, University of Tartu, Tartu, Estonia and Department of Molecular Biology and Biochemistry-CIBER de Enfermedades Raras, University of Malaga, Malaga, Spain.|Research Department of Structural & Molecular Biology, University College London, London, UK, Cell Biology/Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, Inflamex-Laboratoire Analyse Géométrie et Applications, Université Paris Nord-Sorbonne, France, Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO) and Spanish National Bioinformatics Institute (INB), Madrid, Spain, Institute of Molecular and Cell Biology, and Institute of Computer Science, University of Tartu, Tartu, Estonia and Department of Molecular Biology and Biochemistry-CIBER de Enfermedades Raras, University of Malaga, Malaga, Spain.|Research Department of Structural & Molecular Biology, University College London, London, UK, Cell Biology/Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, Inflamex-Laboratoire Analyse Géométrie et Applications, Université Paris Nord-Sorbonne, France, Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO) and Spanish National Bioinformatics Institute (INB), Madrid, Spain, Institute of Molecular and Cell Biology, and Institute of Computer Science, University of Tartu, Tartu, Estonia and Department of Molecular Biology and Biochemistry-CIBER de Enfermedades Raras, University of Malaga, Malaga, Spain.|Research Department of Structural & Molecular Biology, University College London, London, UK, Cell Biology/Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, Inflamex-Laboratoire Analyse Géométrie et Applications, Université Paris Nord-Sorbonne, France, Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO) and Spanish National Bioinformatics Institute (INB), Madrid, Spain, Institute of Molecular and Cell Biology, and Institute of Computer Science, University of Tartu, Tartu, Estonia and Department of Molecular Biology and Biochemistry-CIBER de Enfermedades Raras, University of Malaga, Malaga, Spain.|Research Department of Structural & Molecular Biology, University College London, London, UK, Cell Biology/Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, Inflamex-Laboratoire Analyse Géométrie et Applications, Université Paris Nord-Sorbonne, France, Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO) and Spanish National Bioinformatics Institute (INB), Madrid, Spain, Institute of Molecular and Cell Biology, and Institute of Computer Science, University of Tartu, Tartu, Estonia and Department of Molecular Biology and Biochemistry-CIBER de Enfermedades Raras, University of Malaga, Malaga, Spain.|Research Department of Structural & Molecular Biology, University College London, London, UK, Cell Biology/Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, Inflamex-Laboratoire Analyse Géométrie et Applications, Université Paris Nord-Sorbonne, France, Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO) and Spanish National Bioinformatics Institute (INB), Madrid, Spain, Institute of Molecular and Cell Biology, and Institute of Computer Science, University of Tartu, Tartu, Estonia and Department of Molecular Biology and Biochemistry-CIBER de Enfermedades Raras, University of Malaga, Malaga, Spain.|Research Department of Structural & Molecular Biology, University College London, London, UK, Cell Biology/Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, Inflamex-Laboratoire Analyse Géométrie et Applications, Université Paris Nord-Sorbonne, France, Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO) and Spanish National Bioinformatics Institute (INB), Madrid, Spain, Institute of Molecular and Cell Biology, and Institute of Computer Science, University of Tartu, Tartu, Estonia and Department of Molecular Biology and Biochemistry-CIBER de Enfermedades Raras, University of Malaga, Malaga, Spain.|Research Department of Structural & Molecular Biology, University College London, London, UK, Cell Biology/Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, Inflamex-Laboratoire Analyse Géométrie et Applications, Université Paris Nord-Sorbonne, France, Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO) and Spanish National Bioinformatics Institute (INB), Madrid, Spain, Institute of Molecular and Cell Biology, and Institute of Computer Science, University of Tartu, Tartu, Estonia and Department of Molecular Biology and Biochemistry-CIBER de Enfermedades Raras, University of Malaga, Malaga, Spain.|Research Department of Structural & Molecular Biology, University College London, London, UK, Cell Biology/Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, Inflamex-Laboratoire Analyse Géométrie et Applications, Université Paris Nord-Sorbonne, France, Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO) and Spanish National Bioinformatics Institute (INB), Madrid, Spain, Institute of Molecular and Cell Biology, and Institute of Computer Science, University of Tartu, Tartu, Estonia and Department of Molecular Biology and Biochemistry-CIBER de Enfermedades Raras, University of Malaga, Malaga, Spain.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 6, 'Algorithms|Computational Biology|Data Mining|Gene Regulatory Networks|Humans|Phenotype|RNA Interference|Software', 'Journal Article', '10.1093/bioinformatics/btv073', '25667547', 'Most biological processes remain only partially characterized with many components still to be identified. Given that a whole genome can usually not be tested in a functional assay, identifying the genes most likely to be of interest is of critical importance to avoid wasting resources.'),
(79048, 2015, 'bio', 'A multiobjective memetic algorithm for PPI network alignment', 'Clark, Connor|Kalita, Jugal', 'Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.', 'United States|United States', 30, 'Algorithms|Computational Biology|Humans|Protein Interaction Mapping|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btv063', '25667548', 'There recently has been great interest in aligning protein-protein interaction (PPI) networks to identify potentially orthologous proteins between species. It is thought that the topological information contained in these networks will yield better orthology predictions than sequence similarity alone. Recent work has found that existing aligners have difficulty making use of both topological and sequence similarity when aligning, with either one or the other being better matched. This can be at least partially attributed to the fact that existing aligners try to combine these two potentially conflicting objectives into a single objective.'),
(79049, 2015, 'bio', 'BioTextQuest+: a knowledge integration platform for literature mining and concept discovery', 'Papanikolaou, Nikolas|Pavlopoulos, Georgios A|Pafilis, Evangelos|Theodosiou, Theodosios|Schneider, Reinhard|Satagopam, Venkata P|Ouzounis, Christos A|Eliopoulos, Aristides G|Promponas, Vasilis J|Iliopoulos, Ioannis', 'Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 1, '-', 'Published Erratum', '10.1093/bioinformatics/btv029', '25673338', '-'),
(79050, 2015, 'bio', 'Detecting differential peaks in ChIP-seq signals with ODIN', 'Allhoff, Manuel|Seré, Kristin|Chauvistré, Heike|Lin, Qiong|Zenke, Martin|Costa, Ivan G', 'Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.|Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.', 'United States|United States|United States|United States|United States|United States', 0, '-', 'Published Erratum', '10.1093/bioinformatics/btv030', '25673339', '-'),
(79051, 2015, 'bio', 'MESMER: minimal ensemble solutions to multiple experimental restraints', 'Ihms, Elihu C|Foster, Mark P', 'Ohio State University Biophysics Program, Department of Chemistry and Biochemistry, and Center for RNA Biology, The Ohio State University, Columbus, OH, USA Ohio State University Biophysics Program, Department of Chemistry and Biochemistry, and Center for RNA Biology, The Ohio State University, Columbus, OH, USA.|Ohio State University Biophysics Program, Department of Chemistry and Biochemistry, and Center for RNA Biology, The Ohio State University, Columbus, OH, USA Ohio State University Biophysics Program, Department of Chemistry and Biochemistry, and Center for RNA Biology, The Ohio State University, Columbus, OH, USA Ohio State University Biophysics Program, Department of Chemistry and Biochemistry, and Center for RNA Biology, The Ohio State University, Columbus, OH, USA.', 'United States|United States', 3, 'Acid Phosphatase|Calmodulin|Computational Biology|Computer Simulation|Endosomal Sorting Complexes Required for Transport|Humans|Isoenzymes|Models, Molecular|Multiprotein Complexes|Nuclear Magnetic Resonance, Biomolecular|Protein Conformation|Scattering, Small Angle|Software|Tartrate-Resistant Acid Phosphatase', 'Journal Article', '10.1093/bioinformatics/btv079', '25673340', 'Macromolecular structures and interactions are intrinsically heterogeneous, temporally adopting a range of configurations that can confound the analysis of data from bulk experiments. To obtain quantitative insights into heterogeneous systems, an ensemble-based approach can be employed, in which predicted data computed from a collection of models is compared to the observed experimental results. By simultaneously fitting orthogonal structural data (e.g. small-angle X-ray scattering, nuclear magnetic resonance residual dipolar couplings, dipolar electron-electron resonance spectra), the range and population of accessible macromolecule structures can be probed.'),
(79052, 2015, 'bio', 'DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis', 'Yu, Guangchuang|Wang, Li-Gen|Yan, Guang-Rong|He, Qing-Yu', 'State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, College of Life Science and Technology, Jinan University, Guangzhou 510632 and Guangdong Information Center, Guangzhou 510031, China State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, College of Life Science and Technology, Jinan University, Guangzhou 510632 and Guangdong Information Center, Guangzhou 510031, China.|State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, College of Life Science and Technology, Jinan University, Guangzhou 510632 and Guangdong Information Center, Guangzhou 510031, China.|State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, College of Life Science and Technology, Jinan University, Guangzhou 510632 and Guangdong Information Center, Guangzhou 510031, China.|State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, College of Life Science and Technology, Jinan University, Guangzhou 510632 and Guangdong Information Center, Guangzhou 510031, China.', 'China|China|China|China', 166, 'Computational Biology|Databases, Genetic|Disease|Gene Ontology|Humans|Multigene Family|Programming Languages|Semantics|Software', 'Journal Article', '10.1093/bioinformatics/btu684', '25677125', 'Disease ontology (DO) annotates human genes in the context of disease. DO is important annotation in translating molecular findings from high-throughput data to clinical relevance. DOSE is an R package providing semantic similarity computations among DO terms and genes which allows biologists to explore the similarities of diseases and of gene functions in disease perspective. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented to support discovering disease associations of high-throughput biological data. This allows biologists to verify disease relevance in a biological experiment and identify unexpected disease associations. Comparison among gene clusters is also supported.'),
(79053, 2015, 'bio', 'MOST: a software environment for constraint-based metabolic modeling and strain design', 'Kelley, James J|Lane, Anatoliy|Li, Xiaowei|Mutthoju, Brahmaji|Maor, Shay|Egen, Dennis|Lun, Desmond S', 'Center for Computational and Integrative Biology and Department of Computer Science, Rutgers University, Camden, NJ 08102, USA and Phenomics and Bioinformatics Research Centre and School of Mathematics and Statistics, University of South Australia, Mawson Lakes, SA 5095, Australia.|Center for Computational and Integrative Biology and Department of Computer Science, Rutgers University, Camden, NJ 08102, USA and Phenomics and Bioinformatics Research Centre and School of Mathematics and Statistics, University of South Australia, Mawson Lakes, SA 5095, Australia.|Center for Computational and Integrative Biology and Department of Computer Science, Rutgers University, Camden, NJ 08102, USA and Phenomics and Bioinformatics Research Centre and School of Mathematics and Statistics, University of South Australia, Mawson Lakes, SA 5095, Australia.|Center for Computational and Integrative Biology and Department of Computer Science, Rutgers University, Camden, NJ 08102, USA and Phenomics and Bioinformatics Research Centre and School of Mathematics and Statistics, University of South Australia, Mawson Lakes, SA 5095, Australia.|Center for Computational and Integrative Biology and Department of Computer Science, Rutgers University, Camden, NJ 08102, USA and Phenomics and Bioinformatics Research Centre and School of Mathematics and Statistics, University of South Australia, Mawson Lakes, SA 5095, Australia.|Center for Computational and Integrative Biology and Department of Computer Science, Rutgers University, Camden, NJ 08102, USA and Phenomics and Bioinformatics Research Centre and School of Mathematics and Statistics, University of South Australia, Mawson Lakes, SA 5095, Australia.|Center for Computational and Integrative Biology and Department of Computer Science, Rutgers University, Camden, NJ 08102, USA and Phenomics and Bioinformatics Research Centre and School of Mathematics and Statistics, University of South Australia, Mawson Lakes, SA 5095, Australia Center for Computational and Integrative Biology and Department of Computer Science, Rutgers University, Camden, NJ 08102, USA and Phenomics and Bioinformatics Research Centre and School of Mathematics and Statistics, University of South Australia, Mawson Lakes, SA 5095, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia', 6, 'Algorithms|Animals|Computational Biology|Gene Knockout Techniques|Metabolic Flux Analysis|Metabolic Networks and Pathways|Models, Biological|Software', 'Journal Article', '10.1093/bioinformatics/btu685', '25677126', 'MOST (metabolic optimization and simulation tool) is a software package that implements GDBB (genetic design through branch and bound) in an intuitive user-friendly interface with excel-like editing functionality, as well as implementing FBA (flux balance analysis), and supporting systems biology markup language and comma-separated values files. GDBB is currently the fastest algorithm for finding gene knockouts predicted by FBA to increase production of desired products, but GDBB has only been available on a command line interface, which is difficult to use for those without programming knowledge, until the release of MOST.'),
(79054, 2015, 'bio', 'A trimming-and-retrieving alignment scheme for reduced representation bisulfite sequencing', 'Wang, Xuefeng|Yu, Xiaoqing|Zhu, Wei|McCombie, W Richard|Antoniou, Eric|Powers, R Scott|Davidson, Nicholas O|Li, Ellen|Williams, Jennie', 'Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.|Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.|Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.|Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.|Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.|Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.|Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.|Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.|Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 2, 'DNA Methylation|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Software|Sulfites', 'Journal Article', '10.1093/bioinformatics/btv089', '25681254', 'Currently available bisulfite sequencing tools frequently suffer from low mapping rates and low methylation calls, especially for data generated from the Illumina sequencer, NextSeq. Here, we introduce a sequential trimming-and-retrieving alignment approach for investigating DNA methylation patterns, which significantly improves the number of mapped reads and covered CpG sites. The method is implemented in an automated analysis toolkit for processing bisulfite sequencing reads.'),
(79055, 2015, 'bio', 'Mobility-based prediction of hydration structures of protein surfaces', 'Jeszenxc5x91i, Norbert|Horvxc3xa1th, Istvxc3xa1n|Bxc3xa1lint, Mxc3xb3nika|van der Spoel, David|Hetxc3xa9nyi, Csaba', 'Department of Genetics, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Pxc3xa1zmxc3xa1ny Pxc3xa9ter sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Chemistry Doctoral School, University of Szeged, Dugonics txc3xa9r 13, 6720 Szeged, Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Pxc3xa1zmxc3xa1ny Pxc3xa9ter sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Hungary, Uppsala Center for Computational Chemistry, Science for Life Laboratory, Department of Cell and Molecular Biology, University of Uppsala, Box 596, SE-75124 Uppsala, Sweden, and MTA-ELTE Molecular Biophysics Research Group, Hungarian Academy of Sciences, Pxc3xa1zmxc3xa1ny sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Hungary.|Department of Genetics, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Pxc3xa1zmxc3xa1ny Pxc3xa9ter sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Chemistry Doctoral School, University of Szeged, Dugonics txc3xa9r 13, 6720 Szeged, Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Pxc3xa1zmxc3xa1ny Pxc3xa9ter sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Hungary, Uppsala Center for Computational Chemistry, Science for Life Laboratory, Department of Cell and Molecular Biology, University of Uppsala, Box 596, SE-75124 Uppsala, Sweden, and MTA-ELTE Molecular Biophysics Research Group, Hungarian Academy of Sciences, Pxc3xa1zmxc3xa1ny sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Hungary.|Department of Genetics, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Pxc3xa1zmxc3xa1ny Pxc3xa9ter sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Chemistry Doctoral School, University of Szeged, Dugonics txc3xa9r 13, 6720 Szeged, Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Pxc3xa1zmxc3xa1ny Pxc3xa9ter sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Hungary, Uppsala Center for Computational Chemistry, Science for Life Laboratory, Department of Cell and Molecular Biology, University of Uppsala, Box 596, SE-75124 Uppsala, Sweden, and MTA-ELTE Molecular Biophysics Research Group, Hungarian Academy of Sciences, Pxc3xa1zmxc3xa1ny sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Hungary.|Department of Genetics, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Pxc3xa1zmxc3xa1ny Pxc3xa9ter sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Chemistry Doctoral School, University of Szeged, Dugonics txc3xa9r 13, 6720 Szeged, Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Pxc3xa1zmxc3xa1ny Pxc3xa9ter sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Hungary, Uppsala Center for Computational Chemistry, Science for Life Laboratory, Department of Cell and Molecular Biology, University of Uppsala, Box 596, SE-75124 Uppsala, Sweden, and MTA-ELTE Molecular Biophysics Research Group, Hungarian Academy of Sciences, Pxc3xa1zmxc3xa1ny sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Hungary.|Department of Genetics, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Pxc3xa1zmxc3xa1ny Pxc3xa9ter sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Chemistry Doctoral School, University of Szeged, Dugonics txc3xa9r 13, 6720 Szeged, Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Pxc3xa1zmxc3xa1ny Pxc3xa9ter sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Hungary, Uppsala Center for Computational Chemistry, Science for Life Laboratory, Department of Cell and Molecular Biology, University of Uppsala, Box 596, SE-75124 Uppsala, Sweden, and MTA-ELTE Molecular Biophysics Research Group, Hungarian Academy of Sciences, Pxc3xa1zmxc3xa1ny sxc3xa9txc3xa1ny 1/C, 1117 Budapest, Hungary.', 'Hungary|Hungary|Hungary|Hungary|Hungary', 16, 'Algorithms|Crystallography, X-Ray|Cyclin-Dependent Kinase 2|Humans|Molecular Dynamics Simulation|Protein Conformation|Water', 'Journal Article', '10.1093/bioinformatics/btv093', '25682067', 'Hydration largely determines solubility, aggregation of proteins and influences interactions between proteins and drug molecules. Despite the importance of hydration, structural determination of hydration structure of protein surfaces is still challenging from both experimental and theoretical viewpoints. The precision of experimental measurements is often affected by fluctuations and mobility of water molecules resulting in uncertain assignment of water positions.'),
(79056, 2015, 'bio', 'A novel statistical method for quantitative comparison of multiple ChIP-seq datasets', 'Chen, Li|Wang, Chi|Qin, Zhaohui S|Wu, Hao', 'Department of Mathematics and Computer Science, Atlanta, GA 30322, USA, Department of Biostatistics and Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA, Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA and Department of Biomedical Informatics, Emory University, Atlanta, GA 30322, USA.|Department of Mathematics and Computer Science, Atlanta, GA 30322, USA, Department of Biostatistics and Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA, Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA and Department of Biomedical Informatics, Emory University, Atlanta, GA 30322, USA.|Department of Mathematics and Computer Science, Atlanta, GA 30322, USA, Department of Biostatistics and Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA, Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA and Department of Biomedical Informatics, Emory University, Atlanta, GA 30322, USA Department of Mathematics and Computer Science, Atlanta, GA 30322, USA, Department of Biostatistics and Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA, Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA and Department of Biomedical Informatics, Emory University, Atlanta, GA 30322, USA.|Department of Mathematics and Computer Science, Atlanta, GA 30322, USA, Department of Biostatistics and Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA, Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA and Department of Biomedical Informatics, Emory University, Atlanta, GA 30322, USA.', 'United States|United States|United States|United States', 19, 'Algorithms|Artifacts|Chromatin Immunoprecipitation|Computational Biology|Computer Simulation|Datasets as Topic|Genome, Human|High-Throughput Nucleotide Sequencing|Histones|Humans|Models, Statistical|Poisson Distribution|Protein Binding|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btv094', '25682068', 'ChIP-seq is a powerful technology to measure the protein binding or histone modification strength in the whole genome scale. Although there are a number of methods available for single ChIP-seq data analysis (e.g. peak detection), rigorous statistical method for quantitative comparison of multiple ChIP-seq datasets with the considerations of data from control experiment, signal to noise ratios, biological variations and multiple-factor experimental designs is under-developed.'),
(79057, 2015, 'bio', 'A cautionary note on using binary calls for analysis of DNA methylation', 'Prochenka, Agnieszka|Pokarowski, Piotr|Gasperowicz, Piotr|Kosixc5x84ska, Joanna|Stawixc5x84ski, Piotr|Zbiexc4x87-Piekarska, Renata|Spxc3xb3lnicka, Magdalena|Branicki, Wojciech|Pxc5x82oski, Rafaxc5x82', 'Institute of Computer Science, Polish Academy of Sciences, Jana Kazimierza 5, Warsaw, Poland, Department of Medical Genetics, Medical University of Warsaw, Pawixc5x84skiego 3c, Warsaw, Poland, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw, Poland, Department of Immunology, Center for Biostructure Research, Medical University of Warsaw, Banacha 2, Warsaw, Poland, Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, Warsaw, Poland and Institute of Forensic Research, Westerplatte 9, Krakow, Poland Institute of Computer Science, Polish Academy of Sciences, Jana Kazimierza 5, Warsaw, Poland, Department of Medical Genetics, Medical University of Warsaw, Pawixc5x84skiego 3c, Warsaw, Poland, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw, Poland, Department of Immunology, Center for Biostructure Research, Medical University of Warsaw, Banacha 2, Warsaw, Poland, Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, Warsaw, Poland and Institute of Forensic Research, Westerplatte 9, Krakow, Poland.|Institute of Computer Science, Polish Academy of Sciences, Jana Kazimierza 5, Warsaw, Poland, Department of Medical Genetics, Medical University of Warsaw, Pawixc5x84skiego 3c, Warsaw, Poland, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw, Poland, Department of Immunology, Center for Biostructure Research, Medical University of Warsaw, Banacha 2, Warsaw, Poland, Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, Warsaw, Poland and Institute of Forensic Research, Westerplatte 9, Krakow, Poland.|Institute of Computer Science, Polish Academy of Sciences, Jana Kazimierza 5, Warsaw, Poland, Department of Medical Genetics, Medical University of Warsaw, Pawixc5x84skiego 3c, Warsaw, Poland, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw, Poland, Department of Immunology, Center for Biostructure Research, Medical University of Warsaw, Banacha 2, Warsaw, Poland, Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, Warsaw, Poland and Institute of Forensic Research, Westerplatte 9, Krakow, Poland.|Institute of Computer Science, Polish Academy of Sciences, Jana Kazimierza 5, Warsaw, Poland, Department of Medical Genetics, Medical University of Warsaw, Pawixc5x84skiego 3c, Warsaw, Poland, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw, Poland, Department of Immunology, Center for Biostructure Research, Medical University of Warsaw, Banacha 2, Warsaw, Poland, Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, Warsaw, Poland and Institute of Forensic Research, Westerplatte 9, Krakow, Poland.|Institute of Computer Science, Polish Academy of Sciences, Jana Kazimierza 5, Warsaw, Poland, Department of Medical Genetics, Medical University of Warsaw, Pawixc5x84skiego 3c, Warsaw, Poland, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw, Poland, Department of Immunology, Center for Biostructure Research, Medical University of Warsaw, Banacha 2, Warsaw, Poland, Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, Warsaw, Poland and Institute of Forensic Research, Westerplatte 9, Krakow, Poland.|Institute of Computer Science, Polish Academy of Sciences, Jana Kazimierza 5, Warsaw, Poland, Department of Medical Genetics, Medical University of Warsaw, Pawixc5x84skiego 3c, Warsaw, Poland, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw, Poland, Department of Immunology, Center for Biostructure Research, Medical University of Warsaw, Banacha 2, Warsaw, Poland, Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, Warsaw, Poland and Institute of Forensic Research, Westerplatte 9, Krakow, Poland.|Institute of Computer Science, Polish Academy of Sciences, Jana Kazimierza 5, Warsaw, Poland, Department of Medical Genetics, Medical University of Warsaw, Pawixc5x84skiego 3c, Warsaw, Poland, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw, Poland, Department of Immunology, Center for Biostructure Research, Medical University of Warsaw, Banacha 2, Warsaw, Poland, Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, Warsaw, Poland and Institute of Forensic Research, Westerplatte 9, Krakow, Poland.|Institute of Computer Science, Polish Academy of Sciences, Jana Kazimierza 5, Warsaw, Poland, Department of Medical Genetics, Medical University of Warsaw, Pawixc5x84skiego 3c, Warsaw, Poland, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw, Poland, Department of Immunology, Center for Biostructure Research, Medical University of Warsaw, Banacha 2, Warsaw, Poland, Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, Warsaw, Poland and Institute of Forensic Research, Westerplatte 9, Krakow, Poland.|Institute of Computer Science, Polish Academy of Sciences, Jana Kazimierza 5, Warsaw, Poland, Department of Medical Genetics, Medical University of Warsaw, Pawixc5x84skiego 3c, Warsaw, Poland, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw, Poland, Department of Immunology, Center for Biostructure Research, Medical University of Warsaw, Banacha 2, Warsaw, Poland, Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, Warsaw, Poland and Institute of Forensic Research, Westerplatte 9, Krakow, Poland.', 'Poland|Poland|Poland|Poland|Poland|Poland|Poland|Poland|Poland', 3, 'DNA Methylation|Gene Expression Profiling|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sulfites', 'Letter', '10.1093/bioinformatics/btv090', '25682069', '-'),
(79058, 2015, 'bio', 'Folding RaCe: a robust method for predicting changes in protein folding rates upon point mutations', 'Chaudhary, Priyashree|Naganathan, Athi N|Gromiha, M Michael', 'Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600xc2xa0036, India.|Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600xc2xa0036, India.|Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600xc2xa0036, India.', 'India|India|India', 14, 'Amino Acids|Humans|Mutation|Point Mutation|Protein Folding|Protein Structure, Secondary|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btv091', '25686635', 'Protein engineering methods are commonly employed to decipher the folding mechanism of proteins and enzymes. However, such experiments are exceedingly time and resource intensive. It would therefore be advantageous to develop a simple computational tool to predict changes in folding rates upon mutations. Such a method should be able to rapidly provide the sequence position and chemical nature to modulate through mutation, to effect a particular change in rate. This can be of importance in protein folding, function or mechanistic studies.'),
(79059, 2015, 'bio', 'Characterizing spatial distributions of astrocytes in the mammalian retina', 'Jammalamadaka, Aruna|Suwannatat, Panuakdet|Fisher, Steven K|Manjunath, B S|Höllerer, Tobias|Luna, Gabriel', 'Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA.|Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA.|Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA.|Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA.|Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA.|Department of Electrical and Computer Engineering, Department of Computer Science, Neuroscience Research Institute and Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA.', 'United States|United States|United States|United States|United States|United States', 13, 'Animals|Astrocytes|Cells, Cultured|Image Processing, Computer-Assisted|Mice|Neurons|Retina', 'Journal Article', '10.1093/bioinformatics/btv097', '25686636', 'In addition to being involved in retinal vascular growth, astrocytes play an important role in diseases and injuries, such as glaucomatous neuro-degeneration and retinal detachment. Studying astrocytes, their morphological cell characteristics and their spatial relationships to the surrounding vasculature in the retina may elucidate their role in these conditions.');
