INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78317, 2014, 'bio', 'massiR: a method for predicting the sex of samples in gene expression microarray datasets', 'Buckberry, Sam|Bent, Stephen J|Bianco-Miotto, Tina|Roberts, Claire T', 'The Robinson Research Institute, School of Paediatrics and Reproductive Health, The University of Adelaide, Adelaide 5005, Australia and School of Agriculture Food and Wine, The University of Adelaide, Adelaide 5005, Australia.|The Robinson Research Institute, School of Paediatrics and Reproductive Health, The University of Adelaide, Adelaide 5005, Australia and School of Agriculture Food and Wine, The University of Adelaide, Adelaide 5005, Australia.|The Robinson Research Institute, School of Paediatrics and Reproductive Health, The University of Adelaide, Adelaide 5005, Australia and School of Agriculture Food and Wine, The University of Adelaide, Adelaide 5005, AustraliaThe Robinson Research Institute, School of Paediatrics and Reproductive Health, The University of Adelaide, Adelaide 5005, Australia and School of Agriculture Food and Wine, The University of Adelaide, Adelaide 5005, Australia.|The Robinson Research Institute, School of Paediatrics and Reproductive Health, The University of Adelaide, Adelaide 5005, Australia and School of Agriculture Food and Wine, The University of Adelaide, Adelaide 5005, Australia.', 'Australia|Australia|Australia|Australia', 10, 'Cluster Analysis|Female|Gene Expression Profiling|Humans|Male|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btu161', '24659105', 'High-throughput gene expression microarrays are currently the most efficient method for transcriptome-wide expression analyses. Consequently, gene expression data available through public repositories have largely been obtained from microarray experiments. However, the metadata associated with many publicly available expression microarray datasets often lacks sample sex information, therefore limiting the reuse of these data in new analyses or larger meta-analyses where the effect of sex is to be considered. Here, we present the massiR package, which provides a method for researchers to predict the sex of samples in microarray datasets. Using information from microarray probes representing Y chromosome genes, this package implements unsupervised clustering methods to classify samples into male and female groups, providing an efficient way to identify or confirm the sex of samples in mammalian microarray datasets.'),
(78318, 2014, 'bio', 'Improved transcript isoform discovery using ORF graphs', 'Majoros, William H|Lebeck, Niel|Ohler, Uwe|Li, Song', 'Program in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708, USA, Institute for Genome Sciences and Policy, Duke University, Durham, NC 27705, USA, Department of Computer Science, Duke University, Durham, NC 27708, USA, Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA, Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin 13125, Germany and Department of Biology, Humboldt University of Berlin, Berlin 10115, GermanyProgram in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708, USA, Institute for Genome Sciences and Policy, Duke University, Durham, NC 27705, USA, Department of Computer Science, Duke University, Durham, NC 27708, USA, Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA, Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin 13125, Germany and Department of Biology, Humboldt University of Berlin, Berlin 10115, Germany.|Program in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708, USA, Institute for Genome Sciences and Policy, Duke University, Durham, NC 27705, USA, Department of Computer Science, Duke University, Durham, NC 27708, USA, Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA, Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin 13125, Germany and Department of Biology, Humboldt University of Berlin, Berlin 10115, Germany.|Program in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708, USA, Institute for Genome Sciences and Policy, Duke University, Durham, NC 27705, USA, Department of Computer Science, Duke University, Durham, NC 27708, USA, Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA, Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin 13125, Germany and Department of Biology, Humboldt University of Berlin, Berlin 10115, GermanyProgram in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708, USA, Institute for Genome Sciences and Policy, Duke University, Durham, NC 27705, USA, Department of Computer Science, Duke University, Durham, NC 27708, USA, Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA, Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin 13125, Germany and Department of Biology, Humboldt University of Berlin, Berlin 10115, GermanyProgram in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708, USA, Institute for Genome Sciences and Policy, Duke University, Durham, NC 27705, USA, Department of Computer Science, Duke University, Durham, NC 27708, USA, Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA, Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin 13125, Germany and Department of Biology, Humboldt University of Berlin, Berlin 10115, GermanyProgram in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708, USA, Institute for Genome Sciences and Policy, Duke University, Durham, NC 27705, USA, Department of Computer Science, Duke University, Durham, NC 27708, USA, Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA, Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicin|Program in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708, USA, Institute for Genome Sciences and Policy, Duke University, Durham, NC 27705, USA, Department of Computer Science, Duke University, Durham, NC 27708, USA, Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA, Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin 13125, Germany and Department of Biology, Humboldt University of Berlin, Berlin 10115, Germany.', 'Germany|Germany|Germany|Germany', 4, 'Arabidopsis|Exons|High-Throughput Nucleotide Sequencing|Humans|Open Reading Frames|RNA Isoforms|RNA Splicing|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu160', '24659106', 'High-throughput sequencing of RNA in vivo facilitates many applications, not the least of which is the cataloging of variant splice isoforms of protein-coding messenger RNAs. Although many solutions have been proposed for reconstructing putative isoforms from deep sequencing data, these generally take as their substrate the collective alignment structure of RNA-seq reads and ignore the biological signals present in the actual nucleotide sequence. The majority of these solutions are graph-theoretic, relying on a splice graph representing the splicing patterns and exon expression levels indicated by the spliced-alignment process.'),
(78319, 2014, 'bio', 'Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression', 'Marttinen, Pekka|Pirinen, Matti|Sarin, Antti-Pekka|Gillberg, Jussi|Kettunen, Johannes|Surakka, Ida|Kangas, Antti J|Soininen, Pasi|OReilly, Paul|Kaakinen, Marika|Kähönen, Mika|Lehtimäki, Terho|Ala-Korpela, Mika|Raitakari, Olli T|Salomaa, Veikko|Järvelin, Marjo-Riitta|Ripatti, Samuli|Kaski, Samuel', 'Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, FinlandDepartment of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Dise|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland.|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, FinlandDepartment of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Dise|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland.|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, FinlandDepartment of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Dise|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, FinlandDepartment of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Dise|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland.|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, FinlandDepartment of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Dise|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland.|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, FinlandDepartment of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Dise|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland.|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland.|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, FinlandDepartment of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Dise|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, FinlandDepartment of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Dise|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland.|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, FinlandDepartment of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Dise|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, FinlandDepartment of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Dise|Department of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA, USA Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Unit of Public Health Genomics, National Institute for Health and Welfare, Helsinki, Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection, Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK, Institute of Health Sciences, Biocenter Oulu, University of Oulu, Oulu, Department of Clinical Physiology, Tampere University Hospital and University of Tampere, Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK, Department of Clinical Physiology and Nuclear Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Unit of Primary Care, Oulu University Hospital, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK, Hjelt Institute and Department of Computer Science, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, FinlandDepartment of Information and Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Esbo, Finland, Center for Communicable Dise', 'Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finl', 0, 'Adult|Bayes Theorem|Genome-Wide Association Study|Humans|Lipoproteins|Metabolome|Metabolomics|Multivariate Analysis|Phenotype|Polymorphism, Single Nucleotide|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/btu140', '24665129', 'A typical genome-wide association study searches for associations between single nucleotide polymorphisms (SNPs) and a univariate phenotype. However, there is a growing interest to investigate associations between genomics data and multivariate phenotypes, for example, in gene expression or metabolomics studies. A common approach is to perform a univariate test between each genotype-phenotype pair, and then to apply a stringent significance cutoff to account for the large number of tests performed. However, this approach has limited ability to uncover dependencies involving multiple variables. Another trend in the current genetics is the investigation of the impact of rare variants on the phenotype, where the standard methods often fail owing to lack of power when the minor allele is present in only a limited number of individuals.'),
(78320, 2014, 'bio', 'Improving MEME via a two-tiered significance analysis', 'Tanaka, Emi|Bailey, Timothy L|Keich, Uri', 'School of Mathematics and Statistics, University of Sydney, Sydney 2006, School of Mathematics and Applied Statistics, University of Wollongong, Wollongong 2522, New South Wales and Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4072, AustraliaSchool of Mathematics and Statistics, University of Sydney, Sydney 2006, School of Mathematics and Applied Statistics, University of Wollongong, Wollongong 2522, New South Wales and Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4072, Australia.|School of Mathematics and Statistics, University of Sydney, Sydney 2006, School of Mathematics and Applied Statistics, University of Wollongong, Wollongong 2522, New South Wales and Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4072, Australia.|School of Mathematics and Statistics, University of Sydney, Sydney 2006, School of Mathematics and Applied Statistics, University of Wollongong, Wollongong 2522, New South Wales and Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4072, Australia.', 'Australia|Australia|Australia', 11, 'Algorithms|Data Interpretation, Statistical|Nucleotide Motifs|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu163', '24665130', 'With over 9000 unique users recorded in the first half of 2013, MEME is one of the most popular motif-finding tools available. Reliable estimates of the statistical significance of motifs can greatly increase the usefulness of any motif finder. By analogy, it is difficult to imagine evaluating a BLAST result without its accompanying E-value. Currently MEME evaluates its EM-generated candidate motifs using an extension of BLASTs E-value to the motif-finding context. Although we previously indicated the drawbacks of MEMEs current significance evaluation, we did not offer a practical substitute suited for its needs, especially because MEME also relies on the E-value internally to rank competing candidate motifs.'),
(78321, 2014, 'bio', 'Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles', 'Aksoy, Bülent Arman|Demir, Emek|Babur, Özgün|Wang, Weiqing|Jing, Xiaohong|Schultz, Nikolaus|Sander, Chris', 'Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10065 and Tri-Institutional Training Program in Computational Biology & Medicine, New York, NY 10065, USAComputational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10065 and Tri-Institutional Training Program in Computational Biology & Medicine, New York, NY 10065, USA.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10065 and Tri-Institutional Training Program in Computational Biology & Medicine, New York, NY 10065, USA.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10065 and Tri-Institutional Training Program in Computational Biology & Medicine, New York, NY 10065, USA.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10065 and Tri-Institutional Training Program in Computational Biology & Medicine, New York, NY 10065, USA.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10065 and Tri-Institutional Training Program in Computational Biology & Medicine, New York, NY 10065, USA.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10065 and Tri-Institutional Training Program in Computational Biology & Medicine, New York, NY 10065, USA.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10065 and Tri-Institutional Training Program in Computational Biology & Medicine, New York, NY 10065, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Cell Line, Tumor|DNA Copy Number Variations|Gene Deletion|Genomics|Glioblastoma|Humans|Isoenzymes|Mice|Neoplasms|Precision Medicine', 'Journal Article', '10.1093/bioinformatics/btu164', '24665131', 'Somatic homozygous deletions of chromosomal regions in cancer, while not necessarily oncogenic, may lead to therapeutic vulnerabilities specific to cancer cells compared with normal cells. A recently reported example is the loss of one of the two isoenzymes in glioblastoma cancer cells such that the use of a specific inhibitor selectively inhibited growth of the cancer cells, which had become fully dependent on the second isoenzyme. We have now made use of the unprecedented conjunction of large-scale cancer genomics profiling of tumor samples in The Cancer Genome Atlas (TCGA) and of tumor-derived cell lines in the Cancer Cell Line Encyclopedia, as well as the availability of integrated pathway information systems, such as Pathway Commons, to systematically search for a comprehensive set of such epistatic vulnerabilities.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78322, 2014, 'bio', 'CAGExploreR: an R package for the analysis and visualization of promoter dynamics across multiple experiments', 'Dimont, Emmanuel|Hofmann, Oliver|Ho Sui, Shannan J|Forrest, Alistair R R|Kawaji, Hideya|FANTOM Consortium|Hide, Winston', 'Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA, RIKEN Omics Science Center, Yokohama, Kanagawa 230-0045 Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa 230-0045, Japan and RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama 351-0198, Japan.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA, RIKEN Omics Science Center, Yokohama, Kanagawa 230-0045 Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa 230-0045, Japan and RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama 351-0198, Japan.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA, RIKEN Omics Science Center, Yokohama, Kanagawa 230-0045 Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa 230-0045, Japan and RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama 351-0198, Japan.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA, RIKEN Omics Science Center, Yokohama, Kanagawa 230-0045 Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa 230-0045, Japan and RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama 351-0198, Japan Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA, RIKEN Omics Science Center, Yokohama, Kanagawa 230-0045 Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa 230-0045, Japan and RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama 351-0198, Japan.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA, RIKEN Omics Science Center, Yokohama, Kanagawa 230-0045 Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa 230-0045, Japan and RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama 351-0198, Japan Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA, RIKEN Omics Science Center, Yokohama, Kanagawa 230-0045 Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa 230-0045, Japan and RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama 351-0198, Japan Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA, RIKEN Omics Science Center, Yokohama, Kanagawa 230-0045 Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa 230-0045, Japan and RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama 351-0198, Japan.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA, RIKEN Omics Science Center, Yokohama, Kanagawa 230-0045 Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa 230-0045, Japan and RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama 351-0198, Japan Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA, RIKEN Omics Science Center, Yokohama, Kanagawa 230-0045 Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa 230-0045, Japan and RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama 351-0198, Japan Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA, RIKEN Omics Science Center, Yokohama, Kanagawa 230-0045 Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa 230-0045, Japan and RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama 351-0198, Japan.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA, RIKEN Omics Science Center, Yokohama, Kanagawa 230-0045 Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa 230-0045, Japan and RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama 351-0198, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 4, 'Computational Biology|Gene Expression|Promoter Regions, Genetic|RNA|Software|Transcription Initiation Site', 'Journal Article', '10.1093/bioinformatics/btu125', '24675730', 'Alternate promoter usage is an important molecular mechanism for generating RNA and protein diversity. Cap Analysis Gene Expression (CAGE) is a powerful approach for revealing the multiplicity of transcription start site (TSS) events across experiments and conditions. An understanding of the dynamics of TSS choice across these conditions requires both sensitive quantification and comparative visualization. We have developed CAGExploreR, an R package to detect and visualize changes in the use of specific TSS in wider promoter regions in the context of changes in overall gene expression when comparing different CAGE samples. These changes provide insight into the modification of transcript isoform generation and regulatory network alterations associated with cell types and conditions. CAGExploreR is based on the FANTOM5 and MPromDb promoter set definitions but can also work with user-supplied regions. The package compares multiple CAGE libraries simultaneously. Supplementary Materials describe methods in detail, and a vignette demonstrates a workflow with a real data example.'),
(78323, 2014, 'bio', 'Census 2: isobaric labeling data analysis', 'Park, Sung Kyu Robin|Aslanian, Aaron|McClatchy, Daniel B|Han, Xuemei|Shah, Harshil|Singh, Meha|Rauniyar, Navin|Moresco, James J|Pinto, Antonio F M|Diedrich, Jolene K|Delahunty, Claire|Yates, John R', 'Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Cell Line|Isotope Labeling|Mass Spectrometry|Mice|Peptides|Proteins|Proteomics|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btu151', '24681903', 'We introduce Census 2, an update of a mass spectrometry data analysis tool for peptide/protein quantification. New features for analysis of isobaric labeling, such as Tandem Mass Tag (TMT) or Isobaric Tags for Relative and Absolute Quantification (iTRAQ), have been added in this version, including a reporter ion impurity correction, a reporter ion intensity threshold filter and an option for weighted normalization to correct mixing errors. TMT/iTRAQ analysis can be performed on experiments using HCD (High Energy Collision Dissociation) only, CID (Collision Induced Dissociation)/HCD (High Energy Collision Dissociation) dual scans or HCD triple-stage mass spectrometry data. To improve measurement accuracy, we implemented weighted normalization, multiple tandem spectral approach, impurity correction and dynamic intensity threshold features.'),
(78324, 2014, 'bio', 'CorMut: an R/Bioconductor package for computing correlated mutations based on selection pressure', 'Li, Zhenpeng|Huang, Yang|Ouyang, Yabo|Jiao, Yang|Xing, Hui|Liao, Lingjie|Jiang, Shibo|Shao, Yiming|Ma, Liying', 'State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206 and Key Laboratory of Medical Molecular Virology (Ministries of Education and Health), Shanghai Medical College and Institute of Medical Microbiology, Fudan University, Shanghai 200032, China.|State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206 and Key Laboratory of Medical Molecular Virology (Ministries of Education and Health), Shanghai Medical College and Institute of Medical Microbiology, Fudan University, Shanghai 200032, China.|State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206 and Key Laboratory of Medical Molecular Virology (Ministries of Education and Health), Shanghai Medical College and Institute of Medical Microbiology, Fudan University, Shanghai 200032, China.|State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206 and Key Laboratory of Medical Molecular Virology (Ministries of Education and Health), Shanghai Medical College and Institute of Medical Microbiology, Fudan University, Shanghai 200032, China.|State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206 and Key Laboratory of Medical Molecular Virology (Ministries of Education and Health), Shanghai Medical College and Institute of Medical Microbiology, Fudan University, Shanghai 200032, China.|State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206 and Key Laboratory of Medical Molecular Virology (Ministries of Education and Health), Shanghai Medical College and Institute of Medical Microbiology, Fudan University, Shanghai 200032, China.|State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206 and Key Laboratory of Medical Molecular Virology (Ministries of Education and Health), Shanghai Medical College and Institute of Medical Microbiology, Fudan University, Shanghai 200032, China.|State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206 and Key Laboratory of Medical Molecular Virology (Ministries of Education and Health), Shanghai Medical College and Institute of Medical Microbiology, Fudan University, Shanghai 200032, China.|State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206 and Key Laboratory of Medical Molecular Virology (Ministries of Education and Health), Shanghai Medical College and Institute of Medical Microbiology, Fudan University, Shanghai 200032, China.', 'China|China|China|China|China|China|China|China|China', 8, 'Amino Acid Substitution|Codon|DNA Mutational Analysis|HIV Protease|Mutation|Software', 'Journal Article', '10.1093/bioinformatics/btu154', '24681904', 'Correlated mutations constitute a fundamental idea in evolutionary biology, and understanding correlated mutations will, in turn, facilitate an understanding of the genetic mechanisms governing evolution. CorMut is an R package designed to compute correlated mutations in the unit of codon or amino acid mutation. Three classical methods were incorporated, and the computation results can be represented as correlation mutation networks. CorMut also enables the comparison of correlated mutations between two different evolutionary conditions.'),
(78325, 2014, 'bio', 'Motifs tree: a new method for predicting post-translational modifications', 'Charpilloz, Christophe|Veuthey, Anne-Lise|Chopard, Bastien|Falcone, Jean-Luc', 'Department of Computer Science, University of Geneva, 1227 Carouge and Swiss Institute of Bioinformatics, Centre Mxc3xa9dical Universitaire, Geneva 4, SwitzerlandDepartment of Computer Science, University of Geneva, 1227 Carouge and Swiss Institute of Bioinformatics, Centre Mxc3xa9dical Universitaire, Geneva 4, Switzerland.|Department of Computer Science, University of Geneva, 1227 Carouge and Swiss Institute of Bioinformatics, Centre Mxc3xa9dical Universitaire, Geneva 4, Switzerland.|Department of Computer Science, University of Geneva, 1227 Carouge and Swiss Institute of Bioinformatics, Centre Mxc3xa9dical Universitaire, Geneva 4, SwitzerlandDepartment of Computer Science, University of Geneva, 1227 Carouge and Swiss Institute of Bioinformatics, Centre Mxc3xa9dical Universitaire, Geneva 4, Switzerland.|Department of Computer Science, University of Geneva, 1227 Carouge and Swiss Institute of Bioinformatics, Centre Mxc3xa9dical Universitaire, Geneva 4, SwitzerlandDepartment of Computer Science, University of Geneva, 1227 Carouge and Swiss Institute of Bioinformatics, Centre Mxc3xa9dical Universitaire, Geneva 4, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Acetylation|Acetyltransferases|Algorithms|Amino Acid Motifs|Artificial Intelligence|Humans|Methionine|Protein Processing, Post-Translational|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btu165', '24681905', 'Post-translational modifications (PTMs) are important steps in the maturation of proteins. Several models exist to predict specific PTMs, from manually detected patterns to machine learning methods. On one hand, the manual detection of patterns does not provide the most efficient classifiers and requires an important workload, and on the other hand, models built by machine learning methods are hard to interpret and do not increase biological knowledge. Therefore, we developed a novel method based on patterns discovery and decision trees to predict PTMs. The proposed algorithm builds a decision tree, by coupling the C4.5 algorithm with genetic algorithms, producing high-performance white box classifiers. Our method was tested on the initiator methionine cleavage (IMC) and N(xcexb1)-terminal acetylation (N-Ac), two of the most common PTMs.'),
(78326, 2014, 'bio', 'GAP: towards almost 100 percent prediction for xcexb2-strand-mediated aggregating peptides with distinct morphologies', 'Thangakani, A Mary|Kumar, Sandeep|Nagarajan, R|Velmurugan, D|Gromiha, M Michael', 'Department of Crystallography and Biophysics, University of Madras, Chennai 600025, India, Biotherapeutics Pharmaceutical Sciences, Pfizer Inc., Chesterfield, MO 63017, USA and Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600036, India.|Department of Crystallography and Biophysics, University of Madras, Chennai 600025, India, Biotherapeutics Pharmaceutical Sciences, Pfizer Inc., Chesterfield, MO 63017, USA and Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600036, India.|Department of Crystallography and Biophysics, University of Madras, Chennai 600025, India, Biotherapeutics Pharmaceutical Sciences, Pfizer Inc., Chesterfield, MO 63017, USA and Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600036, India.|Department of Crystallography and Biophysics, University of Madras, Chennai 600025, India, Biotherapeutics Pharmaceutical Sciences, Pfizer Inc., Chesterfield, MO 63017, USA and Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600036, India.|Department of Crystallography and Biophysics, University of Madras, Chennai 600025, India, Biotherapeutics Pharmaceutical Sciences, Pfizer Inc., Chesterfield, MO 63017, USA and Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600036, India.', 'India|India|India|India|India', 0, 'Algorithms|Amino Acids|Amyloid|Artificial Intelligence|Oligopeptides|Peptides|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btu167', '24681906', 'Distinguishing between amyloid fibril-forming and amorphous xcexb2-aggregating aggregation-prone regions (APRs) in proteins and peptides is crucial for designing novel biomaterials and improved aggregation inhibitors for biotechnological and therapeutic purposes.'),
(78327, 2014, 'bio', 'VariantAnnotation: a Bioconductor package for exploration and annotation of genetic variants', 'Obenchain, Valerie|Lawrence, Michael|Carey, Vincent|Gogarten, Stephanie|Shannon, Paul|Morgan, Martin', 'Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, Bioinformatics and Computational Biology, Genentech, South San Francisco, CA 94080, Brigham and Womens Hospital, Harvard Medical School, Boston, MA 02115 and Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.|Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, Bioinformatics and Computational Biology, Genentech, South San Francisco, CA 94080, Brigham and Womens Hospital, Harvard Medical School, Boston, MA 02115 and Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.|Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, Bioinformatics and Computational Biology, Genentech, South San Francisco, CA 94080, Brigham and Womens Hospital, Harvard Medical School, Boston, MA 02115 and Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.|Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, Bioinformatics and Computational Biology, Genentech, South San Francisco, CA 94080, Brigham and Womens Hospital, Harvard Medical School, Boston, MA 02115 and Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.|Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, Bioinformatics and Computational Biology, Genentech, South San Francisco, CA 94080, Brigham and Womens Hospital, Harvard Medical School, Boston, MA 02115 and Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.|Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, Bioinformatics and Computational Biology, Genentech, South San Francisco, CA 94080, Brigham and Womens Hospital, Harvard Medical School, Boston, MA 02115 and Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Genetic Variation|Genomics|Molecular Sequence Annotation|Software', 'Journal Article', '10.1093/bioinformatics/btu168', '24681907', 'VariantAnnotation is an R / Bioconductor package for the exploration and annotation of genetic variants. Capabilities exist for reading, writing and filtering variant call format (VCF) files. VariantAnnotation allows ready access to additional R / Bioconductor facilities for advanced statistical analysis, data transformation, visualization and integration with diverse genomic resources.'),
(78328, 2014, 'bio', 'molBLOCKS: decomposing small molecule sets and uncovering enriched fragments', 'Ghersi, Dario|Singh, Mona', 'Lewis-Sigler Institute for Integrative Genomics and Department of Computer Science, Princeton University, Princeton, NJ 08544, USA.|Lewis-Sigler Institute for Integrative Genomics and Department of Computer Science, Princeton University, Princeton, NJ 08544, USALewis-Sigler Institute for Integrative Genomics and Department of Computer Science, Princeton University, Princeton, NJ 08544, USA.', 'United States|United States', 19, 'Antineoplastic Agents|Drug Discovery|Ligands|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btu173', '24681908', 'The chemical structures of biomolecules, whether naturally occurring or synthetic, are composed of functionally important building blocks. Given a set of small molecules-for example, those known to bind a particular protein-computationally decomposing them into chemically meaningful fragments can help elucidate their functional properties, and may be useful for designing novel compounds with similar properties. Here we introduce molBLOCKS, a suite of programs for breaking down sets of small molecules into fragments according to a predefined set of chemical rules, clustering the resulting fragments, and uncovering statistically enriched fragments. Among other applications, our software should be a great aid in large-scale chemical analysis of ligands binding specific targets of interest.'),
(78329, 2014, 'bio', 'flowFit: a Bioconductor package to estimate proliferation in cell-tracking dye studies', 'Rambaldi, Davide|Pece, Salvatore|Di Fiore, Pier Paolo', 'Department of Experimental Oncology, Istituto Europeo di Oncologia, 20141 Milan and Dipartimento di Scienze della Salute, Università degli Studi di Milano, 20122 Milan, Italy.|Department of Experimental Oncology, Istituto Europeo di Oncologia, 20141 Milan and Dipartimento di Scienze della Salute, Università degli Studi di Milano, 20122 Milan, ItalyDepartment of Experimental Oncology, Istituto Europeo di Oncologia, 20141 Milan and Dipartimento di Scienze della Salute, Università degli Studi di Milano, 20122 Milan, Italy.|Department of Experimental Oncology, Istituto Europeo di Oncologia, 20141 Milan and Dipartimento di Scienze della Salute, Università degli Studi di Milano, 20122 Milan, ItalyDepartment of Experimental Oncology, Istituto Europeo di Oncologia, 20141 Milan and Dipartimento di Scienze della Salute, Università degli Studi di Milano, 20122 Milan, Italy.', 'Italy|Italy|Italy', 4, 'Algorithms|Animals|Cell Proliferation|Cell Separation|Cell Tracking|Flow Cytometry|Fluorescent Dyes|Mice|Software', 'Journal Article', '10.1093/bioinformatics/btu127', '24681909', 'Herein we introduce flowFit, a Bioconductor package designed to perform quantitative analysis of cell proliferation in tracking dye-based experiments. The software, distributed as an R Bioconductor library, is based on a mathematical model that takes into account the height of each peak, the size and position of the parental population (labeled but not proliferating) and the estimated distance between the brightness of a cell and the brightness of its daughter (in which the dye is assumed to undergo a 2-fold dilution). Although the algorithm does not make any inference on cell types, rates of cell divisions or rates of cell death, it deconvolutes the actual collected data into a set of peaks, whereby each peak corresponds to a subpopulation of cells that have divided N times. We validated flowFit by retrospective analysis of published proliferation-tracking experiments and demonstrated that the algorithm predicts the same percentage of cells/generation either in samples with discernible peaks (in which the peaks are visible in the collected raw data) or in samples with non-discernible peaks (in which the peaks are fused together). To the best of our knowledge, flowFit represents the first open-source algorithm in its category and might be applied to numerous areas of cell biology in which quantitative deconvolution of tracking dye-based experiments is desired, including stem cell research.'),
(78330, 2014, 'bio', 'SECA: SNP effect concordance analysis using genome-wide association summary results', 'Nyholt, Dale R', 'Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane 4000, Queensland, Australia.', 'Australia', 33, 'Genome-Wide Association Study|Genomics|Genotype|Humans|Internet|Phenotype|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btu171', '24695403', 'The genomics era provides opportunities to assess the genetic overlap across phenotypes at the measured genotype level, however, current approaches require individual-level genome-wide association (GWA) single nucleotide polymorphism (SNP) genotype data in one or both of a pair of GWA samples. To facilitate the discovery of pleiotropic effects and examine genetic overlap across two phenotypes, I have developed a user-friendly web-based application called SECA to perform SNP effect concordance analysis using GWA summary results. The method is validated using publicly available summary data from the Psychiatric Genomics Consortium.'),
(78331, 2014, 'bio', 'Trimmomatic: a flexible trimmer for Illumina sequence data', 'Bolger, Anthony M|Lohse, Marc|Usadel, Bjoern', 'Department Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, GermanyDepartment Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, Germany.|Department Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, Germany.|Department Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, GermanyDepartment Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, Germany.', 'Germany|Germany|Germany', 13250, 'Computational Biology|Databases, Genetic|High-Throughput Nucleotide Sequencing|Software', 'Journal Article', '10.1093/bioinformatics/btu170', '24695404', 'Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data.'),
(78332, 2014, 'bio', 'PRADA: pipeline for RNA sequencing data analysis', 'Torres-Garcxc3xada, Wandaliz|Zheng, Siyuan|Sivachenko, Andrey|Vegesna, Rahulsimham|Wang, Qianghu|Yao, Rong|Berger, Michael F|Weinstein, John N|Getz, Gad|Verhaak, Roel G W', 'Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10015, USA.|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10015, USA.|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10015, USA.|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10015, USA.|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10015, USA.|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10015, USA.|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10015, USA.|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10015, USA.|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10015, USA.|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10015, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 93, 'Base Sequence|Gene Fusion|Genome, Human|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|RNA, Messenger|Sequence Analysis, RNA|Software|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btu169', '24695405', 'Technological advances in high-throughput sequencing necessitate improved computational tools for processing and analyzing large-scale datasets in a systematic automated manner. For that purpose, we have developed PRADA (Pipeline for RNA-Sequencing Data Analysis), a flexible, modular and highly scalable software platform that provides many different types of information available by multifaceted analysis starting from raw paired-end RNA-seq data: gene expression levels, quality metrics, detection of unsupervised and supervised fusion transcripts, detection of intragenic fusion variants, homology scores and fusion frame classification. PRADA uses a dual-mapping strategy that increases sensitivity and refines the analytical endpoints. PRADA has been used extensively and successfully in the glioblastoma and renal clear cell projects of The Cancer Genome Atlas program.'),
(78333, 2014, 'bio', 'Deconvolving tumor purity and ploidy by integrating copy number alterations and loss of heterozygosity', 'Li, Yi|Xie, Xiaohui', 'Department of Computer Science, Institute for Genomics and Bioinformatics and Center for Machine Learning and Intelligent Systems, University of California, Irvine, CA 92697, USA.|Department of Computer Science, Institute for Genomics and Bioinformatics and Center for Machine Learning and Intelligent Systems, University of California, Irvine, CA 92697, USADepartment of Computer Science, Institute for Genomics and Bioinformatics and Center for Machine Learning and Intelligent Systems, University of California, Irvine, CA 92697, USADepartment of Computer Science, Institute for Genomics and Bioinformatics and Center for Machine Learning and Intelligent Systems, University of California, Irvine, CA 92697, USA.', 'United States|United States', 22, 'Algorithms|Breast Neoplasms|Chromosome Mapping|Computational Biology|DNA Copy Number Variations|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Loss of Heterozygosity|Models, Statistical|Neoplasms|Ploidies|Software', 'Journal Article', '10.1093/bioinformatics/btu174', '24695406', 'Next-generation sequencing (NGS) has revolutionized the study of cancer genomes. However, the reads obtained from NGS of tumor samples often consist of a mixture of normal and tumor cells, which themselves can be of multiple clonal types. A prominent problem in the analysis of cancer genome sequencing data is deconvolving the mixture to identify the reads associated with tumor cells or a particular subclone of tumor cells. Solving the problem is, however, challenging because of the so-called identifiability problem, where different combinations of tumor purity and ploidy often explain the sequencing data equally well.'),
(78334, 2014, 'bio', 'Fast alignment-free sequence comparison using spaced-word frequencies', 'Leimeister, Chris-Andre|Boden, Marcus|Horwege, Sebastian|Lindner, Sebastian|Morgenstern, Burkhard', 'Department of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, 37073 Göttingen, Germany and Université dÉvry Val dEssonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA, 91037 Évry, France.|Department of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, 37073 Göttingen, Germany and Université dÉvry Val dEssonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA, 91037 Évry, France.|Department of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, 37073 Göttingen, Germany and Université dÉvry Val dEssonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA, 91037 Évry, France.|Department of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, 37073 Göttingen, Germany and Université dÉvry Val dEssonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA, 91037 Évry, France.|Department of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, 37073 Göttingen, Germany and Université dÉvry Val dEssonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA, 91037 Évry, FranceDepartment of Bioinformatics, University of Göttingen, Institute of Microbiology and Genetics, 37073 Göttingen, Germany and Université dÉvry Val dEssonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA, 91037 Évry, France.', 'Germany|Germany|Germany|Germany|Germany', 76, 'Algorithms|Animals|Genome, Mitochondrial|Genome, Plant|Genomics|Phylogeny|Primates|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btu177', '24700317', 'Alignment-free methods for sequence comparison are increasingly used for genome analysis and phylogeny reconstruction, they circumvent various difficulties of traditional alignment-based approaches. In particular, alignment-free methods are much faster than pairwise or multiple alignments. They are, however, less accurate than methods based on sequence alignment. Most alignment-free approaches work by comparing the word composition of sequences. A well-known problem with these methods is that neighbouring word matches are far from independent.'),
(78335, 2014, 'bio', 'SVAMP: sequence variation analysis, maps and phylogeny', 'Naeem, Raeece|Hidayah, Lailatul|Preston, Mark D|Clark, Taane G|Pain, Arnab', 'Pathogen Genomics Laboratory, Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia and Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Pathogen Genomics Laboratory, Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia and Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Pathogen Genomics Laboratory, Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia and Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Pathogen Genomics Laboratory, Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia and Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Pathogen Genomics Laboratory, Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia and Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.', 'Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia', 2, 'Disease Outbreaks|Genetic Variation|Genomics|High-Throughput Nucleotide Sequencing|Humans|Malaria, Falciparum|Methicillin-Resistant Staphylococcus aureus|Phylogeny|Plasmodium falciparum|Polymorphism, Single Nucleotide|Software|Staphylococcal Infections|Time Factors', 'Journal Article', '10.1093/bioinformatics/btu176', '24700318', 'SVAMP is a stand-alone desktop application to visualize genomic variants (in variant call format) in the context of geographical metadata. Users of SVAMP are able to generate phylogenetic trees and perform principal coordinate analysis in real time from variant call format (VCF) and associated metadata files. Allele frequency map, geographical map of isolates, Tajimas D metric, single nucleotide polymorphism density, GC and variation density are also available for visualization in real time. We demonstrate the utility of SVAMP in tracking a methicillin-resistant Staphylococcus aureus outbreak from published next-generation sequencing data across 15 countries. We also demonstrate the scalability and accuracy of our software on 245 Plasmodium falciparum malaria isolates from three continents.'),
(78336, 2014, 'bio', 'rTANDEM, an R/Bioconductor package for MS/MS protein identification', 'Fournier, Frédéric|Joly Beauparlant, Charles|Paradis, René|Droit, Arnaud', 'Proteomics Center and Department of Molecular Medicine, CHUQ Research Center, Laval University, Quebec G1V 4G2, Canada.|Proteomics Center and Department of Molecular Medicine, CHUQ Research Center, Laval University, Quebec G1V 4G2, Canada.|Proteomics Center and Department of Molecular Medicine, CHUQ Research Center, Laval University, Quebec G1V 4G2, Canada.|Proteomics Center and Department of Molecular Medicine, CHUQ Research Center, Laval University, Quebec G1V 4G2, CanadaProteomics Center and Department of Molecular Medicine, CHUQ Research Center, Laval University, Quebec G1V 4G2, Canada.', 'Canada|Canada|Canada|Canada', 5, 'Algorithms|Computer Graphics|Databases, Protein|Internet|Proteomics|Software|Tandem Mass Spectrometry|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu178', '24700319', 'rTANDEM is an R/Bioconductor package that interfaces the X!Tandem protein identification algorithm. The package can run the multi-threaded algorithm on proteomic data files directly from R. It also provides functions to convert search parameters and results to/from R as well as functions to manipulate parameters and automate searches. An associated R package, shinyTANDEM, provides a web-based graphical interface to visualize and interpret the results. Together, those two packages form an entry point for a general MS/MS-based proteomic pipeline in R/Bioconductor.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78337, 2014, 'bio', 'Filling annotation gaps in yeast genomes using genome-wide contact maps', 'Marie-Nelly, Hervé|Marbouty, Martial|Cournac, Axel|Liti, Gianni|Fischer, Gilles|Zimmer, Christophe|Koszul, Romain', 'Institut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, FranceInstitut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, FranceInstitut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, FranceInstitut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Agein|Institut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, FranceInstitut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, France.|Institut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, FranceInstitut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, France.|Institut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, France.|Institut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, FranceInstitut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, France.|Institut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, FranceInstitut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, France.|Institut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, FranceInstitut Pasteur, Groupe Régulation Spatiale des Génomes, Department of Genomes and Genetics, CNRS, UMR 3525, Institut Pasteur, Unité Imagerie et Modélisation, Department of Cell Biology and Infection, CNRS, URA 2582, F-75015 Paris, France, Institute for Research on Cancer and Ageing of Nice (IRCAN), CNRS UMR 7284 - INSERM U108, Université de Nice Sophia Antipolis, 06107 Nice, France, CNRS, UMR7238, Biologie Computationnelle et Quantitative and Sorbonne Universités, UPMC Univ Paris 06, UMR7238, Biologie Computationnelle et Quantitative, F-75005, Paris, France.', 'France|France|France|France|France|France|France', 26, 'Centromere|Consensus Sequence|DNA, Ribosomal|Genetic Loci|Genome, Fungal|Genomics|Molecular Sequence Annotation|Saccharomycetales|Synteny', 'Journal Article', '10.1093/bioinformatics/btu162', '24711652', 'De novo sequencing of genomes is followed by annotation analyses aiming at identifying functional genomic features such as genes, non-coding RNAs or regulatory sequences, taking advantage of diverse datasets. These steps sometimes fail at detecting non-coding functional sequences: for example, origins of replication, centromeres and rDNA positions have proven difficult to annotate with high confidence. Here, we demonstrate an unconventional application of Chromosome Conformation Capture (3C) technique, which typically aims at deciphering the average 3D organization of genomes, by showing how functional information about the sequence can be extracted solely from the chromosome contact map.'),
(78338, 2014, 'bio', 'Covariate-modulated local false discovery rate for genome-wide association studies', 'Zablocki, Rong W|Schork, Andrew J|Levine, Richard A|Andreassen, Ole A|Dale, Anders M|Thompson, Wesley K', 'Computational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USA.|Computational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USA.|Computational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USA.|Computational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USA.|Computational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USAComputational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USAComputational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USA.|Computational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USA.', 'Norway|Norway|Norway|Norway|Norway|Norway', 25, 'Analysis of Variance|Bayes Theorem|Computational Biology|False Positive Reactions|Genome-Wide Association Study|Humans|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btu145', '24711653', 'Genome-wide association studies (GWAS) have largely failed to identify most of the genetic basis of highly heritable diseases and complex traits. Recent work has suggested this could be because many genetic variants, each with individually small effects, compose their genetic architecture, limiting the power of GWAS, given currently obtainable sample sizes. In this scenario, Bonferroni-derived thresholds are severely underpowered to detect the vast majority of associations. Local false discovery rate (fdr) methods provide more power to detect non-null associations, but implicit assumptions about the exchangeability of single nucleotide polymorphisms (SNPs) limit their ability to discover non-null loci.'),
(78339, 2014, 'bio', 'Normalization of metabolomics data with applications to correlation maps', 'Jauhiainen, Alexandra|Madhu, Basetti|Narita, Masako|Narita, Masashi|Griffiths, John|Tavaré, Simon', 'Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, SE-171 77 Stockholm, Sweden and Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.|Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, SE-171 77 Stockholm, Sweden and Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.|Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, SE-171 77 Stockholm, Sweden and Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.|Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, SE-171 77 Stockholm, Sweden and Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.|Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, SE-171 77 Stockholm, Sweden and Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.|Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, SE-171 77 Stockholm, Sweden and Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 28, 'Data Interpretation, Statistical|Humans|Magnetic Resonance Spectroscopy|Metabolic Networks and Pathways|Metabolomics|Reference Standards', 'Journal Article', '10.1093/bioinformatics/btu175', '24711654', 'In metabolomics, the goal is to identify and measure the concentrations of different metabolites (small molecules) in a cell or a biological system. The metabolites form an important layer in the complex metabolic network, and the interactions between different metabolites are often of interest. It is crucial to perform proper normalization of metabolomics data, but current methods may not be applicable when estimating interactions in the form of correlations between metabolites. We propose a normalization approach based on a mixed model, with simultaneous estimation of a correlation matrix. We also investigate how the common use of a calibration standard in nuclear magnetic resonance (NMR) experiments affects the estimation of correlations.'),
(78340, 2014, 'bio', 'HyperModules: identifying clinically and phenotypically significant network modules with disease mutations for biomarker discovery', 'Leung, Alvin|Bader, Gary D|Reimand, Jüri', 'The Donnelly Centre, University of Toronto, 160 College Street, M5S 3E1 Toronto, Ontario, Canada.|The Donnelly Centre, University of Toronto, 160 College Street, M5S 3E1 Toronto, Ontario, Canada.|The Donnelly Centre, University of Toronto, 160 College Street, M5S 3E1 Toronto, Ontario, Canada.', 'Canada|Canada|Canada', 0, 'Algorithms|Biomarkers, Tumor|Computer Graphics|Gene Regulatory Networks|Genomics|Humans|Internet|Mutation|Neoplasms|Phenotype|Protein Interaction Maps|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btu172', '24713437', 'Correlating disease mutations with clinical and phenotypic information such as drug response or patient survival is an important goal of personalized cancer genomics and a first step in biomarker discovery. HyperModules is a network search algorithm that finds frequently mutated gene modules with significant clinical or phenotypic signatures from biomolecular interaction networks.'),
(78341, 2014, 'bio', 'MetDisease--connecting metabolites to diseases via literature', 'Duren, William|Weymouth, Terry|Hull, Tim|Omenn, Gilbert S|Athey, Brian|Burant, Charles|Karnovsky, Alla', 'Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Departments of Medicine and Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA and Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Departments of Medicine and Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA and Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Departments of Medicine and Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA and Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Departments of Medicine and Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA and Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Departments of Medicine and Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA and Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Departments of Medicine and Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA and Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA Departments of Medicine and Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA and Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Databases, Chemical|Disease|Genome, Human|Humans|Medical Subject Headings|Metabolic Networks and Pathways|Metabolomics|Software', 'Journal Article', '10.1093/bioinformatics/btu179', '24713438', 'In recent years, metabolomics has emerged as an approach to perform large-scale characterization of small molecules in biological systems. Metabolomics posed a number of bioinformatics challenges associated in data analysis and interpretation. Genome-based metabolic reconstructions have established a powerful framework for connecting metabolites to genes through metabolic reactions and enzymes that catalyze them. Pathway databases and bioinformatics tools that use this framework have proven to be useful for annotating experimental metabolomics data. This framework can be used to infer connections between metabolites and diseases through annotated disease genes. However, only about half of experimentally detected metabolites can be mapped to canonical metabolic pathways. We present a new Cytoscape 3 plug-in, MetDisease, which uses an alternative approach to link metabolites to disease information. MetDisease uses Medical Subject Headings (MeSH) disease terms mapped to PubChem compounds through literature to annotate compound networks.'),
(78342, 2014, 'bio', 'ProQM-resample: improved model quality assessment for membrane proteins by limited conformational sampling', 'Wallner, Björn', 'Department of Physics, Chemistry and Biology, Linköping University, SE-581 83 Linköping and Swedish e-Science Research Center, Stockholm, SwedenDepartment of Physics, Chemistry and Biology, Linköping University, SE-581 83 Linköping and Swedish e-Science Research Center, Stockholm, Sweden.', 'Sweden', 0, 'Benchmarking|Computational Biology|Membrane Proteins|Models, Molecular|Protein Conformation', 'Journal Article', '10.1093/bioinformatics/btu187', '24713439', 'Model Quality Assessment Programs (MQAPs) are used to predict the quality of modeled protein structures. These usually use two approaches: methods using consensus of many alternative models and methods requiring only a single model to do its prediction. The consensus methods are useful to improve overall accuracy, however, they frequently fail to pick out the best possible model and cannot be used to generate and score new structures. Single-model methods, on the other hand, do not have these inherent shortcomings and can be used to both sample new structures and improve existing consensus methods. Here, we present ProQM-resample, a membrane protein-specific single-model MQAP, that couples side-chain resampling with MQAP rescoring by ProQM to improve model selection. The side-chain resampling is able to improve side-chain packing for 96% of all models, and improve model selection by 24% as measured by the sum of the Z-score for the first-ranked model (from 25.0 to 31.1), even better than the state-of-the-art consensus method Pcons. The improved model selection can be attributed to the improved side-chain quality, which enables the MQAP to rescue good backbone models with poor side-chain packing.'),
(78343, 2014, 'bio', 'Direct calculation of elementary flux modes satisfying several biological constraints in genome-scale metabolic networks', 'Pey, Jon|Planes, Francisco J', 'CEIT and TECNUN, University of Navarra, 20018 San Sebastian, Spain.|CEIT and TECNUN, University of Navarra, 20018 San Sebastian, Spain.', 'Spain|Spain', 16, 'Algorithms|Genome, Fungal|Genomics|Glucose|Metabolic Flux Analysis|Metabolic Networks and Pathways|Reproducibility of Results|Saccharomyces cerevisiae', 'Journal Article', '10.1093/bioinformatics/btu193', '24728852', 'The concept of Elementary Flux Mode (EFM) has been widely used for the past 20 years. However, its application to genome-scale metabolic networks (GSMNs) is still under development because of methodological limitations. Therefore, novel approaches are demanded to extend the application of EFMs. A novel family of methods based on optimization is emerging that provides us with a subset of EFMs. Because the calculation of the whole set of EFMs goes beyond our capacity, performing a selective search is a proper strategy.'),
(78344, 2014, 'bio', 'Codon Optimization OnLine (COOL): a web-based multi-objective optimization platform for synthetic gene design', 'Chin, Ju Xin|Chung, Bevan Kai-Sheng|Lee, Dong-Yup', 'Bioprocessing Technology Institute, Agency for Science, Technology and Research (A*STAR), Singapore 138668 and Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore 117576, Singapore.|Bioprocessing Technology Institute, Agency for Science, Technology and Research (A*STAR), Singapore 138668 and Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore 117576, Singapore.|Bioprocessing Technology Institute, Agency for Science, Technology and Research (A*STAR), Singapore 138668 and Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore 117576, SingaporeBioprocessing Technology Institute, Agency for Science, Technology and Research (A*STAR), Singapore 138668 and Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore 117576, Singapore.', 'Singapore|Singapore|Singapore', 0, 'Codon|Genes, Synthetic|Genetic Engineering|Humans|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btu192', '24728853', 'Codon optimization has been widely used for designing synthetic genes to improve their expression in heterologous host organisms. However, most of the existing codon optimization tools consider a single design criterion and/or implement a rather rigid user interface to yield only one optimal sequence, which may not be the best solution. Hence, we have developed Codon Optimization OnLine (COOL), which is the first web tool that provides the multi-objective codon optimization functionality to aid systematic synthetic gene design. COOL supports a simple and flexible interface for customizing various codon optimization parameters such as codon adaptation index, individual codon usage and codon pairing. In addition, users can visualize and compare the optimal synthetic sequences with respect to various fitness measures. User-defined DNA sequences can also be compared against the COOL optimized sequences to show the extent by which the users sequences can be further improved.'),
(78345, 2014, 'bio', 'methylC Track: visual integration of single-base resolution DNA methylation data on the WashU EpiGenome Browser', 'Zhou, Xin|Li, Daofeng|Lowdon, Rebecca F|Costello, Joseph F|Wang, Ting', 'Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63108, USA and Department of Neurosurgery, Brain Tumor Research Center, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA 94143, USA.|Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63108, USA and Department of Neurosurgery, Brain Tumor Research Center, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA 94143, USA.|Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63108, USA and Department of Neurosurgery, Brain Tumor Research Center, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA 94143, USA.|Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63108, USA and Department of Neurosurgery, Brain Tumor Research Center, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA 94143, USA.|Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63108, USA and Department of Neurosurgery, Brain Tumor Research Center, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA 94143, USA.', 'United States|United States|United States|United States|United States', 15, 'DNA Methylation|Databases, Genetic|Epigenomics|Genome, Human|Humans|Sequence Analysis, DNA|Sulfites|Web Browser', 'Journal Article', '10.1093/bioinformatics/btu191', '24728854', 'We present methylC track, an efficient mechanism for visualizing single-base resolution DNA methylation data on a genome browser. The methylC track dynamically integrates the level of methylation, the position and context of the methylated cytosine (i.e. CG, CHG and CHH), strand and confidence level (e.g. read coverage depth in the case of whole-genome bisulfite sequencing data). Investigators can access and integrate these information visually at specific locus or at the genome-wide level on the WashU EpiGenome Browser in the context of other rich epigenomic datasets.'),
(78346, 2014, 'bio', 'geiger v20: an expanded suite of methods for fitting macroevolutionary models to phylogenetic trees', 'Pennell, Matthew W|Eastman, Jonathan M|Slater, Graham J|Brown, Joseph W|Uyeda, Josef C|FitzJohn, Richard G|Alfaro, Michael E|Harmon, Luke J', 'Department of Biological Sciences and Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID 83844, Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA, Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia and Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA.|Department of Biological Sciences and Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID 83844, Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA, Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia and Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA.|Department of Biological Sciences and Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID 83844, Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA, Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia and Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA.|Department of Biological Sciences and Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID 83844, Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA, Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia and Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USADepartment of Biological Sciences and Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID 83844, Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA, Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia and Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA.|Department of Biological Sciences and Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID 83844, Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA, Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia and Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA.|Department of Biological Sciences and Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID 83844, Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA, Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia and Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA.|Department of Biological Sciences and Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID 83844, Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA, Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia and Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA.|Department of Biological Sciences and Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID 83844, Department of Paleobiology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA, Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia and Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 180, 'Algorithms|Bayes Theorem|Biological Evolution|Computational Biology|Likelihood Functions|Models, Biological|Phylogeny|Programming Languages', 'Journal Article', '10.1093/bioinformatics/btu181', '24728855', 'Phylogenetic comparative methods are essential for addressing evolutionary hypotheses with interspecific data. The scale and scope of such data have increased dramatically in the past few years. Many existing approaches are either computationally infeasible or inappropriate for data of this size. To address both of these problems, we present geiger v2.0, a complete overhaul of the popular R package geiger. We have reimplemented existing methods with more efficient algorithms and have developed several new approaches for accomodating heterogeneous models and data types.'),
(78347, 2014, 'bio', 'Lossy compression of quality scores in genomic data', 'Cánovas, Rodrigo|Moffat, Alistair|Turpin, Andrew', 'NICTA Victoria Research Laboratory, Department of Computing and Information Systems, The University of Melbourne, Victoria 3010, Australia.|NICTA Victoria Research Laboratory, Department of Computing and Information Systems, The University of Melbourne, Victoria 3010, Australia.|NICTA Victoria Research Laboratory, Department of Computing and Information Systems, The University of Melbourne, Victoria 3010, Australia.', 'Australia|Australia|Australia', 36, 'Algorithms|Base Sequence|Data Compression|Genome|Genomics|High-Throughput Nucleotide Sequencing|Polymorphism, Single Nucleotide|Quality Control', 'Journal Article', '10.1093/bioinformatics/btu183', '24728856', 'Next-generation sequencing technologies are revolutionizing medicine. Data from sequencing technologies are typically represented as a string of bases, an associated sequence of per-base quality scores and other metadata, and in aggregate can require a large amount of space. The quality scores show how accurate the bases are with respect to the sequencing process, that is, how confident the sequencer is of having called them correctly, and are the largest component in datasets in which they are retained. Previous research has examined how to store sequences of bases effectively, here we add to that knowledge by examining methods for compressing quality scores. The quality values originate in a continuous domain, and so if a fidelity criterion is introduced, it is possible to introduce flexibility in the way these values are represented, allowing lossy compression over the quality score data.'),
(78348, 2014, 'bio', 'Computational identification of natural peptides based on analysis of molecular evolution', 'Toporik, Amir|Borukhov, Itamar|Apatoff, Avihay|Gerber, Doron|Kliger, Yossef', 'The Mina and Everard Goodman Faculty of Life Sciences, Bar Ilan University, 52900 Ramat-Gan and Compugen Ltd., 69512 Tel Aviv, IsraelThe Mina and Everard Goodman Faculty of Life Sciences, Bar Ilan University, 52900 Ramat-Gan and Compugen Ltd., 69512 Tel Aviv, Israel.|The Mina and Everard Goodman Faculty of Life Sciences, Bar Ilan University, 52900 Ramat-Gan and Compugen Ltd., 69512 Tel Aviv, Israel.|The Mina and Everard Goodman Faculty of Life Sciences, Bar Ilan University, 52900 Ramat-Gan and Compugen Ltd., 69512 Tel Aviv, Israel.|The Mina and Everard Goodman Faculty of Life Sciences, Bar Ilan University, 52900 Ramat-Gan and Compugen Ltd., 69512 Tel Aviv, Israel.|The Mina and Everard Goodman Faculty of Life Sciences, Bar Ilan University, 52900 Ramat-Gan and Compugen Ltd., 69512 Tel Aviv, Israel.', 'Israel|Israel|Israel|Israel|Israel', 0, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Calcitonin|Computational Biology|Conserved Sequence|Evolution, Molecular|Humans|Molecular Sequence Data|Mutation Rate|Peptide Hormones|ROC Curve|Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btu195', '24728857', 'Many secretory peptides are synthesized as inactive precursors that must undergo post-translational processing to become biologically active peptides. Attempts to predict natural peptides are limited by the low performance of proteolytic site predictors and by the high combinatorial complexity of pairing such sites. To overcome these limitations, we analyzed the site-wise evolutionary mutation rates of peptide hormone precursors, calculated using the Rate4Site algorithm.'),
(78349, 2014, 'bio', 'A change-point model for identifying 3UTR switching by next-generation RNA sequencing', 'Wang, Wei|Wei, Zhi|Li, Hongzhe', 'Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102 and Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.|Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102 and Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.|Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102 and Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.', 'Jersey|Jersey|Jersey', 20, '3 Untranslated Regions|Base Sequence|Cell Line, Tumor|Computational Biology|Gene Expression Regulation|High-Throughput Nucleotide Sequencing|Humans|Likelihood Functions|Models, Statistical|Polyadenylation|RNA Isoforms|Sequence Analysis, RNA|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btu189', '24728858', 'Next-generation RNA sequencing offers an opportunity to investigate transcriptome in an unprecedented scale. Recent studies have revealed widespread alternative polyadenylation (polyA) in eukaryotes, leading to various mRNA isoforms differing in their 3 untranslated regions (3UTR), through which, the stability, localization and translation of mRNA can be regulated. However, very few, if any, methods and tools are available for directly analyzing this special alternative RNA processing event. Conventional methods rely on annotation of polyA sites, yet, such knowledge remains incomplete, and identification of polyA sites is still challenging. The goal of this article is to develop methods for detecting 3UTR switching without any prior knowledge of polyA annotations.'),
(78350, 2014, 'bio', 'A comprehensive comparison of association estimators for gene network inference algorithms', 'Kurt, Zeyneb|Aydin, Nizamettin|Altay, Gökmen', 'Department of Computer Engineering, Yildiz Technical University, Davutpasa, 34220 Esenler, Istanbul, Turkey and Department of Biomedical Engineering, Bahcesehir University, 34349 Besiktas, Istanbul, Turkey.|Department of Computer Engineering, Yildiz Technical University, Davutpasa, 34220 Esenler, Istanbul, Turkey and Department of Biomedical Engineering, Bahcesehir University, 34349 Besiktas, Istanbul, Turkey.|Department of Computer Engineering, Yildiz Technical University, Davutpasa, 34220 Esenler, Istanbul, Turkey and Department of Biomedical Engineering, Bahcesehir University, 34349 Besiktas, Istanbul, Turkey.', 'Turkey|Turkey|Turkey', 10, 'Algorithms|Computational Biology|Gene Regulatory Networks|Saccharomyces cerevisiae|Time Factors', 'Comparative Study', '10.1093/bioinformatics/btu182', '24728859', 'Gene network inference (GNI) algorithms enable the researchers to explore the interactions among the genes and gene products by revealing these interactions. The principal process of the GNI algorithms is to obtain the association scores among genes. Although there are several association estimators used in different applications, there is no commonly accepted estimator as the best one for the GNI applications. In this study, 27 different interaction estimators were reviewed and 14 most promising ones among them were evaluated by using three popular GNI algorithms with two synthetic and two real biological datasets belonging to Escherichia coli bacteria and Saccharomyces cerevisiae yeast. Influences of the Copula Transform (CT) pre-processing operation on the performance of the interaction estimators are also observed. This study is expected to assist many researchers while studying with GNI applications.'),
(78351, 2014, 'bio', 'R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment', 'Carroll, Robert J|Bastarache, Lisa|Denny, Joshua C', 'Department of Biomedical Informatics and Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37212, USA.|Department of Biomedical Informatics and Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37212, USA.|Department of Biomedical Informatics and Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37212, USADepartment of Biomedical Informatics and Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37212, USA.', 'United States|United States|United States', 0, 'Data Interpretation, Statistical|Genetic Association Studies|Genetic Variation|Humans|Multiple Sclerosis|Phenotype|Software', 'Journal Article', '10.1093/bioinformatics/btu197', '24733291', 'Phenome-wide association studies (PheWAS) have been used to replicate known genetic associations and discover new phenotype associations for genetic variants. This PheWAS implementation allows users to translate ICD-9 codes to PheWAS case and control groups, perform analyses using these and/or other phenotypes with covariate adjustments and plot the results. We demonstrate the methods by replicating a PheWAS on rs3135388 (near HLA-DRB, associated with multiple sclerosis) and performing a novel PheWAS using an individuals maximum white blood cell count (WBC) as a continuous measure. Our results for rs3135388 replicate known associations with more significant results than the original study on the same dataset. Our PheWAS of WBC found expected results, including associations with infections, myeloproliferative diseases and associated conditions, such as anemia. These results demonstrate the performance of the improved classification scheme and the flexibility of PheWAS encapsulated in this package.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78352, 2014, 'bio', 'Association analysis using next-generation sequence data from publicly available control groups: the robust variance score statistic', 'Derkach, Andriy|Chiang, Theodore|Gong, Jiafen|Addis, Laura|Dobbins, Sara|Tomlinson, Ian|Houlston, Richard|Pal, Deb K|Strug, Lisa J', 'Department of Statistical Science, University of Toronto, Toronto, ON, Canada, Program in Child Health Evaluative Sciences, the Hospital for Sick Children Research Institute, Toronto, ON, Canada, Department of Clinical Neuroscience, Institute of Psychiatry, Kings College London, London, Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, Molecular and Population Genetics and NIHR Comprehensive Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.|Department of Statistical Science, University of Toronto, Toronto, ON, Canada, Program in Child Health Evaluative Sciences, the Hospital for Sick Children Research Institute, Toronto, ON, Canada, Department of Clinical Neuroscience, Institute of Psychiatry, Kings College London, London, Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, Molecular and Population Genetics and NIHR Comprehensive Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.|Department of Statistical Science, University of Toronto, Toronto, ON, Canada, Program in Child Health Evaluative Sciences, the Hospital for Sick Children Research Institute, Toronto, ON, Canada, Department of Clinical Neuroscience, Institute of Psychiatry, Kings College London, London, Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, Molecular and Population Genetics and NIHR Comprehensive Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.|Department of Statistical Science, University of Toronto, Toronto, ON, Canada, Program in Child Health Evaluative Sciences, the Hospital for Sick Children Research Institute, Toronto, ON, Canada, Department of Clinical Neuroscience, Institute of Psychiatry, Kings College London, London, Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, Molecular and Population Genetics and NIHR Comprehensive Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.|Department of Statistical Science, University of Toronto, Toronto, ON, Canada, Program in Child Health Evaluative Sciences, the Hospital for Sick Children Research Institute, Toronto, ON, Canada, Department of Clinical Neuroscience, Institute of Psychiatry, Kings College London, London, Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, Molecular and Population Genetics and NIHR Comprehensive Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.|Department of Statistical Science, University of Toronto, Toronto, ON, Canada, Program in Child Health Evaluative Sciences, the Hospital for Sick Children Research Institute, Toronto, ON, Canada, Department of Clinical Neuroscience, Institute of Psychiatry, Kings College London, London, Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, Molecular and Population Genetics and NIHR Comprehensive Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.|Department of Statistical Science, University of Toronto, Toronto, ON, Canada, Program in Child Health Evaluative Sciences, the Hospital for Sick Children Research Institute, Toronto, ON, Canada, Department of Clinical Neuroscience, Institute of Psychiatry, Kings College London, London, Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, Molecular and Population Genetics and NIHR Comprehensive Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.|Department of Statistical Science, University of Toronto, Toronto, ON, Canada, Program in Child Health Evaluative Sciences, the Hospital for Sick Children Research Institute, Toronto, ON, Canada, Department of Clinical Neuroscience, Institute of Psychiatry, Kings College London, London, Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, Molecular and Population Genetics and NIHR Comprehensive Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.|Department of Statistical Science, University of Toronto, Toronto, ON, Canada, Program in Child Health Evaluative Sciences, the Hospital for Sick Children Research Institute, Toronto, ON, Canada, Department of Clinical Neuroscience, Institute of Psychiatry, Kings College London, London, Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, Molecular and Population Genetics and NIHR Comprehensive Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, CanadaDepartment of Statistical Science, University of Toronto, Toronto, ON, Canada, Program in Child Health Evaluative Sciences, the Hospital for Sick Children Research Institute, Toronto, ON, Canada, Department of Clinical Neuroscience, Institute of Psychiatry, Kings College London, London, Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, Surrey, Molecular and Population Genetics and NIHR Comprehensive Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 18, 'Algorithms|Analysis of Variance|Case-Control Studies|Child|Computational Biology|Control Groups|Data Interpretation, Statistical|Epilepsy, Rolandic|Gene Frequency|Genotype|High-Throughput Nucleotide Sequencing|Human Genome Project|Humans|Likelihood Functions|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btu196', '24733292', 'Sufficiently powered case-control studies with next-generation sequence (NGS) data remain prohibitively expensive for many investigators. If feasible, a more efficient strategy would be to include publicly available sequenced controls. However, these studies can be confounded by differences in sequencing platform, alignment, single nucleotide polymorphism and variant calling algorithms, read depth, and selection thresholds. Assuming one can match cases and controls on the basis of ethnicity and other potential confounding factors, and one has access to the aligned reads in both groups, we investigate the effect of systematic differences in read depth and selection threshold when comparing allele frequencies between cases and controls. We propose a novel likelihood-based method, the robust variance score (RVS), that substitutes genotype calls by their expected values given observed sequence data.'),
(78353, 2014, 'bio', 'CABS-flex predictions of protein flexibility compared with NMR ensembles', 'Jamroz, Michal|Kolinski, Andrzej|Kmiecik, Sebastian', 'Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw, Pasteura 1, Warsaw 02-093, Poland.|Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw, Pasteura 1, Warsaw 02-093, Poland.|Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw, Pasteura 1, Warsaw 02-093, Poland.', 'Poland|Poland|Poland', 34, 'Computational Biology|Magnetic Resonance Spectroscopy|Molecular Dynamics Simulation|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1093/bioinformatics/btu184', '24735558', 'Identification of flexible regions of protein structures is important for understanding of their biological functions. Recently, we have developed a fast approach for predicting protein structure fluctuations from a single protein model: the CABS-flex. CABS-flex was shown to be an efficient alternative to conventional all-atom molecular dynamics (MD). In this work, we evaluate CABS-flex and MD predictions by comparison with protein structural variations within NMR ensembles.'),
(78354, 2014, 'bio', 'Inferring rare disease risk variants based on exact probabilities of sharing by multiple affected relatives', 'Bureau, Alexandre|Younkin, Samuel G|Parker, Margaret M|Bailey-Wilson, Joan E|Marazita, Mary L|Murray, Jeffrey C|Mangold, Elisabeth|Albacha-Hejazi, Hasan|Beaty, Terri H|Ruczinski, Ingo', 'Centre de Recherche de lInstitut Universitaire en Santé Mentale de Québec, G1J 2G3, Département de Médecine Sociale et Préventive, Université Laval, Québec, G1V 0A6 Canada, Department of Biostatistics, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, Department of Oral Biology, Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, PA 15219, Department of Pediatrics, School of Medicine, University of Iowa, IA 52242, USA, Institute of Human Genetics, University of Bonn, Bonn D-53127, Germany and Dr. Hejazi Clinic, P.O. Box 2519, Riyadh 11461, Saudi ArabiaCentre de Recherche de lInstitut Universitaire en Santé Mentale de Québec, G1J 2G3, Département de Médecine Sociale et Préventive, Université Laval, Québec, G1V 0A6 Canada, Department of Biostatistics, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, Department of Oral Biology, Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, PA 15219, Department of Pediatrics, School of Medicine, University of Iowa, IA 52242, USA, Institute of Human Genetics, University of Bonn, Bonn D-53127, Germany and Dr. Hejazi Clinic, P.O. Box 2519, Riyadh 11461, Saudi Arabia.|Centre de Recherche de lInstitut Universitaire en Santé Mentale de Québec, G1J 2G3, Département de Médecine Sociale et Préventive, Université Laval, Québec, G1V 0A6 Canada, Department of Biostatistics, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, Department of Oral Biology, Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, PA 15219, Department of Pediatrics, School of Medicine, University of Iowa, IA 52242, USA, Institute of Human Genetics, University of Bonn, Bonn D-53127, Germany and Dr. Hejazi Clinic, P.O. Box 2519, Riyadh 11461, Saudi Arabia.|Centre de Recherche de lInstitut Universitaire en Santé Mentale de Québec, G1J 2G3, Département de Médecine Sociale et Préventive, Université Laval, Québec, G1V 0A6 Canada, Department of Biostatistics, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, Department of Oral Biology, Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, PA 15219, Department of Pediatrics, School of Medicine, University of Iowa, IA 52242, USA, Institute of Human Genetics, University of Bonn, Bonn D-53127, Germany and Dr. Hejazi Clinic, P.O. Box 2519, Riyadh 11461, Saudi Arabia.|Centre de Recherche de lInstitut Universitaire en Santé Mentale de Québec, G1J 2G3, Département de Médecine Sociale et Préventive, Université Laval, Québec, G1V 0A6 Canada, Department of Biostatistics, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, Department of Oral Biology, Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, PA 15219, Department of Pediatrics, School of Medicine, University of Iowa, IA 52242, USA, Institute of Human Genetics, University of Bonn, Bonn D-53127, Germany and Dr. Hejazi Clinic, P.O. Box 2519, Riyadh 11461, Saudi Arabia.|Centre de Recherche de lInstitut Universitaire en Santé Mentale de Québec, G1J 2G3, Département de Médecine Sociale et Préventive, Université Laval, Québec, G1V 0A6 Canada, Department of Biostatistics, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, Department of Oral Biology, Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, PA 15219, Department of Pediatrics, School of Medicine, University of Iowa, IA 52242, USA, Institute of Human Genetics, University of Bonn, Bonn D-53127, Germany and Dr. Hejazi Clinic, P.O. Box 2519, Riyadh 11461, Saudi Arabia.|Centre de Recherche de lInstitut Universitaire en Santé Mentale de Québec, G1J 2G3, Département de Médecine Sociale et Préventive, Université Laval, Québec, G1V 0A6 Canada, Department of Biostatistics, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, Department of Oral Biology, Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, PA 15219, Department of Pediatrics, School of Medicine, University of Iowa, IA 52242, USA, Institute of Human Genetics, University of Bonn, Bonn D-53127, Germany and Dr. Hejazi Clinic, P.O. Box 2519, Riyadh 11461, Saudi Arabia.|Centre de Recherche de lInstitut Universitaire en Santé Mentale de Québec, G1J 2G3, Département de Médecine Sociale et Préventive, Université Laval, Québec, G1V 0A6 Canada, Department of Biostatistics, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, Department of Oral Biology, Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, PA 15219, Department of Pediatrics, School of Medicine, University of Iowa, IA 52242, USA, Institute of Human Genetics, University of Bonn, Bonn D-53127, Germany and Dr. Hejazi Clinic, P.O. Box 2519, Riyadh 11461, Saudi Arabia.|Centre de Recherche de lInstitut Universitaire en Santé Mentale de Québec, G1J 2G3, Département de Médecine Sociale et Préventive, Université Laval, Québec, G1V 0A6 Canada, Department of Biostatistics, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, Department of Oral Biology, Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, PA 15219, Department of Pediatrics, School of Medicine, University of Iowa, IA 52242, USA, Institute of Human Genetics, University of Bonn, Bonn D-53127, Germany and Dr. Hejazi Clinic, P.O. Box 2519, Riyadh 11461, Saudi Arabia.|Centre de Recherche de lInstitut Universitaire en Santé Mentale de Québec, G1J 2G3, Département de Médecine Sociale et Préventive, Université Laval, Québec, G1V 0A6 Canada, Department of Biostatistics, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, Department of Oral Biology, Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, PA 15219, Department of Pediatrics, School of Medicine, University of Iowa, IA 52242, USA, Institute of Human Genetics, University of Bonn, Bonn D-53127, Germany and Dr. Hejazi Clinic, P.O. Box 2519, Riyadh 11461, Saudi Arabia.|Centre de Recherche de lInstitut Universitaire en Santé Mentale de Québec, G1J 2G3, Département de Médecine Sociale et Préventive, Université Laval, Québec, G1V 0A6 Canada, Department of Biostatistics, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, Department of Oral Biology, Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, PA 15219, Department of Pediatrics, School of Medicine, University of Iowa, IA 52242, USA, Institute of Human Genetics, University of Bonn, Bonn D-53127, Germany and Dr. Hejazi Clinic, P.O. Box 2519, Riyadh 11461, Saudi Arabia.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 20, 'Case-Control Studies|Exome|Female|Genetic Linkage|Genetic Predisposition to Disease|Genetic Variation|Genome-Wide Association Study|Genomics|Humans|Male|Monte Carlo Method|Pedigree|Probability|Rare Diseases', 'Journal Article', '10.1093/bioinformatics/btu198', '24740360', 'Family-based designs are regaining popularity for genomic sequencing studies because they provide a way to test cosegregation with disease of variants that are too rare in the population to be tested individually in a conventional case-control study.'),
(78355, 2014, 'bio', 'DSRC 2--Industry-oriented compression of FASTQ files', 'Roguski, Lukasz|Deorowicz, Sebastian', 'Polish-Japanese Institute of Information Technology, 02-008 Warszawa and Institute of Informatics, Silesian University of Technology, 44-100 Gliwice, Poland.|Polish-Japanese Institute of Information Technology, 02-008 Warszawa and Institute of Informatics, Silesian University of Technology, 44-100 Gliwice, Poland.', 'Japan|Japan', 47, 'Algorithms|Data Compression|Documentation|Genomics|Industry|Sequence Analysis, DNA|Software|Time Factors', 'Journal Article', '10.1093/bioinformatics/btu208', '24747219', 'Modern sequencing platforms produce huge amounts of data. Archiving them raises major problems but is crucial for reproducibility of results, one of the most fundamental principles of science. The widely used gzip compressor, used for reduction of storage and transfer costs, is not a perfect solution, so a few specialized FASTQ compressors were proposed recently. Unfortunately, they are often impractical because of slow processing, lack of support for some variants of FASTQ files or instability. We propose DSRC 2 that offers compression ratios comparable with the best existing solutions, while being a few times faster and more flexible.'),
(78356, 2014, 'bio', 'Herpesviral helicase-primase subunit UL8 is inactivated B-family polymerase', 'Kazlauskas, Darius|Venclovas, Ceslovas', 'Institute of Biotechnology, Vilnius University, Graixc4x8dixc5xabno 8, LT-02241 Vilnius, Lithuania.|Institute of Biotechnology, Vilnius University, Graixc4x8dixc5xabno 8, LT-02241 Vilnius, Lithuania.', 'Lithuania|Lithuania', 6, 'Amino Acid Motifs|Animals|Binding Sites|Computational Biology|Conserved Sequence|DNA Helicases|DNA Primase|DNA Replication|DNA-Directed DNA Polymerase|Enzyme Activation|Evolution, Molecular|Herpesvirus 1, Human|Humans|Models, Molecular|Multifunctional Enzymes|Viral Proteins|Virus Replication', 'Journal Article', '10.1093/bioinformatics/btu204', '24747220', 'Herpesviruses are large DNA viruses causing a variety of diseases in humans and animals. To develop effective treatment, it is important to understand the mechanisms of their replication. One of the components of the herpesviral DNA replication system is a helicase-primase complex, consisting of UL5 (helicase), UL52 (primase) and UL8. UL8 is an essential herpesviral protein involved in multiple protein-protein interactions. Intriguingly, so far no UL8 homologs outside of herpesviruses could be identified. Moreover, nothing is known about its structure or domain organization.'),
(78357, 2014, 'bio', 'Efficient Bayesian inference under the structured coalescent', 'Vaughan, Timothy G|Kühnert, Denise|Popinga, Alex|Welch, David|Drummond, Alexei J', 'Allan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North 4442, New Zealand, Institute of Integrative Biology, Swiss Federal Institute of Technology (ETH), Zurich 8092, Switzerland and Department of Computer Science, University of Auckland, Auckland 1142, New Zealand.|Allan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North 4442, New Zealand, Institute of Integrative Biology, Swiss Federal Institute of Technology (ETH), Zurich 8092, Switzerland and Department of Computer Science, University of Auckland, Auckland 1142, New ZealandAllan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North 4442, New Zealand, Institute of Integrative Biology, Swiss Federal Institute of Technology (ETH), Zurich 8092, Switzerland and Department of Computer Science, University of Auckland, Auckland 1142, New ZealandAllan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North 4442, New Zealand, Institute of Integrative Biology, Swiss Federal Institute of Technology (ETH), Zurich 8092, Switzerland and Department of Computer Science, University of Auckland, Auckland 1142, New Zealand.|Allan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North 4442, New Zealand, Institute of Integrative Biology, Swiss Federal Institute of Technology (ETH), Zurich 8092, Switzerland and Department of Computer Science, University of Auckland, Auckland 1142, New ZealandAllan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North 4442, New Zealand, Institute of Integrative Biology, Swiss Federal Institute of Technology (ETH), Zurich 8092, Switzerland and Department of Computer Science, University of Auckland, Auckland 1142, New Zealand.|Allan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North 4442, New Zealand, Institute of Integrative Biology, Swiss Federal Institute of Technology (ETH), Zurich 8092, Switzerland and Department of Computer Science, University of Auckland, Auckland 1142, New ZealandAllan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North 4442, New Zealand, Institute of Integrative Biology, Swiss Federal Institute of Technology (ETH), Zurich 8092, Switzerland and Department of Computer Science, University of Auckland, Auckland 1142, New Zealand.|Allan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North 4442, New Zealand, Institute of Integrative Biology, Swiss Federal Institute of Technology (ETH), Zurich 8092, Switzerland and Department of Computer Science, University of Auckland, Auckland 1142, New ZealandAllan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North 4442, New Zealand, Institute of Integrative Biology, Swiss Federal Institute of Technology (ETH), Zurich 8092, Switzerland and Department of Computer Science, University of Auckland, Auckland 1142, New Zealand.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 49, 'Algorithms|Bayes Theorem|Influenza A Virus, H3N2 Subtype|Markov Chains|Monte Carlo Method|Mutation Rate|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btu201', '24753484', 'Population structure significantly affects evolutionary dynamics. Such structure may be due to spatial segregation, but may also reflect any other gene-flow-limiting aspect of a model. In combination with the structured coalescent, this fact can be used to inform phylogenetic tree reconstruction, as well as to infer parameters such as migration rates and subpopulation sizes from annotated sequence data. However, conducting Bayesian inference under the structured coalescent is impeded by the difficulty of constructing Markov Chain Monte Carlo (MCMC) sampling algorithms (samplers) capable of efficiently exploring the state space.'),
(78358, 2014, 'bio', 'MRMPROBS suite for metabolomics using large-scale MRM assays', 'Tsugawa, Hiroshi|Kanazawa, Mitsuhiro|Ogiwara, Atsushi|Arita, Masanori', 'RIKEN Center for Sustainable Resource Science, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan Department of Biotechnology, Graduate School of Engineering, Osaka University, Suita, Osaka 565-0871, Japan Reifycs Incorporated, 1-6-12 Nishishinbashi, Minato-ku, Tokyo 105-0003, Japan and National Institute of Genetics, Mishima, Shizuoka 411-8540, JapanRIKEN Center for Sustainable Resource Science, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan Department of Biotechnology, Graduate School of Engineering, Osaka University, Suita, Osaka 565-0871, Japan Reifycs Incorporated, 1-6-12 Nishishinbashi, Minato-ku, Tokyo 105-0003, Japan and National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan.|RIKEN Center for Sustainable Resource Science, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan Department of Biotechnology, Graduate School of Engineering, Osaka University, Suita, Osaka 565-0871, Japan Reifycs Incorporated, 1-6-12 Nishishinbashi, Minato-ku, Tokyo 105-0003, Japan and National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan.|RIKEN Center for Sustainable Resource Science, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan Department of Biotechnology, Graduate School of Engineering, Osaka University, Suita, Osaka 565-0871, Japan Reifycs Incorporated, 1-6-12 Nishishinbashi, Minato-ku, Tokyo 105-0003, Japan and National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan.|RIKEN Center for Sustainable Resource Science, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan Department of Biotechnology, Graduate School of Engineering, Osaka University, Suita, Osaka 565-0871, Japan Reifycs Incorporated, 1-6-12 Nishishinbashi, Minato-ku, Tokyo 105-0003, Japan and National Institute of Genetics, Mishima, Shizuoka 411-8540, JapanRIKEN Center for Sustainable Resource Science, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan Department of Biotechnology, Graduate School of Engineering, Osaka University, Suita, Osaka 565-0871, Japan Reifycs Incorporated, 1-6-12 Nishishinbashi, Minato-ku, Tokyo 105-0003, Japan and National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan.', 'Japan|Japan|Japan|Japan', 25, 'Algorithms|Mass Spectrometry|Metabolomics|Software', 'Journal Article', '10.1093/bioinformatics/btu203', '24753485', 'We developed new software environment for the metabolome analysis of large-scale multiple reaction monitoring (MRM) assays. It supports the data format of four major mass spectrometer vendors and mzML common data format. This program provides a process pipeline from the raw-format import to high-dimensional statistical analyses. The novel aspect is graphical user interface-based visualization to perform peak quantification, to interpolate missing values and to normalize peaks interactively based on quality control samples. Together with the software platform, the MRM standard library of 301 metabolites with 775 transitions is also available, which contributes to the reliable peak identification by using retention time and ion abundances.'),
(78359, 2014, 'bio', 'aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data', 'Rosenberger, George|Ludwig, Christina|Röst, Hannes L|Aebersold, Ruedi|Malmström, Lars', 'Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland, PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland and Faculty of Science, University of Zurich, Zurich, Switzerland Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland, PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland and Faculty of Science, University of Zurich, Zurich, Switzerland.|Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland, PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland and Faculty of Science, University of Zurich, Zurich, Switzerland.|Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland, PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland and Faculty of Science, University of Zurich, Zurich, Switzerland Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland, PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland and Faculty of Science, University of Zurich, Zurich, Switzerland.|Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland, PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland and Faculty of Science, University of Zurich, Zurich, Switzerland Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland, PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland and Faculty of Science, University of Zurich, Zurich, Switzerland.|Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland, PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland and Faculty of Science, University of Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 36, 'Algorithms|Chromatography, Liquid|Proteins|Proteomics|Software|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btu200', '24753486', 'The determination of absolute quantities of proteins in biological samples is necessary for multiple types of scientific inquiry. While relative quantification has been commonly used in proteomics, few proteomic datasets measuring absolute protein quantities have been reported to date. Various technologies have been applied using different types of input data, e.g. ion intensities or spectral counts, as well as different absolute normalization strategies. To date, a user-friendly and transparent software supporting large-scale absolute protein quantification has been lacking.'),
(78360, 2014, 'bio', 'Multiscale DNA partitioning: statistical evidence for segments', 'Futschik, Andreas|Hotz, Thomas|Munk, Axel|Sieling, Hannes', 'Department of Applied Statistics, JK University Linz, A-4040 Linz, Austria, Institute of Mathematics, Technische Universität Ilmenau, D-98693 Ilmenau, Germany, Institute for Mathematical Stochastics and Felix Bernstein Institute for Mathematical Statistics in Biosciences, Georgia Augusta University of Goettingen and Max Planck Institute for Biophysical Chemistry, D-37077 Goettingen, Germany.|Department of Applied Statistics, JK University Linz, A-4040 Linz, Austria, Institute of Mathematics, Technische Universität Ilmenau, D-98693 Ilmenau, Germany, Institute for Mathematical Stochastics and Felix Bernstein Institute for Mathematical Statistics in Biosciences, Georgia Augusta University of Goettingen and Max Planck Institute for Biophysical Chemistry, D-37077 Goettingen, Germany.|Department of Applied Statistics, JK University Linz, A-4040 Linz, Austria, Institute of Mathematics, Technische Universität Ilmenau, D-98693 Ilmenau, Germany, Institute for Mathematical Stochastics and Felix Bernstein Institute for Mathematical Statistics in Biosciences, Georgia Augusta University of Goettingen and Max Planck Institute for Biophysical Chemistry, D-37077 Goettingen, GermanyDepartment of Applied Statistics, JK University Linz, A-4040 Linz, Austria, Institute of Mathematics, Technische Universität Ilmenau, D-98693 Ilmenau, Germany, Institute for Mathematical Stochastics and Felix Bernstein Institute for Mathematical Statistics in Biosciences, Georgia Augusta University of Goettingen and Max Planck Institute for Biophysical Chemistry, D-37077 Goettingen, Germany.|Department of Applied Statistics, JK University Linz, A-4040 Linz, Austria, Institute of Mathematics, Technische Universität Ilmenau, D-98693 Ilmenau, Germany, Institute for Mathematical Stochastics and Felix Bernstein Institute for Mathematical Statistics in Biosciences, Georgia Augusta University of Goettingen and Max Planck Institute for Biophysical Chemistry, D-37077 Goettingen, Germany.', 'Austria|Austria|Austria|Austria', 12, 'Algorithms|Bacteriophage lambda|Base Composition|DNA|Data Interpretation, Statistical|Genome, Human|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu180', '24753487', 'DNA segmentation, i.e. the partitioning of DNA in compositionally homogeneous segments, is a basic task in bioinformatics. Different algorithms have been proposed for various partitioning criteria such as Guanine/Cytosine (GC) content, local ancestry in population genetics or copy number variation. A critical component of any such method is the choice of an appropriate number of segments. Some methods use model selection criteria and do not provide a suitable error control. Other methods that are based on simulating a statistic under a null model provide suitable error control only if the correct null model is chosen.'),
(78361, 2014, 'bio', 'Improving B-cell epitope prediction and its application to global antibody-antigen docking', 'Krawczyk, Konrad|Liu, Xiaofeng|Baker, Terry|Shi, Jiye|Deane, Charlotte M', 'Department of Statistics, Oxford University, OX1 3TG, Oxford, UCB Pharma, SL1 3WE Slough, UK and Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China.|Department of Statistics, Oxford University, OX1 3TG, Oxford, UCB Pharma, SL1 3WE Slough, UK and Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China.|Department of Statistics, Oxford University, OX1 3TG, Oxford, UCB Pharma, SL1 3WE Slough, UK and Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China.|Department of Statistics, Oxford University, OX1 3TG, Oxford, UCB Pharma, SL1 3WE Slough, UK and Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, ChinaDepartment of Statistics, Oxford University, OX1 3TG, Oxford, UCB Pharma, SL1 3WE Slough, UK and Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China.|Department of Statistics, Oxford University, OX1 3TG, Oxford, UCB Pharma, SL1 3WE Slough, UK and Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China.', 'China|China|China|China|China', 42, 'Algorithms|Antigen-Antibody Complex|Epitopes, B-Lymphocyte|Humans|Molecular Docking Simulation|Software', 'Journal Article', '10.1093/bioinformatics/btu190', '24753488', 'Antibodies are currently the most important class of biopharmaceuticals. Development of such antibody-based drugs depends on costly and time-consuming screening campaigns. Computational techniques such as antibody-antigen docking hold the potential to facilitate the screening process by rapidly providing a list of initial poses that approximate the native complex.'),
(78362, 2014, 'bio', 'A new era in bioimage informatics', 'Murphy, Robert F', 'Lane Center for Computational Biology, and Departments of Biological Sciences, Biomedical Engineering, and Machine Learning, Carnegie Mellon University and Faculty of Biology and Freiburg Institute for Advanced Studies, Albert Ludwig University of Freiburg.', '-', 12, 'Algorithms|Automation, Laboratory|Computational Biology|Software', 'Editorial', '10.1093/bioinformatics/btu158', '24753489', '-'),
(78363, 2014, 'bio', 'Rgb: a scriptable genome browser for R', 'Mareschal, Sylvain|Dubois, Sydney|Lecroq, Thierry|Jardin, Fabrice', 'Centre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, FranceCentre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, FranceCentre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, France.|Centre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, FranceCentre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, FranceCentre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, France.|Centre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, FranceCentre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, FranceCentre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, France.|Centre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, FranceCentre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, FranceCentre Henri Becquerel, INSERM UMR 918, 76038 Rouen Cedex 1, France, Normandy University, University of Rouen, 76821 Mont-Saint-Aignan, France, Institute for Research and Innovation in Biomedicine (IRIB), Haute-Normandie, 76183 Rouen Cedex, France and LITIS, INSA EA 4108, 76801 Saint-Etienne-du-Rouvray, France.', 'France|France|France|France', 2, 'Algorithms|Genome, Human|Genomics|Humans|User-Computer Interface|Web Browser', 'Journal Article', '10.1093/bioinformatics/btu185', '24753490', 'Thanks to its free licensing and the development of initiatives like Bioconductor, R has become an essential part of the bioinformatics toolbox in the past years and is more and more confronted with genomically located data. While separate solutions are available to manipulate and visualize such data, no R package currently offers the efficiency required for computationally intensive tasks such as interactive genome browsing. The package proposed here fulfills this specific need, providing a multilevel interface suitable for most needs, from a completely interfaced genome browser to low-level classes and methods. Its time and memory efficiency have been challenged in a human dataset, where it outperformed existing solutions by several orders of magnitude.'),
(78364, 2014, 'bio', 'A power set-based statistical selection procedure to locate susceptible rare variants associated with complex traits with sequencing data', 'Sun, Hokeun|Wang, Shuang', 'Department of Statistics, Pusan National University, Pusan 609-735, Korea and Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.|Department of Statistics, Pusan National University, Pusan 609-735, Korea and Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.', 'United States|United States', 5, 'Angiopoietin-like 4 Protein|Angiopoietins|Data Interpretation, Statistical|Energy Metabolism|Genetic Association Studies|Genetic Variation|Humans|Lipoproteins, VLDL|Phenotype|Sequence Analysis, DNA|Triglycerides', 'Journal Article', '10.1093/bioinformatics/btu207', '24755303', 'Existing association methods for rare variants from sequencing data have focused on aggregating variants in a gene or a genetic region because of the fact that analysing individual rare variants is underpowered. However, these existing rare variant detection methods are not able to identify which rare variants in a gene or a genetic region of all variants are associated with the complex diseases or traits. Once phenotypic associations of a gene or a genetic region are identified, the natural next step in the association study with sequencing data is to locate the susceptible rare variants within the gene or the genetic region.'),
(78365, 2014, 'bio', 'The cell behavior ontology: describing the intrinsic biological behaviors of real and model cells seen as active agents', 'Sluka, James P|Shirinifard, Abbas|Swat, Maciej|Cosmanescu, Alin|Heiland, Randy W|Glazier, James A', 'Department of Physics, Biocomplexity Institute, Indiana University, Bloomington, IN 47405, USA.|Department of Physics, Biocomplexity Institute, Indiana University, Bloomington, IN 47405, USA.|Department of Physics, Biocomplexity Institute, Indiana University, Bloomington, IN 47405, USA.|Department of Physics, Biocomplexity Institute, Indiana University, Bloomington, IN 47405, USA.|Department of Physics, Biocomplexity Institute, Indiana University, Bloomington, IN 47405, USA.|Department of Physics, Biocomplexity Institute, Indiana University, Bloomington, IN 47405, USA.', 'India|India|India|India|India|India', 16, 'Biological Ontologies|Cell Physiological Phenomena|Computer Simulation|Models, Biological', 'Journal Article', '10.1093/bioinformatics/btu210', '24755304', 'Currently, there are no ontologies capable of describing both the spatial organization of groups of cells and the behaviors of those cells. The lack of a formalized method for describing the spatiality and intrinsic biological behaviors of cells makes it difficult to adequately describe cells, tissues and organs as spatial objects in living tissues, in vitro assays and in computational models of tissues.'),
(78366, 2014, 'bio', 'kdetrees: Non-parametric estimation of phylogenetic tree distributions', 'Weyenberg, Grady|Huggins, Peter M|Schardl, Christopher L|Howe, Daniel K|Yoshida, Ruriko', 'Department of Statistics, University of Kentucky, Lexington, KY 40536, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, Plant Pathology Department and Department of Veterinary Science, University of Kentucky, Lexington, KY 40546, USA.|Department of Statistics, University of Kentucky, Lexington, KY 40536, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, Plant Pathology Department and Department of Veterinary Science, University of Kentucky, Lexington, KY 40546, USA.|Department of Statistics, University of Kentucky, Lexington, KY 40536, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, Plant Pathology Department and Department of Veterinary Science, University of Kentucky, Lexington, KY 40546, USA.|Department of Statistics, University of Kentucky, Lexington, KY 40536, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, Plant Pathology Department and Department of Veterinary Science, University of Kentucky, Lexington, KY 40546, USA.|Department of Statistics, University of Kentucky, Lexington, KY 40536, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, Plant Pathology Department and Department of Veterinary Science, University of Kentucky, Lexington, KY 40546, USA.', 'United States|United States|United States|United States|United States', 24, 'Algorithms|Apicomplexa|Epichloe|Gene Transfer, Horizontal|Genes|Phylogeny|Sequence Alignment|Software|Statistics, Nonparametric', 'Journal Article', '10.1093/bioinformatics/btu258', '24764459', 'Although the majority of gene histories found in a clade of organisms are expected to be generated by a common process (e.g. the coalescent process), it is well known that numerous other coexisting processes (e.g. horizontal gene transfers, gene duplication and subsequent neofunctionalization) will cause some genes to exhibit a history distinct from those of the majority of genes. Such outlying gene trees are considered to be biologically interesting, and identifying these genes has become an important problem in phylogenetics.'),
(78367, 2014, 'bio', 'Circular RNAs are depleted of polymorphisms at microRNA binding sites', 'Thomas, Laurent F|Sætrom, Pål', 'Department of Cancer Research and Molecular Medicine and Department of Computer and Information Science, Norwegian University of Science and Technology, N-7489 Trondheim, Norway.|Department of Cancer Research and Molecular Medicine and Department of Computer and Information Science, Norwegian University of Science and Technology, N-7489 Trondheim, NorwayDepartment of Cancer Research and Molecular Medicine and Department of Computer and Information Science, Norwegian University of Science and Technology, N-7489 Trondheim, Norway.', 'Norway|Norway', 96, 'Binding Sites|Humans|MicroRNAs|Polymorphism, Single Nucleotide|RNA', 'Journal Article', '10.1093/bioinformatics/btu257', '24764460', 'Circular RNAs (circRNAs) are an abundant class of highly stable RNAs that can affect gene regulation by binding and preventing microRNAs (miRNAs) from regulating their messenger RNA (mRNA) targets. Mammals have thousands of circRNAs with predicted miRNA binding sites, but only two circRNAs have been verified as being actual miRNA sponges. As it is unclear whether these thousands of predicted miRNA binding sites are functional, we investigated whether miRNA seed sites within human circRNAs are under selective pressure.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78368, 2014, 'bio', 'relax: the analysis of biomolecular kinetics and thermodynamics using NMR relaxation dispersion data', 'Morin, Sébastien|Linnet, Troels E|Lescanne, Mathilde|Schanda, Paul|Thompson, Gary S|Tollinger, Martin|Teilum, Kaare|Gagné, Stéphane|Marion, Dominique|Griesinger, Christian|Blackledge, Martin|dAuvergne, Edward J', 'PROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, GermanyPROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, Germany.|PROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, Germany.|PROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, Germany.|PROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, Germany.|PROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, Germany.|PROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, Germany.|PROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, Germany.|PROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, Germany.|PROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, Germany.|PROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, Germany.|PROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, Germany.|PROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, GermanyPROTEO, Université Laval, Québec G1V 0A6, Canada, International AIDS Society HQ, CH-1202 Geneva, Switzerland, Department of Biology, University of Copenhagen, DK-2200 Denmark, Institut de Biologie Structurale, Grenoble F-38027, France, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK, Institute of Organic Chemistry & CMBI, University of Innsbruck, A-6020, Austria and NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, D-37077 Göttingen, Germany.', 'Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria', 26, 'Computer Graphics|Kinetics|Nuclear Magnetic Resonance, Biomolecular|Software|Statistics as Topic|Thermodynamics|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu166', '24764461', 'Nuclear magnetic resonance (NMR) is a powerful tool for observing the motion of biomolecules at the atomic level. One technique, the analysis of relaxation dispersion phenomenon, is highly suited for studying the kinetics and thermodynamics of biological processes. Built on top of the relax computational environment for NMR dynamics is a new dispersion analysis designed to be comprehensive, accurate and easy-to-use. The software supports more models, both numeric and analytic, than current solutions. An automated protocol, available for scripting and driving the graphical user interface (GUI), is designed to simplify the analysis of dispersion data for NMR spectroscopists. Decreases in optimization time are granted by parallelization for running on computer clusters and by skipping an initial grid search by using parameters from one solution as the starting point for another -using analytic model results for the numeric models, taking advantage of model nesting, and using averaged non-clustered results for the clustered analysis.'),
(78369, 2014, 'bio', 'On non-detects in qPCR data', 'McCall, Matthew N|McMurray, Helene R|Land, Hartmut|Almudevar, Anthony', 'Department of Biostatistics and Computational Biology, Department of Biomedical Genetics and James P Wilmot Cancer Center, University of Rochester Medical Center, Rochester, NY 14642, USA.|Department of Biostatistics and Computational Biology, Department of Biomedical Genetics and James P Wilmot Cancer Center, University of Rochester Medical Center, Rochester, NY 14642, USA.|Department of Biostatistics and Computational Biology, Department of Biomedical Genetics and James P Wilmot Cancer Center, University of Rochester Medical Center, Rochester, NY 14642, USADepartment of Biostatistics and Computational Biology, Department of Biomedical Genetics and James P Wilmot Cancer Center, University of Rochester Medical Center, Rochester, NY 14642, USA.|Department of Biostatistics and Computational Biology, Department of Biomedical Genetics and James P Wilmot Cancer Center, University of Rochester Medical Center, Rochester, NY 14642, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Animals|Gene Expression Profiling|Mice|Models, Theoretical|Real-Time Polymerase Chain Reaction|Software', 'Journal Article', '10.1093/bioinformatics/btu239', '24764462', 'Quantitative real-time PCR (qPCR) is one of the most widely used methods to measure gene expression. Despite extensive research in qPCR laboratory protocols, normalization and statistical analysis, little attention has been given to qPCR non-detects-those reactions failing to produce a minimum amount of signal.'),
(78370, 2014, 'bio', 'GenCLiP 20: a web server for functional clustering of genes and construction of molecular networks based on free terms', 'Wang, Jia-Hong|Zhao, Ling-Feng|Lin, Pei|Su, Xiao-Rong|Chen, Shi-Jun|Huang, Li-Qiang|Wang, Hua-Feng|Zhang, Hai|Hu, Zhen-Fu|Yao, Kai-Tai|Huang, Zhong-Xi', 'Cancer Institute, Key Laboratory of Zebrafish Modeling and Drug Screening for Human Diseases of Guangdong Higher Education Institutes, Department of Cell Biology, Southern Medical University, Guangzhou 510515, Guangzhou Biotechnology Center, Guangzhou, 510630, School of Basic Medical Sciences, Network Center and Department of Plastic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.|Cancer Institute, Key Laboratory of Zebrafish Modeling and Drug Screening for Human Diseases of Guangdong Higher Education Institutes, Department of Cell Biology, Southern Medical University, Guangzhou 510515, Guangzhou Biotechnology Center, Guangzhou, 510630, School of Basic Medical Sciences, Network Center and Department of Plastic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.|Cancer Institute, Key Laboratory of Zebrafish Modeling and Drug Screening for Human Diseases of Guangdong Higher Education Institutes, Department of Cell Biology, Southern Medical University, Guangzhou 510515, Guangzhou Biotechnology Center, Guangzhou, 510630, School of Basic Medical Sciences, Network Center and Department of Plastic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.|Cancer Institute, Key Laboratory of Zebrafish Modeling and Drug Screening for Human Diseases of Guangdong Higher Education Institutes, Department of Cell Biology, Southern Medical University, Guangzhou 510515, Guangzhou Biotechnology Center, Guangzhou, 510630, School of Basic Medical Sciences, Network Center and Department of Plastic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.|Cancer Institute, Key Laboratory of Zebrafish Modeling and Drug Screening for Human Diseases of Guangdong Higher Education Institutes, Department of Cell Biology, Southern Medical University, Guangzhou 510515, Guangzhou Biotechnology Center, Guangzhou, 510630, School of Basic Medical Sciences, Network Center and Department of Plastic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.|Cancer Institute, Key Laboratory of Zebrafish Modeling and Drug Screening for Human Diseases of Guangdong Higher Education Institutes, Department of Cell Biology, Southern Medical University, Guangzhou 510515, Guangzhou Biotechnology Center, Guangzhou, 510630, School of Basic Medical Sciences, Network Center and Department of Plastic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.|Cancer Institute, Key Laboratory of Zebrafish Modeling and Drug Screening for Human Diseases of Guangdong Higher Education Institutes, Department of Cell Biology, Southern Medical University, Guangzhou 510515, Guangzhou Biotechnology Center, Guangzhou, 510630, School of Basic Medical Sciences, Network Center and Department of Plastic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.|Cancer Institute, Key Laboratory of Zebrafish Modeling and Drug Screening for Human Diseases of Guangdong Higher Education Institutes, Department of Cell Biology, Southern Medical University, Guangzhou 510515, Guangzhou Biotechnology Center, Guangzhou, 510630, School of Basic Medical Sciences, Network Center and Department of Plastic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.|Cancer Institute, Key Laboratory of Zebrafish Modeling and Drug Screening for Human Diseases of Guangdong Higher Education Institutes, Department of Cell Biology, Southern Medical University, Guangzhou 510515, Guangzhou Biotechnology Center, Guangzhou, 510630, School of Basic Medical Sciences, Network Center and Department of Plastic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.|Cancer Institute, Key Laboratory of Zebrafish Modeling and Drug Screening for Human Diseases of Guangdong Higher Education Institutes, Department of Cell Biology, Southern Medical University, Guangzhou 510515, Guangzhou Biotechnology Center, Guangzhou, 510630, School of Basic Medical Sciences, Network Center and Department of Plastic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.|Cancer Institute, Key Laboratory of Zebrafish Modeling and Drug Screening for Human Diseases of Guangdong Higher Education Institutes, Department of Cell Biology, Southern Medical University, Guangzhou 510515, Guangzhou Biotechnology Center, Guangzhou, 510630, School of Basic Medical Sciences, Network Center and Department of Plastic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.', 'China|China|China|China|China|China|China|China|China|China|China', 42, 'Cluster Analysis|Data Mining|Gene Regulatory Networks|Genes|Humans|Internet|MEDLINE|Software', 'Journal Article', '10.1093/bioinformatics/btu241', '24764463', 'Identifying biological functions and molecular networks in a gene list and how the genes may relate to various topics is of considerable value to biomedical researchers. Here, we present a web-based text-mining server, GenCLiP 2.0, which can analyze human genes with enriched keywords and molecular interactions. Compared with other similar tools, GenCLiP 2.0 offers two unique features: (i) analysis of gene functions with free terms (i.e. any terms in the literature) generated by literature mining or provided by the user and (ii) accurate identification and integration of comprehensive molecular interactions from Medline abstracts, to construct molecular networks and subnetworks related to the free terms.'),
(78371, 2014, 'bio', 'ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging', 'Ovesnxc3xbd, Martin|Kxc5x99xc3xadxc5xbeek, Pavel|Borkovec, Josef|Svindrych, Zdenxc4x9bk|Hagen, Guy M', 'Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, Prague 12800, Czech Republic.|Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, Prague 12800, Czech Republic.|Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, Prague 12800, Czech Republic.|Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, Prague 12800, Czech Republic.|Institute of Cellular Biology and Pathology, First Faculty of Medicine, Charles University in Prague, Prague 12800, Czech Republic.', '-|-|-|-|-', 459, 'Algorithms|Computer Graphics|Image Processing, Computer-Assisted|Microscopy|Microscopy, Fluorescence|Monte Carlo Method|Software', 'Journal Article', '10.1093/bioinformatics/btu202', '24771516', 'ThunderSTORM is an open-source, interactive and modular plug-in for ImageJ designed for automated processing, analysis and visualization of data acquired by single-molecule localization microscopy methods such as photo-activated localization microscopy and stochastic optical reconstruction microscopy. ThunderSTORM offers an extensive collection of processing and post-processing methods so that users can easily adapt the process of analysis to their data. ThunderSTORM also offers a set of tools for creation of simulated data and quantitative performance evaluation of localization algorithms using Monte Carlo simulations.'),
(78372, 2014, 'bio', 'Redundancy-weighting for better inference of protein structural features', 'Yanover, Chen|Vanetik, Natalia|Levitt, Michael|Kolodny, Rachel|Keasar, Chen', 'Machine Learning for Healthcare and Life-Sciences, Analytics Department, IBM Research Laboratory, Haifa, 3490002, Department of Software Engineering, Shamoon College of Engineering, Beer-Sheva 84100, Israel, Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA, Department of Computer Science, University of Haifa, Mount Carmel, Haifa, 3498838 and Departments of Life Sciences and Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel.|Machine Learning for Healthcare and Life-Sciences, Analytics Department, IBM Research Laboratory, Haifa, 3490002, Department of Software Engineering, Shamoon College of Engineering, Beer-Sheva 84100, Israel, Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA, Department of Computer Science, University of Haifa, Mount Carmel, Haifa, 3498838 and Departments of Life Sciences and Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel.|Machine Learning for Healthcare and Life-Sciences, Analytics Department, IBM Research Laboratory, Haifa, 3490002, Department of Software Engineering, Shamoon College of Engineering, Beer-Sheva 84100, Israel, Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA, Department of Computer Science, University of Haifa, Mount Carmel, Haifa, 3498838 and Departments of Life Sciences and Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel.|Machine Learning for Healthcare and Life-Sciences, Analytics Department, IBM Research Laboratory, Haifa, 3490002, Department of Software Engineering, Shamoon College of Engineering, Beer-Sheva 84100, Israel, Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA, Department of Computer Science, University of Haifa, Mount Carmel, Haifa, 3498838 and Departments of Life Sciences and Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel.|Machine Learning for Healthcare and Life-Sciences, Analytics Department, IBM Research Laboratory, Haifa, 3490002, Department of Software Engineering, Shamoon College of Engineering, Beer-Sheva 84100, Israel, Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA, Department of Computer Science, University of Haifa, Mount Carmel, Haifa, 3498838 and Departments of Life Sciences and Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel.', 'Israel|Israel|Israel|Israel|Israel', 9, 'Amino Acids|Data Mining|Databases, Protein|Protein Conformation|Proteins', 'Journal Article', '10.1093/bioinformatics/btu242', '24771517', 'Structural knowledge, extracted from the Protein Data Bank (PDB), underlies numerous potential functions and prediction methods. The PDB, however, is highly biased: many proteins have more than one entry, while entire protein families are represented by a single structure, or even not at all. The standard solution to this problem is to limit the studies to non-redundant subsets of the PDB. While alleviating biases, this solution hides the many-to-many relations between sequences and structures. That is, non-redundant datasets conceal the diversity of sequences that share the same fold and the existence of multiple conformations for the same protein. A particularly disturbing aspect of non-redundant subsets is that they hardly benefit from the rapid pace of protein structure determination, as most newly solved structures fall within existing families.'),
(78373, 2014, 'bio', 'Modeling disease progression using dynamics of pathway connectivity', 'Ma, Xiaoke|Gao, Long|Tan, Kai', 'Department of Internal Medicine and Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA.|Department of Internal Medicine and Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA.|Department of Internal Medicine and Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA.', 'United States|United States|United States', 35, 'Algorithms|Breast Neoplasms|Disease Progression|Female|Gene Expression Profiling|Gene Regulatory Networks|Humans|Models, Genetic|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btu298', '24771518', 'Disease progression is driven by dynamic changes in both the activity and connectivity of molecular pathways. Understanding these dynamic events is critical for disease prognosis and effective treatment. Compared with activity dynamics, connectivity dynamics is poorly explored.'),
(78374, 2014, 'bio', 'WebProtégé: a collaborative Web-based platform for editing biomedical ontologies', 'Horridge, Matthew|Tudorache, Tania|Nuylas, Csongor|Vendetti, Jennifer|Noy, Natalya F|Musen, Mark A', 'Stanford Center for Biomedical Informatics Research, Stanford University, 1265 Welch Road, Stanford, CA 94305, USA.|Stanford Center for Biomedical Informatics Research, Stanford University, 1265 Welch Road, Stanford, CA 94305, USA.|Stanford Center for Biomedical Informatics Research, Stanford University, 1265 Welch Road, Stanford, CA 94305, USA.|Stanford Center for Biomedical Informatics Research, Stanford University, 1265 Welch Road, Stanford, CA 94305, USA.|Stanford Center for Biomedical Informatics Research, Stanford University, 1265 Welch Road, Stanford, CA 94305, USA.|Stanford Center for Biomedical Informatics Research, Stanford University, 1265 Welch Road, Stanford, CA 94305, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Biological Ontologies|Cooperative Behavior|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btu256', '24771560', 'WebProtégé is an open-source Web application for editing OWL 2 ontologies. It contains several features to aid collaboration, including support for the discussion of issues, change notification and revision-based change tracking. WebProtégé also features a simple user interface, which is geared towards editing the kinds of class descriptions and annotations that are prevalent throughout biomedical ontologies. Moreover, it is possible to configure the user interface using views that are optimized for editing Open Biomedical Ontology (OBO) class descriptions and metadata. Some of these views are shown in the Supplementary Material and can be seen in WebProtégé itself by configuring the project as an OBO project.'),
(78375, 2014, 'bio', 'EnsembleGASVR: a novel ensemble method for classifying missense single nucleotide polymorphisms', 'Rapakoulia, Trisevgeni|Theofilatos, Konstantinos|Kleftogiannis, Dimitrios|Likothanasis, Spiros|Tsakalidis, Athanasios|Mavroudi, Seferina', 'King Abdullah University of Science and Technology (KAUST), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal 23955-6900, Saudi Arabia, Computer Engineering and Informatics Department, University of Patras, Building B, Patras, 26504, Greece and Department of Social Work, School of Health Sciences, Technological Institute of Western Greece, Patras, Greece.|King Abdullah University of Science and Technology (KAUST), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal 23955-6900, Saudi Arabia, Computer Engineering and Informatics Department, University of Patras, Building B, Patras, 26504, Greece and Department of Social Work, School of Health Sciences, Technological Institute of Western Greece, Patras, Greece.|King Abdullah University of Science and Technology (KAUST), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal 23955-6900, Saudi Arabia, Computer Engineering and Informatics Department, University of Patras, Building B, Patras, 26504, Greece and Department of Social Work, School of Health Sciences, Technological Institute of Western Greece, Patras, Greece.|King Abdullah University of Science and Technology (KAUST), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal 23955-6900, Saudi Arabia, Computer Engineering and Informatics Department, University of Patras, Building B, Patras, 26504, Greece and Department of Social Work, School of Health Sciences, Technological Institute of Western Greece, Patras, Greece.|King Abdullah University of Science and Technology (KAUST), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal 23955-6900, Saudi Arabia, Computer Engineering and Informatics Department, University of Patras, Building B, Patras, 26504, Greece and Department of Social Work, School of Health Sciences, Technological Institute of Western Greece, Patras, Greece.|King Abdullah University of Science and Technology (KAUST), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal 23955-6900, Saudi Arabia, Computer Engineering and Informatics Department, University of Patras, Building B, Patras, 26504, Greece and Department of Social Work, School of Health Sciences, Technological Institute of Western Greece, Patras, GreeceKing Abdullah University of Science and Technology (KAUST), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal 23955-6900, Saudi Arabia, Computer Engineering and Informatics Department, University of Patras, Building B, Patras, 26504, Greece and Department of Social Work, School of Health Sciences, Technological Institute of Western Greece, Patras, Greece.', 'Greece|Greece|Greece|Greece|Greece|Greece', 6, 'Algorithms|Amino Acid Substitution|Humans|Mutation, Missense|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btu297', '24771561', 'Single nucleotide polymorphisms (SNPs) are considered the most frequently occurring DNA sequence variations. Several computational methods have been proposed for the classification of missense SNPs to neutral and disease associated. However, existing computational approaches fail to select relevant features by choosing them arbitrarily without sufficient documentation. Moreover, they are limited to the problem of missing values, imbalance between the learning datasets and most of them do not support their predictions with confidence scores.'),
(78376, 2014, 'bio', 'Power analysis and sample size estimation for sequence-based association studies', 'Wang, Gao T|Li, Biao|Santos-Cortez, Regie P Lyn|Peng, Bo|Leal, Suzanne M', 'Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine and Department of Bioinformatics and Computational Biology, The University of Texas, M D Anderson Cancer Center, Houston, TX 77030, USA.|Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine and Department of Bioinformatics and Computational Biology, The University of Texas, M D Anderson Cancer Center, Houston, TX 77030, USA.|Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine and Department of Bioinformatics and Computational Biology, The University of Texas, M D Anderson Cancer Center, Houston, TX 77030, USA.|Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine and Department of Bioinformatics and Computational Biology, The University of Texas, M D Anderson Cancer Center, Houston, TX 77030, USA.|Center for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine and Department of Bioinformatics and Computational Biology, The University of Texas, M D Anderson Cancer Center, Houston, TX 77030, USA.', 'United States|United States|United States|United States|United States', 0, 'Alleles|Data Interpretation, Statistical|Disease|Genetic Association Studies|Genetic Variation|Humans|Phenotype|Sample Size|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu296', '24778108', 'Statistical methods have been developed to test for complex trait rare variant (RV) associations, in which variants are aggregated across a region, which is typically a gene. Power analysis and sample size estimation for sequence-based RV association studies are challenging because of the necessity to realistically model the underlying allelic architecture of complex diseases within a suitable analytical framework to assess the performance of a variety of RV association methods in an unbiased manner.'),
(78377, 2014, 'bio', 'Regulatory interactions maintaining self-renewal of human embryonic stem cells as revealed through a systems analysis of PI3K/AKT pathway', 'Mathew, Shibin|Sundararaj, Sankaramanivel|Mamiya, Hikaru|Banerjee, Ipsita', 'Department of Chemical and Petroleum Engineering, University of Pittsburgh, PA 15261, Department of Bioengineering and McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.|Department of Chemical and Petroleum Engineering, University of Pittsburgh, PA 15261, Department of Bioengineering and McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.|Department of Chemical and Petroleum Engineering, University of Pittsburgh, PA 15261, Department of Bioengineering and McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.|Department of Chemical and Petroleum Engineering, University of Pittsburgh, PA 15261, Department of Bioengineering and McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USADepartment of Chemical and Petroleum Engineering, University of Pittsburgh, PA 15261, Department of Bioengineering and McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USADepartment of Chemical and Petroleum Engineering, University of Pittsburgh, PA 15261, Department of Bioengineering and McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.', 'United States|United States|United States|United States', 12, 'Embryonic Stem Cells|Feedback, Physiological|Humans|Models, Biological|Phosphatidylinositol 3-Kinases|Phosphatidylinositol Phosphates|Proto-Oncogene Proteins c-akt|Signal Transduction|Systems Analysis', 'Journal Article', '10.1093/bioinformatics/btu209', '24778109', 'Maintenance of the self-renewal state in human embryonic stem cells (hESCs) is the foremost critical step for regenerative therapy applications. The insulin-mediated PI3K/AKT pathway is well appreciated as being the central pathway supporting hESC self-renewal, however, the regulatory interactions in the pathway that maintain cell state are not yet known. Identification of these regulatory pathway components will be critical for designing targeted interventions to facilitate a completely defined platform for hESC propagation and differentiation. Here, we have developed a systems analysis approach to identify regulatory components that control PI3K/AKT pathway in self-renewing hESCs.'),
(78378, 2014, 'bio', 'dbGSH: a database of S-glutathionylation', 'Chen, Yi-Ju|Lu, Cheng-Tsung|Lee, Tzong-Yi|Chen, Yu-Ju', 'Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan and Department of Computer Science and Engineering, Yuan Ze University, Taoyuan 320, Taiwan.|Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan and Department of Computer Science and Engineering, Yuan Ze University, Taoyuan 320, Taiwan.|Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan and Department of Computer Science and Engineering, Yuan Ze University, Taoyuan 320, Taiwan.|Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan and Department of Computer Science and Engineering, Yuan Ze University, Taoyuan 320, Taiwan.', '-|-|-|-', 36, 'Amino Acid Motifs|Cysteine|Databases, Protein|Glutathione|Peptides|Protein Processing, Post-Translational|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1093/bioinformatics/btu301', '24790154', 'S-glutathionylation, the reversible protein posttranslational modification (PTM) that generates a mixed disulfide bond between glutathione and cysteine residue, critically regulates protein activity, stability and redox regulation. Due to its importance in regulating oxidative/nitrosative stress and balance in cellular response, a number of methods have been rapidly developed to study S-glutathionylation, thus expanding the dataset of experimentally determined glutathionylation sites. However, there is currently no database dedicated to the integration of all experimentally verified S-glutathionylation sites along with their characteristics or structural or functional information. Thus, the dbGSH database has been created to integrate all available datasets and to provide the relevant structural analysis. As of January 31, 2014, dbGSH has manually collected >2200 experimentally verified S-glutathionylated peptides from 169 research articles using a text-mining approach. To solve the problem of heterogeneity of the data collected from different sources, the sequence identity of the reported S-glutathionylated peptides is mapped to UniProtKB protein entries. To delineate the structural correlations and consensus motifs of these S-glutathionylation sites, the dbGSH database also provides structural and functional analyses, including the motifs of substrate sites, solvent accessibility, protein secondary and tertiary structures, protein domains and gene ontology.'),
(78379, 2014, 'bio', 'Detecting clustering and ordering binding patterns among transcription factors via point process models', 'Cha, Maria|Zhou, Qing', 'Department of Statistics, University of California, Los Angeles, CA 90095, USA.|Department of Statistics, University of California, Los Angeles, CA 90095, USA.', 'United States|United States', 0, 'Animals|Binding Sites|Chromatin Immunoprecipitation|Cluster Analysis|Embryonic Stem Cells|Mice|Models, Statistical|Protein Binding|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btu303', '24790155', 'Recent development in ChIP-Seq technology has generated binding data for many transcription factors (TFs) in various cell types and cellular conditions. This opens great opportunities for studying combinatorial binding patterns among a set of TFs active in a particular cellular condition, which is a key component for understanding the interaction between TFs in gene regulation.'),
(78380, 2014, 'bio', 'Vacceed: a high-throughput in silico vaccine candidate discovery pipeline for eukaryotic pathogens based on reverse vaccinology', 'Goodswen, Stephen J|Kennedy, Paul J|Ellis, John T', 'School of Medical and Molecular Biosciences, The ithree Institute and Faculty of Engineering and Information Technology, School of Software, The Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney (UTS), Ultimo, NSW 2007, Australia.|School of Medical and Molecular Biosciences, The ithree Institute and Faculty of Engineering and Information Technology, School of Software, The Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney (UTS), Ultimo, NSW 2007, Australia.|School of Medical and Molecular Biosciences, The ithree Institute and Faculty of Engineering and Information Technology, School of Software, The Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney (UTS), Ultimo, NSW 2007, Australia.', 'Australia|Australia|Australia', 25, 'Algorithms|Artificial Intelligence|Computer Simulation|Sequence Analysis, Protein|Software|Vaccines', 'Journal Article', '10.1093/bioinformatics/btu300', '24790156', 'We present Vacceed, a highly configurable and scalable framework designed to automate the process of high-throughput in silico vaccine candidate discovery for eukaryotic pathogens. Given thousands of protein sequences from the target pathogen as input, the main output is a ranked list of protein candidates determined by a set of machine learning algorithms. Vacceed has the potential to save time and money by reducing the number of false candidates allocated for laboratory validation. Vacceed, if required, can also predict protein sequences from the pathogens genome.'),
(78381, 2014, 'bio', 'ReadXplorer--visualization and analysis of mapped sequences', 'Hilker, Rolf|Stadermann, Kai Bernd|Doppmeier, Daniel|Kalinowski, Jörn|Stoye, Jens|Straube, Jasmin|Winnebald, Jörn|Goesmann, Alexander', 'Institute of Medical Microbiology, Justus-Liebig-University, 35392 Giessen, Germany, Faculty of Biology, Institute for Bioinformatics, Center for Biotechnology, Computational Genomics, Center for Biotechnology, Technology Platform Genomics, Center for Biotechnology, Genome Informatics, Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany and Bioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, 35392 Giessen, Germany.|Institute of Medical Microbiology, Justus-Liebig-University, 35392 Giessen, Germany, Faculty of Biology, Institute for Bioinformatics, Center for Biotechnology, Computational Genomics, Center for Biotechnology, Technology Platform Genomics, Center for Biotechnology, Genome Informatics, Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany and Bioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, 35392 Giessen, GermanyInstitute of Medical Microbiology, Justus-Liebig-University, 35392 Giessen, Germany, Faculty of Biology, Institute for Bioinformatics, Center for Biotechnology, Computational Genomics, Center for Biotechnology, Technology Platform Genomics, Center for Biotechnology, Genome Informatics, Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany and Bioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, 35392 Giessen, Germany.|Institute of Medical Microbiology, Justus-Liebig-University, 35392 Giessen, Germany, Faculty of Biology, Institute for Bioinformatics, Center for Biotechnology, Computational Genomics, Center for Biotechnology, Technology Platform Genomics, Center for Biotechnology, Genome Informatics, Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany and Bioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, 35392 Giessen, Germany.|Institute of Medical Microbiology, Justus-Liebig-University, 35392 Giessen, Germany, Faculty of Biology, Institute for Bioinformatics, Center for Biotechnology, Computational Genomics, Center for Biotechnology, Technology Platform Genomics, Center for Biotechnology, Genome Informatics, Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany and Bioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, 35392 Giessen, Germany.|Institute of Medical Microbiology, Justus-Liebig-University, 35392 Giessen, Germany, Faculty of Biology, Institute for Bioinformatics, Center for Biotechnology, Computational Genomics, Center for Biotechnology, Technology Platform Genomics, Center for Biotechnology, Genome Informatics, Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany and Bioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, 35392 Giessen, GermanyInstitute of Medical Microbiology, Justus-Liebig-University, 35392 Giessen, Germany, Faculty of Biology, Institute for Bioinformatics, Center for Biotechnology, Computational Genomics, Center for Biotechnology, Technology Platform Genomics, Center for Biotechnology, Genome Informatics, Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany and Bioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, 35392 Giessen, Germany.|Institute of Medical Microbiology, Justus-Liebig-University, 35392 Giessen, Germany, Faculty of Biology, Institute for Bioinformatics, Center for Biotechnology, Computational Genomics, Center for Biotechnology, Technology Platform Genomics, Center for Biotechnology, Genome Informatics, Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany and Bioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, 35392 Giessen, Germany.|Institute of Medical Microbiology, Justus-Liebig-University, 35392 Giessen, Germany, Faculty of Biology, Institute for Bioinformatics, Center for Biotechnology, Computational Genomics, Center for Biotechnology, Technology Platform Genomics, Center for Biotechnology, Genome Informatics, Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany and Bioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, 35392 Giessen, Germany.|Institute of Medical Microbiology, Justus-Liebig-University, 35392 Giessen, Germany, Faculty of Biology, Institute for Bioinformatics, Center for Biotechnology, Computational Genomics, Center for Biotechnology, Technology Platform Genomics, Center for Biotechnology, Genome Informatics, Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany and Bioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, 35392 Giessen, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 68, 'Computer Graphics|Gene Expression Profiling|Genomics|High-Throughput Nucleotide Sequencing|Operon|Polymorphism, Genetic|Polymorphism, Single Nucleotide|RNA|Sequence Alignment|Sequence Analysis, DNA|Software|Transcription Initiation Site', 'Journal Article', '10.1093/bioinformatics/btu205', '24790157', 'Fast algorithms and well-arranged visualizations are required for the comprehensive analysis of the ever-growing size of genomic and transcriptomic next-generation sequencing data.'),
(78382, 2014, 'bio', 'A fast and powerful tree-based association test for detecting complex joint effects in case-control studies', 'Zhang, Han|Wheeler, William|Wang, Zhaoming|Taylor, Philip R|Yu, Kai', 'Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA, Information Management Services, Inc., Silver Spring, Maryland 20904, USA, and Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland 20877, USA.|Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA, Information Management Services, Inc., Silver Spring, Maryland 20904, USA, and Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland 20877, USA.|Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA, Information Management Services, Inc., Silver Spring, Maryland 20904, USA, and Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland 20877, USABiostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA, Information Management Services, Inc., Silver Spring, Maryland 20904, USA, and Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland 20877, USA.|Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA, Information Management Services, Inc., Silver Spring, Maryland 20904, USA, and Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland 20877, USA.|Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA, Information Management Services, Inc., Silver Spring, Maryland 20904, USA, and Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland 20877, USA.', 'United States|United States|United States|United States|United States', 3, 'Algorithms|Carcinoma, Squamous Cell|Case-Control Studies|Computational Biology|Cyclin-Dependent Kinase Inhibitor p15|Decision Trees|Esophageal Neoplasms|Genetic Predisposition to Disease|Genotype|Humans|Logistic Models|Polymorphism, Single Nucleotide|Time Factors', 'Journal Article', '10.1093/bioinformatics/btu186', '24794927', 'Multivariate tests derived from the logistic regression model are widely used to assess the joint effect of multiple predictors on a disease outcome in case-control studies. These tests become less optimal if the joint effect cannot be approximated adequately by the additive model. The tree-structure model is an attractive alternative, as it is more apt to capture non-additive effects. However, the tree model is used most commonly for prediction and seldom for hypothesis testing, mainly because of the computational burden associated with the resampling-based procedure required for estimating the significance level.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78383, 2014, 'bio', 'A systems-level integrative framework for genome-wide DNA methylation and gene expression data identifies differential gene expression modules under epigenetic control', 'Jiao, Yinming|Widschwendter, Martin|Teschendorff, Andrew E', 'Computational Systems Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, Department of Womens Cancer, UCL Elizabeth Garrett Anderson Institute for Womens Health and Statistical Genomics Group, Paul OGorman Building, UCL Cancer Institute, University College London, London WC1E 6BT, UK.|Computational Systems Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, Department of Womens Cancer, UCL Elizabeth Garrett Anderson Institute for Womens Health and Statistical Genomics Group, Paul OGorman Building, UCL Cancer Institute, University College London, London WC1E 6BT, UK.|Computational Systems Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, Department of Womens Cancer, UCL Elizabeth Garrett Anderson Institute for Womens Health and Statistical Genomics Group, Paul OGorman Building, UCL Cancer Institute, University College London, London WC1E 6BT, UKComputational Systems Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China, Department of Womens Cancer, UCL Elizabeth Garrett Anderson Institute for Womens Health and Statistical Genomics Group, Paul OGorman Building, UCL Cancer Institute, University College London, London WC1E 6BT, UK.', 'China|China|China', 75, 'Algorithms|Cell Differentiation|DNA Methylation|Endometrial Neoplasms|Epigenesis, Genetic|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Genome, Human|Humans|Protein Interaction Mapping|Transcription Initiation Site', 'Journal Article', '10.1093/bioinformatics/btu316', '24794928', 'There is a growing number of studies generating matched Illumina Infinium HumanMethylation450 and gene expression data, yet there is a corresponding shortage of statistical tools aimed at their integrative analysis. Such integrative tools are important for the discovery of epigenetically regulated gene modules or molecular pathways, which play key roles in cellular differentiation and disease.'),
(78384, 2014, 'bio', 'A comparison of algorithms for the pairwise alignment of biological networks', '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', 73, 'Algorithms|Animals|Humans|Protein Interaction Mapping|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btu307', '24794929', 'As biological inquiry produces ever more network data, such as protein-protein interaction networks, gene regulatory networks and metabolic networks, many algorithms have been proposed for the purpose of pairwise network alignment-finding a mapping from the nodes of one network to the nodes of another in such a way that the mapped nodes can be considered to correspond with respect to both their place in the network topology and their biological attributes. This technique is helpful in identifying previously undiscovered homologies between proteins of different species and revealing functionally similar subnetworks. In the past few years, a wealth of different aligners has been published, but few of them have been compared with one another, and no comprehensive review of these algorithms has yet appeared.'),
(78385, 2014, 'bio', 'Structural and energetic determinants of tyrosylprotein sulfotransferase sulfation specificity', 'Nedumpully-Govindan, Praveen|Li, Lin|Alexov, Emil G|Blenner, Mark A|Ding, Feng', 'Department of Physics and Astronomy and Department of Chemical and Biomolecular Engineering, Clemson University, Clemson, SC 29634, USA.|Department of Physics and Astronomy and Department of Chemical and Biomolecular Engineering, Clemson University, Clemson, SC 29634, USA.|Department of Physics and Astronomy and Department of Chemical and Biomolecular Engineering, Clemson University, Clemson, SC 29634, USA.|Department of Physics and Astronomy and Department of Chemical and Biomolecular Engineering, Clemson University, Clemson, SC 29634, USA.|Department of Physics and Astronomy and Department of Chemical and Biomolecular Engineering, Clemson University, Clemson, SC 29634, USA.', 'United States|United States|United States|United States|United States', 4, 'HIV Antibodies|Membrane Proteins|Models, Molecular|Peptides|Protein Binding|Protein Processing, Post-Translational|Protein Unfolding|Static Electricity|Sulfotransferases|Tyrosine', 'Journal Article', '10.1093/bioinformatics/btu309', '24794930', 'Tyrosine sulfation is a type of post-translational modification (PTM) catalyzed by tyrosylprotein sulfotransferases (TPST). The modification plays a crucial role in mediating protein-protein interactions in many biologically important processes. There is no well-defined sequence motif for TPST sulfation, and the underlying determinants of TPST sulfation specificity remains elusive. Here, we perform molecular modeling to uncover the structural and energetic determinants of TPST sulfation specificity.'),
(78386, 2014, 'bio', 'MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments', 'Choi, Meena|Chang, Ching-Yun|Clough, Timothy|Broudy, Daniel|Killeen, Trevor|MacLean, Brendan|Vitek, Olga', 'Department of Statistics, Purdue University, West Lafayette, IN, Department of Genome Sciences, University of Washington, Seattle, WA 98195 and Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA.|Department of Statistics, Purdue University, West Lafayette, IN, Department of Genome Sciences, University of Washington, Seattle, WA 98195 and Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA.|Department of Statistics, Purdue University, West Lafayette, IN, Department of Genome Sciences, University of Washington, Seattle, WA 98195 and Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA.|Department of Statistics, Purdue University, West Lafayette, IN, Department of Genome Sciences, University of Washington, Seattle, WA 98195 and Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA.|Department of Statistics, Purdue University, West Lafayette, IN, Department of Genome Sciences, University of Washington, Seattle, WA 98195 and Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA.|Department of Statistics, Purdue University, West Lafayette, IN, Department of Genome Sciences, University of Washington, Seattle, WA 98195 and Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA.|Department of Statistics, Purdue University, West Lafayette, IN, Department of Genome Sciences, University of Washington, Seattle, WA 98195 and Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA Department of Statistics, Purdue University, West Lafayette, IN, Department of Genome Sciences, University of Washington, Seattle, WA 98195 and Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA.', 'United States|United States|United States|United States|United States|United States|United States', 294, 'Data Interpretation, Statistical|Mass Spectrometry|Peptides|Proteins|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btu305', '24794931', 'MSstats is an R package for statistical relative quantification of proteins and peptides in mass spectrometry-based proteomics. Version 2.0 of MSstats supports label-free and label-based experimental workflows and data-dependent, targeted and data-independent spectral acquisition. It takes as input identified and quantified spectral peaks, and outputs a list of differentially abundant peptides or proteins, or summaries of peptide or protein relative abundance. MSstats relies on a flexible family of linear mixed models.'),
(78387, 2014, 'bio', 'Bioclojure: a functional library for the manipulation of biological sequences', 'Plieskatt, Jordan|Rinaldi, Gabriel|Brindley, Paul J|Jia, Xinying|Potriquet, Jeremy|Bethony, Jeffrey|Mulvenna, Jason', 'Department of Microbiology, Immunology and Tropical Medicine, Research Center for Neglected Diseases of Poverty, School of Medicine and Health Sciences, George Washington University, Washington, DC, 20052, USA, QIMR Berghofer Medical Research Institute, Infectious Disease and Cancer and The University of Queensland, School of Biomedical Sciences, Brisbane, Queensland, 4072, Australia Department of Microbiology, Immunology and Tropical Medicine, Research Center for Neglected Diseases of Poverty, School of Medicine and Health Sciences, George Washington University, Washington, DC, 20052, USA, QIMR Berghofer Medical Research Institute, Infectious Disease and Cancer and The University of Queensland, School of Biomedical Sciences, Brisbane, Queensland, 4072, Australia.|Department of Microbiology, Immunology and Tropical Medicine, Research Center for Neglected Diseases of Poverty, School of Medicine and Health Sciences, George Washington University, Washington, DC, 20052, USA, QIMR Berghofer Medical Research Institute, Infectious Disease and Cancer and The University of Queensland, School of Biomedical Sciences, Brisbane, Queensland, 4072, Australia Department of Microbiology, Immunology and Tropical Medicine, Research Center for Neglected Diseases of Poverty, School of Medicine and Health Sciences, George Washington University, Washington, DC, 20052, USA, QIMR Berghofer Medical Research Institute, Infectious Disease and Cancer and The University of Queensland, School of Biomedical Sciences, Brisbane, Queensland, 4072, Australia.|Department of Microbiology, Immunology and Tropical Medicine, Research Center for Neglected Diseases of Poverty, School of Medicine and Health Sciences, George Washington University, Washington, DC, 20052, USA, QIMR Berghofer Medical Research Institute, Infectious Disease and Cancer and The University of Queensland, School of Biomedical Sciences, Brisbane, Queensland, 4072, Australia Department of Microbiology, Immunology and Tropical Medicine, Research Center for Neglected Diseases of Poverty, School of Medicine and Health Sciences, George Washington University, Washington, DC, 20052, USA, QIMR Berghofer Medical Research Institute, Infectious Disease and Cancer and The University of Queensland, School of Biomedical Sciences, Brisbane, Queensland, 4072, Australia.|Department of Microbiology, Immunology and Tropical Medicine, Research Center for Neglected Diseases of Poverty, School of Medicine and Health Sciences, George Washington University, Washington, DC, 20052, USA, QIMR Berghofer Medical Research Institute, Infectious Disease and Cancer and The University of Queensland, School of Biomedical Sciences, Brisbane, Queensland, 4072, Australia.|Department of Microbiology, Immunology and Tropical Medicine, Research Center for Neglected Diseases of Poverty, School of Medicine and Health Sciences, George Washington University, Washington, DC, 20052, USA, QIMR Berghofer Medical Research Institute, Infectious Disease and Cancer and The University of Queensland, School of Biomedical Sciences, Brisbane, Queensland, 4072, Australia.|Department of Microbiology, Immunology and Tropical Medicine, Research Center for Neglected Diseases of Poverty, School of Medicine and Health Sciences, George Washington University, Washington, DC, 20052, USA, QIMR Berghofer Medical Research Institute, Infectious Disease and Cancer and The University of Queensland, School of Biomedical Sciences, Brisbane, Queensland, 4072, Australia.|Department of Microbiology, Immunology and Tropical Medicine, Research Center for Neglected Diseases of Poverty, School of Medicine and Health Sciences, George Washington University, Washington, DC, 20052, USA, QIMR Berghofer Medical Research Institute, Infectious Disease and Cancer and The University of Queensland, School of Biomedical Sciences, Brisbane, Queensland, 4072, Australia Department of Microbiology, Immunology and Tropical Medicine, Research Center for Neglected Diseases of Poverty, School of Medicine and Health Sciences, George Washington University, Washington, DC, 20052, USA, QIMR Berghofer Medical Research Institute, Infectious Disease and Cancer and The University of Queensland, School of Biomedical Sciences, Brisbane, Queensland, 4072, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia', 5, 'High-Throughput Nucleotide Sequencing|Programming Languages|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btu311', '24794932', 'BioClojure is an open-source library for the manipulation of biological sequence data written in the language Clojure. BioClojure aims to provide a functional framework for the processing of biological sequence data that provides simple mechanisms for concurrency and lazy evaluation of large datasets.'),
(78388, 2014, 'bio', 'unifiedWMWqPCR: the unified Wilcoxon-Mann-Whitney test for analyzing RT-qPCR data in R', 'De Neve, Jan|Meys, Joris|Ottoy, Jean-Pierre|Clement, Lieven|Thas, Olivier', 'Department of Mathematical Modelling, Statistics and Bioinformatics, Department of Applied Mathematics, Computer Science and Statistics, Ghent University, B-9000 Gent, Belgium and National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, University of Wollongong, NSW 2522, Australia.|Department of Mathematical Modelling, Statistics and Bioinformatics, Department of Applied Mathematics, Computer Science and Statistics, Ghent University, B-9000 Gent, Belgium and National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, University of Wollongong, NSW 2522, Australia.|Department of Mathematical Modelling, Statistics and Bioinformatics, Department of Applied Mathematics, Computer Science and Statistics, Ghent University, B-9000 Gent, Belgium and National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, University of Wollongong, NSW 2522, Australia.|Department of Mathematical Modelling, Statistics and Bioinformatics, Department of Applied Mathematics, Computer Science and Statistics, Ghent University, B-9000 Gent, Belgium and National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, University of Wollongong, NSW 2522, Australia.|Department of Mathematical Modelling, Statistics and Bioinformatics, Department of Applied Mathematics, Computer Science and Statistics, Ghent University, B-9000 Gent, Belgium and National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, University of Wollongong, NSW 2522, Australia Department of Mathematical Modelling, Statistics and Bioinformatics, Department of Applied Mathematics, Computer Science and Statistics, Ghent University, B-9000 Gent, Belgium and National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, University of Wollongong, NSW 2522, Australia.', 'Australia|Australia|Australia|Australia|Australia', 6, 'Humans|MicroRNAs|Neuroblastoma|Real-Time Polymerase Chain Reaction|Software|Statistics, Nonparametric', 'Journal Article', '10.1093/bioinformatics/btu313', '24794933', 'Recently, De Neve et al. proposed a modification of the Wilcoxon-Mann-Whitney (WMW) test for assessing differential expression based on RT-qPCR data. Their test, referred to as the unified WMW (uWMW) test, incorporates a robust and intuitive normalization and quantifies the probability that the expression from one treatment group exceeds the expression from another treatment group. However, no software package for this test was available yet.'),
(78389, 2014, 'bio', 'Mirin: identifying microRNA regulatory modules in protein-protein interaction networks', 'Yang, Ken-Chi|Hsu, Chia-Lang|Lin, Chen-Ching|Juan, Hsueh-Fen|Huang, Hsuan-Cheng', 'Institute of Biomedical Informatics, Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei 112, Department of Life Science, Graduate Institute of Biomedical Electronics and Bioinformatics and Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 106, Taiwan.|Institute of Biomedical Informatics, Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei 112, Department of Life Science, Graduate Institute of Biomedical Electronics and Bioinformatics and Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 106, Taiwan.|Institute of Biomedical Informatics, Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei 112, Department of Life Science, Graduate Institute of Biomedical Electronics and Bioinformatics and Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 106, Taiwan Institute of Biomedical Informatics, Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei 112, Department of Life Science, Graduate Institute of Biomedical Electronics and Bioinformatics and Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 106, Taiwan.|Institute of Biomedical Informatics, Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei 112, Department of Life Science, Graduate Institute of Biomedical Electronics and Bioinformatics and Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 106, Taiwan Institute of Biomedical Informatics, Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei 112, Department of Life Science, Graduate Institute of Biomedical Electronics and Bioinformatics and Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 106, Taiwan Institute of Biomedical Informatics, Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei 112, Department of Life Science, Graduate Institute of Biomedical Electronics and Bioinformatics and Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 106, Taiwan.|Institute of Biomedical Informatics, Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei 112, Department of Life Science, Graduate Institute of Biomedical Electronics and Bioinformatics and Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 106, Taiwan.', '-|-|-|-|-', 5, 'Breast Neoplasms|Female|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|MicroRNAs|Protein Interaction Mapping|RNA, Messenger|Software', 'Journal Article', '10.1093/bioinformatics/btu306', '24794934', 'Exploring microRNA (miRNA) regulations and protein-protein interactions could reveal the molecular mechanisms responsible for complex biological processes. Mirin is a web-based application suitable for identifying functional modules from protein-protein interaction networks regulated by aberrant miRNAs under user-defined biological conditions such as cancers. The analysis involves combining miRNA regulations, protein-protein interactions between target genes, as well as mRNA and miRNA expression profiles provided by users. Mirin has successfully uncovered oncomirs and their regulatory networks in various cancers, such as gastric and breast cancer.'),
(78390, 2014, 'bio', 'fastGapFill: efficient gap filling in metabolic networks', 'Thiele, Ines|Vlassis, Nikos|Fleming, Ronan M T', 'Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg, L-4362.|Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg, L-4362.|Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg, L-4362.', 'Luxembourg|Luxembourg|Luxembourg', 54, 'Algorithms|Genome|Metabolic Networks and Pathways|Software', 'Journal Article', '10.1093/bioinformatics/btu321', '24812336', 'Genome-scale metabolic reconstructions summarize current knowledge about a target organism in a structured manner and as such highlight missing information. Such gaps can be filled algorithmically. Scalability limitations of available algorithms for gap filling hinder their application to compartmentalized reconstructions.'),
(78391, 2014, 'bio', 'SEK: sparsity exploiting k-mer-based estimation of bacterial community composition', 'Chatterjee, Saikat|Koslicki, David|Dong, Siyuan|Innocenti, Nicolas|Cheng, Lu|Lan, Yueheng|Vehkaperä, Mikko|Skoglund, Mikael|Rasmussen, Lars K|Aurell, Erik|Corander, Jukka', 'Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland.|Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland.|Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland.|Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland.|Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland.|Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland.|Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland.|Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland.|Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland.|Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland.|Department of Communication Theory, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics, Oregon State University, Corvallis, OR, USA, Systems Biology program, KTH Royal Institute of Technology, Sweden, Aalto University, Esbo, Finland, Department of Computational Biology, KTH Royal Institute of Technology, Stockholm, Sweden, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland, Department of Physics, Tsinghua University, Beijing, China, Department of Signal Processing and Department of Information and Computer Science, Aalto University, Esbo, Finland.', 'China|China|China|China|China|China|China|China|China|China|China', 6, 'Algorithms|Bacteria|High-Throughput Nucleotide Sequencing|Metagenomics|Models, Statistical|RNA, Ribosomal, 16S|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu320', '24812337', 'Estimation of bacterial community composition from a high-throughput sequenced sample is an important task in metagenomics applications. As the sample sequence data typically harbors reads of variable lengths and different levels of biological and technical noise, accurate statistical analysis of such data is challenging. Currently popular estimation methods are typically time-consuming in a desktop computing environment.'),
(78392, 2014, 'bio', 'RNASeqGUI: a GUI for analysing RNA-Seq data', 'Russo, Francesco|Angelini, Claudia', 'Istituto per le Applicazoni del Calcolo, CNR, 80131, Napoli, Italy.|Istituto per le Applicazoni del Calcolo, CNR, 80131, Napoli, Italy.', 'Italy|Italy', 23, 'Gene Expression Profiling|Sequence Analysis, RNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu308', '24812338', 'We present RNASeqGUI R package, a graphical user interface (GUI) for the identification of differentially expressed genes across multiple biological conditions. This R package includes some well-known RNA-Seq tools, available at www.bioconductor.org. RNASeqGUI package is not just a collection of some known methods and functions, but it is designed to guide the user during the entire analysis process. RNASeqGUI package is mainly addressed to those users who have little experience with command-line software. Therefore, thanks to RNASeqGUI, they can conduct analogous analyses using this simple graphical interface. Moreover, RNASeqGUI is also helpful for those who are expert R-users because it speeds up the usage of the included RNASeq methods drastically.'),
(78393, 2014, 'bio', 'Bioinformatics-driven discovery of rational combination for overcoming EGFR-mutant lung cancer resistance to EGFR therapy', 'Kim, Jihye|Vasu, Vihas T|Mishra, Rangnath|Singleton, Katherine R|Yoo, Minjae|Leach, Sonia M|Farias-Hesson, Eveline|Mason, Robert J|Kang, Jaewoo|Ramamoorthy, Preveen|Kern, Jeffrey A|Heasley, Lynn E|Finigan, James H|Tan, Aik Choon', 'Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.|Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.', '-|-|-|-|-|-|-|-|-|-|-|-|-|-', 19, 'Aniline Compounds|Antineoplastic Combined Chemotherapy Protocols|Carcinoma, Non-Small-Cell Lung|Cell Line, Tumor|Computational Biology|Drug Resistance, Neoplasm|ErbB Receptors|Gefitinib|Humans|Lung Neoplasms|Mutation|Nitriles|Protein Kinase Inhibitors|Protein Kinases|Quinazolines|Quinolines|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btu323', '24812339', 'Non-small-cell lung cancer (NSCLC) is the leading cause of cancer death in the United States. Targeted tyrosine kinase inhibitors (TKIs) directed against the epidermal growth factor receptor (EGFR) have been widely and successfully used in treating NSCLC patients with activating EGFR mutations. Unfortunately, the duration of response is short-lived, and all patients eventually relapse by acquiring resistance mechanisms.'),
(78394, 2014, 'bio', 'Inferring the paths of somatic evolution in cancer', 'Misra, Navodit|Szczurek, Ewa|Vingron, Martin', 'Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, D-14195 Berlin, Germany and Department of Biosystems Science and Engineering, ETH Zurich and Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland.|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, D-14195 Berlin, Germany and Department of Biosystems Science and Engineering, ETH Zurich and Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, D-14195 Berlin, Germany and Department of Biosystems Science and Engineering, ETH Zurich and Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland.|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, D-14195 Berlin, Germany and Department of Biosystems Science and Engineering, ETH Zurich and Swiss Institute of Bioinformatics, CH-4058 Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland', 17, 'Algorithms|Bayes Theorem|Clonal Evolution|Genes, Neoplasm|Genotype|Humans|Mutation|Neoplasms', 'Journal Article', '10.1093/bioinformatics/btu319', '24812340', 'Cancer cell genomes acquire several genetic alterations during somatic evolution from a normal cell type. The relative order in which these mutations accumulate and contribute to cell fitness is affected by epistatic interactions. Inferring their evolutionary history is challenging because of the large number of mutations acquired by cancer cells as well as the presence of unknown epistatic interactions.'),
(78395, 2014, 'bio', 'Probabilistic partitioning methods to find significant patterns in ChIP-Seq data', 'Nair, Nishanth Ulhas|Kumar, Sunil|Moret, Bernard M E|Bucher, Philipp', 'Laboratory for Computational Biology and Bioinformatics, School of Computer and Communication Sciences, Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne and Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland.|Laboratory for Computational Biology and Bioinformatics, School of Computer and Communication Sciences, Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne and Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland.|Laboratory for Computational Biology and Bioinformatics, School of Computer and Communication Sciences, Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne and Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland Laboratory for Computational Biology and Bioinformatics, School of Computer and Communication Sciences, Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne and Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland.|Laboratory for Computational Biology and Bioinformatics, School of Computer and Communication Sciences, Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne and Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland Laboratory for Computational Biology and Bioinformatics, School of Computer and Communication Sciences, Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne and Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 5, 'Algorithms|Chromatin Immunoprecipitation|High-Throughput Nucleotide Sequencing|Histones|Humans|Nucleosomes|Probability|Promoter Regions, Genetic|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu318', '24812341', 'We have witnessed an enormous increase in ChIP-Seq data for histone modifications in the past few years. Discovering significant patterns in these data is an important problem for understanding biological mechanisms.'),
(78396, 2014, 'bio', 'PhenoNet: identification of key networks associated with disease phenotype', 'Ben-Hamo, Rotem|Gidoni, Moriah|Efroni, Sol', 'The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel.|The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel.|The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel.', 'Israel|Israel|Israel', 11, 'Algorithms|Female|Gene Expression|Gene Expression Profiling|Gene Regulatory Networks|Humans|Neoplasms|Phenotype|Protein Interaction Mapping|Triple Negative Breast Neoplasms', 'Journal Article', '10.1093/bioinformatics/btu199', '24812342', 'At the core of transcriptome analyses of cancer is a challenge to detect molecular differences affiliated with disease phenotypes. This approach has led to remarkable progress in identifying molecular signatures and in stratifying patients into clinical groups. Yet, despite this progress, many of the identified signatures are not robust enough to be clinically used and not consistent enough to provide a follow-up on molecular mechanisms.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78397, 2014, 'bio', 'GEPdb: a database for investigating the ternary association of genotype, gene expression and phenotype', 'Ryu, Daeun|Cho, SeongBeom|Kim, Hun|Lee, Sanghyuk|Kim, Wankyu', 'Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Division of Biomedical Informatics, National Institute of Health, Korea Center for Disease Control, Cheongwon 363-951 and Ewha Global Top5 Research Program, Ewha Womans University, Seoul 120-750, Republic of Korea.|Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Division of Biomedical Informatics, National Institute of Health, Korea Center for Disease Control, Cheongwon 363-951 and Ewha Global Top5 Research Program, Ewha Womans University, Seoul 120-750, Republic of Korea Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Division of Biomedical Informatics, National Institute of Health, Korea Center for Disease Control, Cheongwon 363-951 and Ewha Global Top5 Research Program, Ewha Womans University, Seoul 120-750, Republic of Korea.|Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Division of Biomedical Informatics, National Institute of Health, Korea Center for Disease Control, Cheongwon 363-951 and Ewha Global Top5 Research Program, Ewha Womans University, Seoul 120-750, Republic of Korea.|Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Division of Biomedical Informatics, National Institute of Health, Korea Center for Disease Control, Cheongwon 363-951 and Ewha Global Top5 Research Program, Ewha Womans University, Seoul 120-750, Republic of Korea Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Division of Biomedical Informatics, National Institute of Health, Korea Center for Disease Control, Cheongwon 363-951 and Ewha Global Top5 Research Program, Ewha Womans University, Seoul 120-750, Republic of Korea.|Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Division of Biomedical Informatics, National Institute of Health, Korea Center for Disease Control, Cheongwon 363-951 and Ewha Global Top5 Research Program, Ewha Womans University, Seoul 120-750, Republic of Korea Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Division of Biomedical Informatics, National Institute of Health, Korea Center for Disease Control, Cheongwon 363-951 and Ewha Global Top5 Research Program, Ewha Womans University, Seoul 120-750, Republic of Korea.', '-|-|-|-|-', 1, 'Chromosome Mapping|Databases, Genetic|Gene Expression|Genome-Wide Association Study|Genotype|HapMap Project|Humans|Linkage Disequilibrium|Phenotype|Polymorphism, Single Nucleotide|Quantitative Trait Loci', 'Journal Article', '10.1093/bioinformatics/btu240', '24812343', 'GEPdb integrates both genome-wide association studies and expression quantitative trait loci information, the two primary sources of genome-wide mapping for genotype-phenotype and genotype-expression associations together with phenotype-associated gene lists. The GEPdb provides simultaneous interpretation of both genetic risks and potential gene regulatory pathways toward phenotypic outcome by establishing the ternary relationship of genotype-expression-phenotype (GEP). The analytic scope is further extended by linkage disequilibrium from five different populations of the international HapMap Project.'),
(78398, 2014, 'bio', 'SAMBLASTER: fast duplicate marking and structural variant read extraction', 'Faust, Gregory G|Hall, Ira M', 'Department of Biochemistry and Molecular Genetics and Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA.|Department of Biochemistry and Molecular Genetics and Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA Department of Biochemistry and Molecular Genetics and Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA.', 'United States|United States', 178, 'Genomic Structural Variation|Genomics|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu314', '24812344', 'Illumina DNA sequencing is now the predominant source of raw genomic data, and data volumes are growing rapidly. Bioinformatic analysis pipelines are having trouble keeping pace. A common bottleneck in such pipelines is the requirement to read, write, sort and compress large BAM files multiple times.'),
(78399, 2014, 'bio', 'A framework for installable external tools in Skyline', 'Broudy, Daniel|Killeen, Trevor|Choi, Meena|Shulman, Nicholas|Mani, Deepak R|Abbatiello, Susan E|Mani, Deepak|Ahmad, Rushdy|Sahu, Alexandria K|Schilling, Birgit|Tamura, Kaipo|Boss, Yuval|Sharma, Vagisha|Gibson, Bradford W|Carr, Steven A|Vitek, Olga|MacCoss, Michael J|MacLean, Brendan', 'Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, Department of Statistics, Purdue University, West Lafayette, IN 47907, Broad Institute of MIT and Harvard, Cambridge, MA 02142 and Buck Institute for Research on Aging, Novato, CA 94945, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Mass Spectrometry|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btu148', '24813211', 'Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. The Skyline document model contains extensive mass spectrometry data from targeted proteomics experiments performed using selected reaction monitoring, parallel reaction monitoring and data-independent and data-dependent acquisition methods. Researchers have developed software tools that perform statistical analysis of the experimental data contained within Skyline documents. The new external tools framework allows researchers to integrate their tools into Skyline without modifying the Skyline codebase. Installed tools provide point-and-click access to downstream statistical analysis of data processed in Skyline. The framework also specifies a uniform interface to format tools for installation into Skyline. Tool developers can now easily share their tools with proteomics researchers using Skyline.'),
(78400, 2014, 'bio', 'lncRNAtor: a comprehensive resource for functional investigation of long non-coding RNAs', 'Park, Charny|Yu, Namhee|Choi, Ikjung|Kim, Wankyu|Lee, Sanghyuk', 'Ewha Research Center for Systems Biology (ERCSB), Department of Life Science, Ewha Womans University, Seoul 120-750, Republic of Korea.|Ewha Research Center for Systems Biology (ERCSB), Department of Life Science, Ewha Womans University, Seoul 120-750, Republic of Korea.|Ewha Research Center for Systems Biology (ERCSB), Department of Life Science, Ewha Womans University, Seoul 120-750, Republic of Korea.|Ewha Research Center for Systems Biology (ERCSB), Department of Life Science, Ewha Womans University, Seoul 120-750, Republic of Korea.|Ewha Research Center for Systems Biology (ERCSB), Department of Life Science, Ewha Womans University, Seoul 120-750, Republic of Korea.', '-|-|-|-|-', 84, 'Animals|Databases, Nucleic Acid|Gene Expression|High-Throughput Nucleotide Sequencing|Humans|Mice|Phylogeny|RNA, Long Noncoding|RNA, Messenger|RNA-Binding Proteins|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btu325', '24813212', 'A number of long non-coding RNAs (lncRNAs) have been identified by deep sequencing methods, but their molecular and cellular functions are known only for a limited number of lncRNAs. Current databases on lncRNAs are mostly for cataloging purpose without providing in-depth information required to infer functions. A comprehensive resource on lncRNA function is an immediate need.'),
(78401, 2014, 'bio', 'PeakLink: a new peptide peak linking method in LC-MS/MS using wavelet and SVM', 'Ghanat Bari, Mehrab|Ma, Xuepo|Zhang, Jianqiu', 'Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, TX 78246, USA.|Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, TX 78246, USA.|Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, TX 78246, USA.', 'United States|United States|United States', 5, 'Algorithms|Chromatography, Liquid|Humans|Peptides|Proteomics|Support Vector Machine|Tandem Mass Spectrometry|Wavelet Analysis', 'Journal Article', '10.1093/bioinformatics/btu299', '24813213', 'In liquid chromatography-mass spectrometry/tandem mass spectrometry (LC-MS/MS), it is necessary to link tandem MS-identified peptide peaks so that protein expression changes between the two runs can be tracked. However, only a small number of peptides can be identified and linked by tandem MS in two runs, and it becomes necessary to link peptide peaks with tandem identification in one run to their corresponding ones in another run without identification. In the past, peptide peaks are linked based on similarities in retention time (rt), mass or peak shape after rt alignment, which corrects mean rt shifts between runs. However, the accuracy in linking is still limited especially for complex samples collected from different conditions. Consequently, large-scale proteomics studies that require comparison of protein expression profiles of hundreds of patients can not be carried out effectively.'),
(78402, 2014, 'bio', 'Efficient RNA isoform identification and quantification from RNA-Seq data with network flows', 'Bernard, Elsa|Jacob, Laurent|Mairal, Julien|Vert, Jean-Philippe', 'Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France and LEAR Project-Team, INRIA Grenoble Rhône Alpes, 38330 Montbonnot, France Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France and LEAR Project-Team, INRIA Grenoble Rhône Alpes, 38330 Montbonnot, France Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France and LEAR Project-Team, INRIA Grenoble Rhône Alpes, 38330 Montbonnot, France.|Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France and LEAR Project-Team, INRIA Grenoble Rhône Alpes, 38330 Montbonnot, France.|Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France and LEAR Project-Team, INRIA Grenoble Rhône Alpes, 38330 Montbonnot, France.|Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France and LEAR Project-Team, INRIA Grenoble Rhône Alpes, 38330 Montbonnot, France Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France and LEAR Project-Team, INRIA Grenoble Rhône Alpes, 38330 Montbonnot, France Mines ParisTech, Centre for Computational Biology, 77300 Fontainebleau, Institut Curie, 26 rue dUlm, 75248 Paris Cedex 05, INSERM U900, Paris F-75248, France, Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRA, UMR5558, Villeurbanne, France and LEAR Project-Team, INRIA Grenoble Rhône Alpes, 38330 Montbonnot, France.', 'France|France|France|France', 31, 'Algorithms|Exons|Gene Expression Profiling|Humans|Models, Statistical|RNA Isoforms|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu317', '24813214', 'Several state-of-the-art methods for isoform identification and quantification are based on [Formula: see text]-regularized regression, such as the Lasso. However, explicitly listing the-possibly exponentially-large set of candidate transcripts is intractable for genes with many exons. For this reason, existing approaches using the [Formula: see text]-penalty are either restricted to genes with few exons or only run the regression algorithm on a small set of preselected isoforms.'),
(78403, 2014, 'bio', 'compcodeR--an R package for benchmarking differential expression methods for RNA-seq data', 'Soneson, Charlotte', 'Bioinformatics Core Facility, SIB Swiss Institute of Bioinformatics, Quartier Sorge, CH-1015 Lausanne, Switzerland.', 'Switzerland', 0, 'Benchmarking|Gene Expression Profiling|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btu324', '24813215', 'compcodeR is an R package for benchmarking of differential expression analysis methods, in particular, methods developed for analyzing RNA-seq data. The package provides functionality for simulating realistic RNA-seq count datasets, an interface to several of the most commonly used differential expression analysis methods and extensive functionality for evaluating and comparing different approaches on real and simulated data.'),
(78404, 2014, 'bio', 'Ceiba: scalable visualization of phylogenies and 2D/3D image collections', 'Sanderson, Michael J', 'Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85721, USA.', 'United States', 1, 'Computer Graphics|Image Processing, Computer-Assisted|Imaging, Three-Dimensional|Phylogeny|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu315', '24813216', 'Phylogenetic trees with hundreds of thousands of leaves are now being inferred from sequence data, posing significant challenges for visualization and exploratory analysis. Image data supplying valuable context for species in trees (and cues for exploring them) are becoming increasingly available in biodiversity databases and elsewhere but have rarely been built into tree visualization software in a scalable way. Ceiba lets the user explore large trees and inspect image collection arrays (sets of homologous images) comprising mixtures of 2D and 3D image objects. Ceiba exploits recent improvements in graphics hardware, OpenGL toolkits and many standard high-performance computer graphics strategies, such as texture compression, level of detail control, culling, animations and image caching. Its tree layouts can be tuned by user-provided phylogenetic definitions of subtrees. The code has been extensively tested on phylogenies of up to 55,000 leaves and images.'),
(78405, 2014, 'bio', 'Exploring protein domain organization by recognition of secondary structure packing interfaces', 'Deng, Lizong|Wu, Aiping|Dai, Wentao|Song, Tingrui|Cui, Ya|Jiang, Taijiao', 'Key Laboratory of Protein & Peptide Pharmaceuticals, National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101 and University of the Chinese Academy of Sciences, Beijing 100049, China Key Laboratory of Protein & Peptide Pharmaceuticals, National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101 and University of the Chinese Academy of Sciences, Beijing 100049, China.|Key Laboratory of Protein & Peptide Pharmaceuticals, National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101 and University of the Chinese Academy of Sciences, Beijing 100049, China.|Key Laboratory of Protein & Peptide Pharmaceuticals, National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101 and University of the Chinese Academy of Sciences, Beijing 100049, China Key Laboratory of Protein & Peptide Pharmaceuticals, National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101 and University of the Chinese Academy of Sciences, Beijing 100049, China.|Key Laboratory of Protein & Peptide Pharmaceuticals, National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101 and University of the Chinese Academy of Sciences, Beijing 100049, China Key Laboratory of Protein & Peptide Pharmaceuticals, National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101 and University of the Chinese Academy of Sciences, Beijing 100049, China.|Key Laboratory of Protein & Peptide Pharmaceuticals, National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101 and University of the Chinese Academy of Sciences, Beijing 100049, China Key Laboratory of Protein & Peptide Pharmaceuticals, National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101 and University of the Chinese Academy of Sciences, Beijing 100049, China.|Key Laboratory of Protein & Peptide Pharmaceuticals, National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101 and University of the Chinese Academy of Sciences, Beijing 100049, China.', 'China|China|China|China|China|China', 1, 'Computational Biology|Humans|Models, Molecular|Protein Kinases|Protein Structure, Secondary|Protein Structure, Tertiary', 'Journal Article', '10.1093/bioinformatics/btu327', '24813541', 'Protein domains are fundamental units of protein structure, function and evolution, thus, it is critical to gain a deep understanding of protein domain organization. Previous works have attempted to identify key residues involved in organization of domain architecture. Because one of the most important characteristics of domain architecture is the arrangement of secondary structure elements (SSEs), here we present a picture of domain organization through an integrated consideration of SSE arrangements and residue contact networks.'),
(78406, 2014, 'bio', 'SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci', 'Slowikowski, Kamil|Hu, Xinli|Raychaudhuri, Soumya', 'Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA 02138, USA, Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston MA 02215, Department of Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, MA 02115, USA and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA 02138, USA, Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston MA 02215, Department of Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, MA 02115, USA and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA.|Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA 02138, USA, Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston MA 02215, Department of Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, MA 02115, USA and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA.|Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA 02138, USA, Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston MA 02215, Department of Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, MA 02115, USA and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA 02138, USA, Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston MA 02215, Department of Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, MA 02115, USA and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA.', 'United States|United States|United States', 27, 'Algorithms|Erythroid Cells|Genetic Loci|Genomics|Humans|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Risk', 'Journal Article', '10.1093/bioinformatics/btu326', '24813542', 'We created a fast, robust and general C+ + implementation of a single-nucleotide polymorphism (SNP) set enrichment algorithm to identify cell types, tissues and pathways affected by risk loci. It tests trait-associated genomic loci for enrichment of specificity to conditions (cell types, tissues and pathways). We use a non-parametric statistical approach to compute empirical P-values by comparison with null SNP sets. As a proof of concept, we present novel applications of our method to four sets of genome-wide significant SNPs associated with red blood cell count, multiple sclerosis, celiac disease and HDL cholesterol.'),
(78407, 2014, 'bio', 'Universal dynamical properties preclude standard clustering in a large class of biochemical data', 'Gomez, Florian|Stoop, Ralph L|Stoop, Ruedi', 'Institute of Neuroinformatics, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland and Institute of Physics, University of Basel, 4056 Basel, Switzerland.|Institute of Neuroinformatics, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland and Institute of Physics, University of Basel, 4056 Basel, Switzerland.|Institute of Neuroinformatics, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland and Institute of Physics, University of Basel, 4056 Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland', 0, 'Biochemical Phenomena|Cluster Analysis|Models, Biological|Neurons', 'Journal Article', '10.1093/bioinformatics/btu332', '24813543', 'Clustering of chemical and biochemical data based on observed features is a central cognitive step in the analysis of chemical substances, in particular in combinatorial chemistry, or of complex biochemical reaction networks. Often, for reasons unknown to the researcher, this step produces disappointing results. Once the sources of the problem are known, improved clustering methods might revitalize the statistical approach of compound and reaction search and analysis. Here, we present a generic mechanism that may be at the origin of many clustering difficulties.'),
(78408, 2014, 'bio', 'PyCorrFit-generic data evaluation for fluorescence correlation spectroscopy', 'Müller, Paul|Schwille, Petra|Weidemann, Thomas', 'Biotechnology Center, Technische Universität Dresden, 01307 Dresden and Max Planck Institute of Biochemistry, Cellular and Molecular Biophysics, 82152 Martinsried, Germany.|Biotechnology Center, Technische Universität Dresden, 01307 Dresden and Max Planck Institute of Biochemistry, Cellular and Molecular Biophysics, 82152 Martinsried, Germany.|Biotechnology Center, Technische Universität Dresden, 01307 Dresden and Max Planck Institute of Biochemistry, Cellular and Molecular Biophysics, 82152 Martinsried, Germany.', 'Germany|Germany|Germany', 37, 'Algorithms|Computer Graphics|Internet|Software|Spectrometry, Fluorescence|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu328', '24825612', 'We present a graphical user interface (PyCorrFit) for the fitting of theoretical model functions to experimental data obtained by fluorescence correlation spectroscopy (FCS). The program supports many data file formats and features a set of tools specialized in FCS data evaluation.'),
(78409, 2014, 'bio', 'SIBIS: a Bayesian model for inconsistent protein sequence estimation', 'Khenoussi, Walyd|Vanhoutrxc3xa8ve, Renaud|Poch, Olivier|Thompson, Julie D', 'Department of Computer Science, ICube, UMR 7357, University of Strasbourg, CNRS, Fxc3xa9dxc3xa9ration de mxc3xa9decine translationnelle, Strasbourg, F-67085, France.|Department of Computer Science, ICube, UMR 7357, University of Strasbourg, CNRS, Fxc3xa9dxc3xa9ration de mxc3xa9decine translationnelle, Strasbourg, F-67085, France.|Department of Computer Science, ICube, UMR 7357, University of Strasbourg, CNRS, Fxc3xa9dxc3xa9ration de mxc3xa9decine translationnelle, Strasbourg, F-67085, France.|Department of Computer Science, ICube, UMR 7357, University of Strasbourg, CNRS, Fxc3xa9dxc3xa9ration de mxc3xa9decine translationnelle, Strasbourg, F-67085, France.', 'France|France|France|France', 0, 'Algorithms|Animals|Bayes Theorem|Databases, Protein|Humans|Macaca mulatta|Phylogeny|Sequence Alignment|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/btu329', '24825613', 'The prediction of protein coding genes is a major challenge that depends on the quality of genome sequencing, the accuracy of the model used to elucidate the exonic structure of the genes and the complexity of the gene splicing process leading to different protein variants. As a consequence, todays protein databases contain a huge amount of inconsistency, due to both natural variants and sequence prediction errors.'),
(78410, 2014, 'bio', 'PLAAC: a web and command-line application to identify proteins with prion-like amino acid composition', 'Lancaster, Alex K|Nutter-Upham, Andrew|Lindquist, Susan|King, Oliver D', 'Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, Department of Pathology, Beth Israel Deaconess Medical Center, Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA, Department of Biology, Howard Hughes Medical Institute, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139 and Department of Cell and Developmental Biology, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA 01655, USA Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, Department of Pathology, Beth Israel Deaconess Medical Center, Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA, Department of Biology, Howard Hughes Medical Institute, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139 and Department of Cell and Developmental Biology, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA 01655, USA Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, Department of Pathology, Beth Israel Deaconess Medical Center, Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA, Department of Biology, Howard Hughes Medical Institute, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139 and Department of Cell and Developmental Biology, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA 01655, USA.|Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, Department of Pathology, Beth Israel Deaconess Medical Center, Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA, Department of Biology, Howard Hughes Medical Institute, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139 and Department of Cell and Developmental Biology, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA 01655, USA.|Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, Department of Pathology, Beth Israel Deaconess Medical Center, Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA, Department of Biology, Howard Hughes Medical Institute, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139 and Department of Cell and Developmental Biology, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA 01655, USA Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, Department of Pathology, Beth Israel Deaconess Medical Center, Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA, Department of Biology, Howard Hughes Medical Institute, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139 and Department of Cell and Developmental Biology, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA 01655, USA Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, Department of Pathology, Beth Israel Deaconess Medical Center, Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA, Department of Biology, Howard Hughes Medical Institute, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139 and Department of Cell and Developmental Biology, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA 01655, USA.|Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142, Department of Pathology, Beth Israel Deaconess Medical Center, Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA, Department of Biology, Howard Hughes Medical Institute, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139 and Department of Cell and Developmental Biology, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA 01655, USA.', 'Israel|Israel|Israel|Israel', 100, 'Algorithms|Amino Acids|Internet|Prions|Saccharomyces cerevisiae Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btu310', '24825614', 'Prions are self-templating protein aggregates that stably perpetuate distinct biological states and are of keen interest to researchers in both evolutionary and biomedical science. The best understood prions are from yeast and have a prion-forming domain with strongly biased amino acid composition, most notably enriched for Q or N. PLAAC is a web application that scans protein sequences for domains with P: rion- L: ike A: mino A: cid C: omposition. Users can upload sequence files, or paste sequences directly into a textbox. PLAAC ranks the input sequences by several summary scores and allows scores along sequences to be visualized. Text output files can be downloaded for further analyses, and visualizations saved in PDF and PNG formats.'),
(78411, 2014, 'bio', 'Kmacs: the k-mismatch average common substring approach to alignment-free sequence comparison', 'Leimeister, Chris-Andre|Morgenstern, Burkhard', 'Department of Bioinformatics, Institute of Microbiology and Genetics, University of Göttingen, Goldschmidtstr. 1, 37073 Göttingen, Germany and Laboratoire Statistique et Génome, Université dÉvry Val dEssonne, UMR CNRS 8071, USC INRA, 23 Boulevard de France, 91037 Évry, France.|Department of Bioinformatics, Institute of Microbiology and Genetics, University of Göttingen, Goldschmidtstr. 1, 37073 Göttingen, Germany and Laboratoire Statistique et Génome, Université dÉvry Val dEssonne, UMR CNRS 8071, USC INRA, 23 Boulevard de France, 91037 Évry, FranceDepartment of Bioinformatics, Institute of Microbiology and Genetics, University of Göttingen, Goldschmidtstr. 1, 37073 Göttingen, Germany and Laboratoire Statistique et Génome, Université dÉvry Val dEssonne, UMR CNRS 8071, USC INRA, 23 Boulevard de France, 91037 Évry, France.', 'Germany|Germany', 71, 'Algorithms|Animals|Genome, Bacterial|Genome, Mitochondrial|Phylogeny|Primates|Roseobacter|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btu331', '24828656', 'Alignment-based methods for sequence analysis have various limitations if large datasets are to be analysed. Therefore, alignment-free approaches have become popular in recent years. One of the best known alignment-free methods is the average common substring approach that defines a distance measure on sequences based on the average length of longest common words between them. Herein, we generalize this approach by considering longest common substrings with k mismatches. We present a greedy heuristic to approximate the length of such k-mismatch substrings, and we describe kmacs, an efficient implementation of this idea based on generalized enhanced suffix arrays.'),
(78412, 2014, 'bio', 'RiboMaker: computational design of conformation-based riboregulation', 'Rodrigo, Guillermo|Jaramillo, Alfonso', 'Institute of Systems and Synthetic Biology, CNRS - Université dÉvry Val dEssonne, F-91000 Évry, France and School of Life Sciences, University of Warwick, Coventry CV4 7AL, United Kingdom.|Institute of Systems and Synthetic Biology, CNRS - Université dÉvry Val dEssonne, F-91000 Évry, France and School of Life Sciences, University of Warwick, Coventry CV4 7AL, United Kingdom Institute of Systems and Synthetic Biology, CNRS - Université dÉvry Val dEssonne, F-91000 Évry, France and School of Life Sciences, University of Warwick, Coventry CV4 7AL, United Kingdom.', 'France|France', 13, '5 Untranslated Regions|Algorithms|Bacteria|Base Sequence|Computational Biology|Nucleic Acid Conformation|RNA, Small Untranslated|Regulatory Sequences, Ribonucleic Acid|Software|Synthetic Biology', 'Journal Article', '10.1093/bioinformatics/btu335', '24833802', 'The ability to engineer control systems of gene expression is instrumental for synthetic biology. Thus, bioinformatic methods that assist such engineering are appealing because they can guide the sequence design and prevent costly experimental screening. In particular, RNA is an ideal substrate to de novo design regulators of protein expression by following sequence-to-function models.'),
(78413, 2014, 'bio', 'FaSD-somatic: a fast and accurate somatic SNV detection algorithm for cancer genome sequencing data', 'Wang, Weixin|Wang, Panwen|Xu, Feng|Luo, Ruibang|Wong, Maria Pik|Lam, Tak-Wah|Wang, Junwen', 'Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.', 'China|China|China|China|China|China|China', 10, 'Algorithms|Databases, Nucleic Acid|Genetic Variation|Genomics|High-Throughput Nucleotide Sequencing|Humans|Neoplasms', 'Evaluation Studies', '10.1093/bioinformatics/btu338', '24833803', 'Recent advances in high-throughput sequencing technologies have enabled us to sequence large number of cancer samples to reveal novel insights into oncogenetic mechanisms. However, the presence of intratumoral heterogeneity, normal cell contamination and insufficient sequencing depth, together pose a challenge for detecting somatic mutations. Here we propose a fast and an accurate somatic single-nucleotide variations (SNVs) detection program, FaSD-somatic. The performance of FaSD-somatic is extensively assessed on various types of cancer against several state-of-the-art somatic SNV detection programs. Benchmarked by somatic SNVs from either existing databases or de novo higher-depth sequencing data, FaSD-somatic has the best overall performance. Furthermore, FaSD-somatic is efficient, it finishes somatic SNV calling within 14 h on 50X whole genome sequencing data in paired samples.'),
(78414, 2014, 'bio', 'Memory-efficient RNA energy landscape exploration', 'Mann, Martin|Kucharík, Marcel|Flamm, Christoph|Wolfinger, Michael T', 'Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria.|Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria.|Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria.|Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria.', 'Austria|Austria|Austria|Austria', 8, 'Algorithms|Computational Biology|Kinetics|Nucleic Acid Conformation|Probability|RNA|Software|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btu337', '24833804', 'Energy landscapes provide a valuable means for studying the folding dynamics of short RNA molecules in detail by modeling all possible structures and their transitions. Higher abstraction levels based on a macro-state decomposition of the landscape enable the study of larger systems, however, they are still restricted by huge memory requirements of exact approaches.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78415, 2014, 'bio', 'RNASeqExpressionBrowser--a web interface to browse and visualize high-throughput expression data', 'Nussbaumer, Thomas|Kugler, Karl G|Bader, Kai C|Sharma, Sapna|Seidel, Michael|Mayer, Klaus F X', 'Institute for Bioinformatics and Systems Biology (IBIS), Helmholtz Center Munich, National Research Center for Environment and Health, 85764 Neuherberg, Germany.|Institute for Bioinformatics and Systems Biology (IBIS), Helmholtz Center Munich, National Research Center for Environment and Health, 85764 Neuherberg, Germany.|Institute for Bioinformatics and Systems Biology (IBIS), Helmholtz Center Munich, National Research Center for Environment and Health, 85764 Neuherberg, Germany.|Institute for Bioinformatics and Systems Biology (IBIS), Helmholtz Center Munich, National Research Center for Environment and Health, 85764 Neuherberg, Germany.|Institute for Bioinformatics and Systems Biology (IBIS), Helmholtz Center Munich, National Research Center for Environment and Health, 85764 Neuherberg, Germany.|Institute for Bioinformatics and Systems Biology (IBIS), Helmholtz Center Munich, National Research Center for Environment and Health, 85764 Neuherberg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 17, 'Computer Graphics|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Internet|Sequence Analysis, RNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu334', '24833805', 'RNA-seq techniques generate massive amounts of expression data. Several pipelines (e.g. Tophat and Cufflinks) are broadly applied to analyse these datasets. However, accessing and handling the analytical output remain challenging for non-experts.'),
(78416, 2014, 'bio', 'MethylSig: a whole genome DNA methylation analysis pipeline', 'Park, Yongseok|Figueroa, Maria E|Rozek, Laura S|Sartor, Maureen A', 'Department of Computational Medicine and Bioinformatics, Pathology Department, Department of Environmental Health Sciences, Department of Otolaryngology and Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Pathology Department, Department of Environmental Health Sciences, Department of Otolaryngology and Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Pathology Department, Department of Environmental Health Sciences, Department of Otolaryngology and Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Pathology Department, Department of Environmental Health Sciences, Department of Otolaryngology and Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Pathology Department, Department of Environmental Health Sciences, Department of Otolaryngology and Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Pathology Department, Department of Environmental Health Sciences, Department of Otolaryngology and Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA.', 'United States|United States|United States|United States', 0, 'CpG Islands|DNA Methylation|Genomics|Humans|Leukemia, Myeloid, Acute|Sequence Analysis, DNA|Software|Sulfites', 'Journal Article', '10.1093/bioinformatics/btu339', '24836530', 'DNA methylation plays critical roles in gene regulation and cellular specification without altering DNA sequences. The wide application of reduced representation bisulfite sequencing (RRBS) and whole genome bisulfite sequencing (bis-seq) opens the door to study DNA methylation at single CpG site resolution. One challenging question is how best to test for significant methylation differences between groups of biological samples in order to minimize false positive findings.'),
(78417, 2014, 'bio', 'SparkSeq: fast, scalable and cloud-ready tool for the interactive genomic data analysis with nucleotide precision', 'Wiewixc3xb3rka, Marek S|Messina, Antonio|Pacholewska, Alicja|Maffioletti, Sergio|Gawrysiak, Piotr|Okoniewski, Michaxc5x82 J', 'Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland, ICS 00-665 Warsaw (MW, PG), Grid Computing Competence Center-GC3, University of Zurich, 8057 Zxc3xbcrich (SM, AM), Swiss Institute of Equine Medicine, Vetsuisse Faculty, University of Bern and ALP-Haras, 3001 Bern (AP), Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, 3001 Bern (AP) and Functional Genomics Center Zurich, CH-8057 Zurich, Switzerland.|Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland, ICS 00-665 Warsaw (MW, PG), Grid Computing Competence Center-GC3, University of Zurich, 8057 Zxc3xbcrich (SM, AM), Swiss Institute of Equine Medicine, Vetsuisse Faculty, University of Bern and ALP-Haras, 3001 Bern (AP), Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, 3001 Bern (AP) and Functional Genomics Center Zurich, CH-8057 Zurich, Switzerland.|Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland, ICS 00-665 Warsaw (MW, PG), Grid Computing Competence Center-GC3, University of Zurich, 8057 Zxc3xbcrich (SM, AM), Swiss Institute of Equine Medicine, Vetsuisse Faculty, University of Bern and ALP-Haras, 3001 Bern (AP), Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, 3001 Bern (AP) and Functional Genomics Center Zurich, CH-8057 Zurich, Switzerland Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland, ICS 00-665 Warsaw (MW, PG), Grid Computing Competence Center-GC3, University of Zurich, 8057 Zxc3xbcrich (SM, AM), Swiss Institute of Equine Medicine, Vetsuisse Faculty, University of Bern and ALP-Haras, 3001 Bern (AP), Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, 3001 Bern (AP) and Functional Genomics Center Zurich, CH-8057 Zurich, Switzerland.|Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland, ICS 00-665 Warsaw (MW, PG), Grid Computing Competence Center-GC3, University of Zurich, 8057 Zxc3xbcrich (SM, AM), Swiss Institute of Equine Medicine, Vetsuisse Faculty, University of Bern and ALP-Haras, 3001 Bern (AP), Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, 3001 Bern (AP) and Functional Genomics Center Zurich, CH-8057 Zurich, Switzerland.|Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland, ICS 00-665 Warsaw (MW, PG), Grid Computing Competence Center-GC3, University of Zurich, 8057 Zxc3xbcrich (SM, AM), Swiss Institute of Equine Medicine, Vetsuisse Faculty, University of Bern and ALP-Haras, 3001 Bern (AP), Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, 3001 Bern (AP) and Functional Genomics Center Zurich, CH-8057 Zurich, Switzerland.|Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland, ICS 00-665 Warsaw (MW, PG), Grid Computing Competence Center-GC3, University of Zurich, 8057 Zxc3xbcrich (SM, AM), Swiss Institute of Equine Medicine, Vetsuisse Faculty, University of Bern and ALP-Haras, 3001 Bern (AP), Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, 3001 Bern (AP) and Functional Genomics Center Zurich, CH-8057 Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 66, 'Algorithms|Genomics|High-Throughput Nucleotide Sequencing|Internet|Nucleotides|Software|Statistics as Topic|Time Factors', 'Journal Article', '10.1093/bioinformatics/btu343', '24845651', 'Many time-consuming analyses of next -: generation sequencing data can be addressed with modern cloud computing. The Apache Hadoop-based solutions have become popular in genomics BECAUSE OF: their scalability in a cloud infrastructure. So far, most of these tools have been used for batch data processing rather than interactive data querying. The SparkSeq software has been created to take advantage of a new MapReduce framework, Apache Spark, for next-generation sequencing data. SparkSeq is a general-purpose, flexible and easily extendable library for genomic cloud computing. It can be used to build genomic analysis pipelines in Scala and run them in an interactive way. SparkSeq opens up the possibility of customized ad hoc secondary analyses and iterative machine learning algorithms. This article demonstrates its scalability and overall fast performance by running the analyses of sequencing datasets. Tests of SparkSeq also prove that the use of cache and HDFS block size can be tuned for the optimal performance on multiple worker nodes.'),
(78418, 2014, 'bio', 'CLImAT: accurate detection of copy number alteration and loss of heterozygosity in impure and aneuploid tumor samples using whole-genome sequencing data', 'Yu, Zhenhua|Liu, Yuanning|Shen, Yi|Wang, Minghui|Li, Ao', 'School of Information Science and Technology and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei AH230027, China.|School of Information Science and Technology and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei AH230027, China.|School of Information Science and Technology and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei AH230027, China.|School of Information Science and Technology and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei AH230027, China School of Information Science and Technology and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei AH230027, China.|School of Information Science and Technology and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei AH230027, China School of Information Science and Technology and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei AH230027, China.', 'China|China|China|China|China', 28, 'Aneuploidy|DNA Copy Number Variations|Gene Frequency|Genomics|Humans|Loss of Heterozygosity|Sequence Analysis, DNA|Software|Triple Negative Breast Neoplasms', 'Journal Article', '10.1093/bioinformatics/btu346', '24845652', 'Whole-genome sequencing of tumor samples has been demonstrated as an efficient approach for comprehensive analysis of genomic aberrations in cancer genome. Critical issues such as tumor impurity and aneuploidy, GC-content and mappability bias have been reported to complicate identification of copy number alteration and loss of heterozygosity in complex tumor samples. Therefore, efficient computational methods are required to address these issues.'),
(78419, 2014, 'bio', 'Exploration and retrieval of whole-metagenome sequencing samples', 'Seth, Sohan|Välimäki, Niko|Kaski, Samuel|Honkela, Antti', 'Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, Espoo, Finland, Genome-Scale Biology Program and Department of Medical Genetics, University of Helsinki, Helsinki, Finland, 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, Genome-Scale Biology Program and Department of Medical Genetics, University of Helsinki, Helsinki, Finland, 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, Genome-Scale Biology Program and Department of Medical Genetics, University of Helsinki, Helsinki, Finland, 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, Genome-Scale Biology Program and Department of Medical Genetics, University of Helsinki, Helsinki, Finland, 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, Genome-Scale Biology Program and Department of Medical Genetics, University of Helsinki, Helsinki, Finland, 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, Genome-Scale Biology Program and Department of Medical Genetics, University of Helsinki, Helsinki, Finland, and Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland.', 'Finland|Finland|Finland|Finland', 0, 'Algorithms|Data Mining|Diabetes Mellitus, Type 2|High-Throughput Nucleotide Sequencing|Humans|Inflammatory Bowel Diseases|Metagenomics|Microbiota|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btu340', '24845653', 'Over the recent years, the field of whole-metagenome shotgun sequencing has witnessed significant growth owing to the high-throughput sequencing technologies that allow sequencing genomic samples cheaper, faster and with better coverage than before. This technical advancement has initiated the trend of sequencing multiple samples in different conditions or environments to explore the similarities and dissimilarities of the microbial communities. Examples include the human microbiome project and various studies of the human intestinal tract. With the availability of ever larger databases of such measurements, finding samples similar to a given query sample is becoming a central operation.'),
(78420, 2014, 'bio', 'Estimates of allele-specific expression in Drosophila with a single genome sequence and RNA-seq data', 'Quinn, Andrew|Juneja, Punita|Jiggins, Francis M', 'Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.', 'United Kingdom|United Kingdom|United Kingdom', 8, 'Alleles|Animals|Chromosome Mapping|Drosophila melanogaster|Gene Expression Profiling|Genome, Insect|Genomics|High-Throughput Nucleotide Sequencing|Polymorphism, Single Nucleotide|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btu342', '24845654', 'Genetic variation in cis-regulatory elements is an important cause of variation in gene expression. Cis-regulatory variation can be detected by using high-throughput RNA sequencing (RNA-seq) to identify differences in the expression of the two alleles of a gene. This requires that reads from the two alleles are equally likely to map to a reference genome(s), and that single-nucleotide polymorphisms (SNPs) are accurately called, so that reads derived from the different alleles can be identified. Both of these prerequisites can be achieved by sequencing the genomes of the parents of the individual being studied, but this is often prohibitively costly.'),
(78421, 2014, 'bio', 'FamLBL: detecting rare haplotype disease association based on common SNPs using case-parent triads', 'Wang, Meng|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', 12, 'Bayes Theorem|Computational Biology|Disease|Female|Genome-Wide Association Study|Haplotypes|Humans|Logistic Models|Male|Parents|Pedigree|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btu347', '24849576', 'In recent years, there has been an increasing interest in using common single-nucleotide polymorphisms (SNPs) amassed in genome-wide association studies to investigate rare haplotype effects on complex diseases. Evidence has suggested that rare haplotypes may tag rare causal single-nucleotide variants, making SNP-based rare haplotype analysis not only cost effective, but also more valuable for detecting causal variants. Although a number of methods for detecting rare haplotype association have been proposed in recent years, they are population based and thus susceptible to population stratification.'),
(78422, 2014, 'bio', 'Evol and ProDy for bridging protein sequence evolution and structural dynamics', 'Bakan, Ahmet|Dutta, Anindita|Mao, Wenzhi|Liu, Ying|Chennubhotla, Chakra|Lezon, Timothy R|Bahar, Ivet', 'Department of Computational and Systems Biology, and Clinical & Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.|Department of Computational and Systems Biology, and Clinical & Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.|Department of Computational and Systems Biology, and Clinical & Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.|Department of Computational and Systems Biology, and Clinical & Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.|Department of Computational and Systems Biology, and Clinical & Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.|Department of Computational and Systems Biology, and Clinical & Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.|Department of Computational and Systems Biology, and Clinical & Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Computational Biology|Evolution, Molecular|Humans|Models, Molecular|Protein Conformation|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btu336', '24849577', 'Correlations between sequence evolution and structural dynamics are of utmost importance in understanding the molecular mechanisms of function and their evolution. We have integrated Evol, a new package for fast and efficient comparative analysis of evolutionary patterns and conformational dynamics, into ProDy, a computational toolbox designed for inferring protein dynamics from experimental and theoretical data. Using information-theoretic approaches, Evol coanalyzes conservation and coevolution profiles extracted from multiple sequence alignments of protein families with their inferred dynamics.'),
(78423, 2014, 'bio', 'HTML5 PivotViewer: high-throughput visualization and querying of image data on the web', 'Taylor, Stephen|Noble, Roger', 'Computational Biology Research Group, Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DS, UK and Coritsu Group, Adelaide, South Australia 5000, Australia.|Computational Biology Research Group, Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DS, UK and Coritsu Group, Adelaide, South Australia 5000, Australia.', 'Australia|Australia', 4, 'Computational Biology|Computer Graphics|Data Mining|Internet|Molecular Imaging|Software', 'Journal Article', '10.1093/bioinformatics/btu349', '24849578', 'Visualization and analysis of large numbers of biological images has generated a bottle neck in research. We present HTML5 PivotViewer, a novel, open source, platform-independent viewer making use of the latest web technologies that allows seamless access to images and associated metadata for each image. This provides a powerful method to allow end users to mine their data.'),
(78424, 2014, 'bio', 'MaxLink: network-based prioritization of genes tightly linked to a disease seed set', 'Guala, Dimitri|Sjölund, Erik|Sonnhammer, Erik L L', 'Stockholm Bioinformatics Centre, Science for Life Laboratory, SE-17121 Solna, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, SE-11321, Sweden and Swedish eScience Research Center, SE-10450 Stockholm, Sweden Stockholm Bioinformatics Centre, Science for Life Laboratory, SE-17121 Solna, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, SE-11321, Sweden and Swedish eScience Research Center, SE-10450 Stockholm, Sweden.|Stockholm Bioinformatics Centre, Science for Life Laboratory, SE-17121 Solna, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, SE-11321, Sweden and Swedish eScience Research Center, SE-10450 Stockholm, Sweden Stockholm Bioinformatics Centre, Science for Life Laboratory, SE-17121 Solna, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, SE-11321, Sweden and Swedish eScience Research Center, SE-10450 Stockholm, Sweden.|Stockholm Bioinformatics Centre, Science for Life Laboratory, SE-17121 Solna, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, SE-11321, Sweden and Swedish eScience Research Center, SE-10450 Stockholm, Sweden Stockholm Bioinformatics Centre, Science for Life Laboratory, SE-17121 Solna, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, SE-11321, Sweden and Swedish eScience Research Center, SE-10450 Stockholm, Sweden Stockholm Bioinformatics Centre, Science for Life Laboratory, SE-17121 Solna, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, SE-11321, Sweden and Swedish eScience Research Center, SE-10450 Stockholm, Sweden.', 'Sweden|Sweden|Sweden', 9, 'Algorithms|Breast Neoplasms|Computational Biology|Disease|Humans|Internet|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btu344', '24849579', 'MaxLink, a guilt-by-association network search algorithm, has been made available as a web resource and a stand-alone version. Based on a user-supplied list of query genes, MaxLink identifies and ranks genes that are tightly linked to the query list. This functionality can be used to predict potential disease genes from an initial set of genes with known association to a disease. The original algorithm, used to identify and rank novel genes potentially involved in cancer, has been updated to use a more statistically sound method for selection of candidate genes and made applicable to other areas than cancer. The algorithm has also been made faster by re-implementation in C++, and the Web site uses FunCoup 3.0 as the underlying network.'),
(78425, 2014, 'bio', 'Accurate cell segmentation in microscopy images using membrane patterns', 'Dimopoulos, Sotiris|Mayer, Christian E|Rudolf, Fabian|Stelling, Joerg', 'Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland, Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland, Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland.|Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland, Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland, Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland.|Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland, Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland.|Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland, Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland, Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Algorithms|Cell Membrane|Computational Biology|Image Processing, Computer-Assisted|Microscopy', 'Journal Article', '10.1093/bioinformatics/btu302', '24849580', 'Identifying cells in an image (cell segmentation) is essential for quantitative single-cell biology via optical microscopy. Although a plethora of segmentation methods exists, accurate segmentation is challenging and usually requires problem-specific tailoring of algorithms. In addition, most current segmentation algorithms rely on a few basic approaches that use the gradient field of the image to detect cell boundaries. However, many microscopy protocols can generate images with characteristic intensity profiles at the cell membrane. This has not yet been algorithmically exploited to establish more general segmentation methods.'),
(78426, 2014, 'bio', 'GenomeVISTA--an integrated software package for whole-genome alignment and visualization', 'Poliakov, Alexandre|Foong, Justin|Brudno, Michael|Dubchak, Inna', 'US Department of Energy Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA 94598, USA, Centre for Computational Medicine, Hospital for Sick Children, Toronto, ON M5G 1X8 Canada, Department of Computer Science, University of Toronto, Toronto, ON M5S 3G4 Canada and Genomics Division, LBNL, Berkeley, CA 94720, USA.|US Department of Energy Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA 94598, USA, Centre for Computational Medicine, Hospital for Sick Children, Toronto, ON M5G 1X8 Canada, Department of Computer Science, University of Toronto, Toronto, ON M5S 3G4 Canada and Genomics Division, LBNL, Berkeley, CA 94720, USA.|US Department of Energy Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA 94598, USA, Centre for Computational Medicine, Hospital for Sick Children, Toronto, ON M5G 1X8 Canada, Department of Computer Science, University of Toronto, Toronto, ON M5S 3G4 Canada and Genomics Division, LBNL, Berkeley, CA 94720, USA US Department of Energy Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA 94598, USA, Centre for Computational Medicine, Hospital for Sick Children, Toronto, ON M5G 1X8 Canada, Department of Computer Science, University of Toronto, Toronto, ON M5S 3G4 Canada and Genomics Division, LBNL, Berkeley, CA 94720, USA.|US Department of Energy Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA 94598, USA, Centre for Computational Medicine, Hospital for Sick Children, Toronto, ON M5G 1X8 Canada, Department of Computer Science, University of Toronto, Toronto, ON M5S 3G4 Canada and Genomics Division, LBNL, Berkeley, CA 94720, USA US Department of Energy Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA 94598, USA, Centre for Computational Medicine, Hospital for Sick Children, Toronto, ON M5G 1X8 Canada, Department of Computer Science, University of Toronto, Toronto, ON M5S 3G4 Canada and Genomics Division, LBNL, Berkeley, CA 94720, USA.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Computer Graphics|Genomics|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btu355', '24860159', 'With the ubiquitous generation of complete genome assemblies for a variety of species, efficient tools for whole-genome alignment along with user-friendly visualization are critically important. Our VISTA family of tools for comparative genomics, based on algorithms for pairwise and multiple alignments of genomic sequences and whole-genome assemblies, has become one of the standard techniques for comparative analysis. Most of the VISTA programs have been implemented as Web-accessible servers and are extensively used by the biomedical community. In this manuscript, we introduce GenomeVISTA: a novel implementation that incorporates most features of the VISTA family--fast and accurate alignment, visualization capabilities, GUI and analytical tools within a stand-alone software package. GenomeVISTA thus provides flexibility and security for users who need to conduct whole-genome comparisons on their own computers.'),
(78427, 2014, 'bio', 'Identification of chromosomal translocation hotspots via scan statistics', 'Silva, Israel T|Rosales, Rafael A|Holanda, Adriano J|Nussenzweig, Michel C|Jankovic, Mila', 'Laboratory of Molecular Immunology, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA, Departamento de Computação e Matemática, Universidade de São Paulo. Av. Bandeirantes, 3900, Ribeirão Preto, CEP 14049-901 and National Institute of Science and Technology in Stem Cell and Cell Therapy and Center for Cell Based Therapy. Rua Catão Roxo, 2501, Ribeirão Preto, CEP 14051-140, SP, Brazil Laboratory of Molecular Immunology, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA, Departamento de Computação e Matemática, Universidade de São Paulo. Av. Bandeirantes, 3900, Ribeirão Preto, CEP 14049-901 and National Institute of Science and Technology in Stem Cell and Cell Therapy and Center for Cell Based Therapy. Rua Catão Roxo, 2501, Ribeirão Preto, CEP 14051-140, SP, Brazil.|Laboratory of Molecular Immunology, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA, Departamento de Computação e Matemática, Universidade de São Paulo. Av. Bandeirantes, 3900, Ribeirão Preto, CEP 14049-901 and National Institute of Science and Technology in Stem Cell and Cell Therapy and Center for Cell Based Therapy. Rua Catão Roxo, 2501, Ribeirão Preto, CEP 14051-140, SP, Brazil.|Laboratory of Molecular Immunology, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA, Departamento de Computação e Matemática, Universidade de São Paulo. Av. Bandeirantes, 3900, Ribeirão Preto, CEP 14049-901 and National Institute of Science and Technology in Stem Cell and Cell Therapy and Center for Cell Based Therapy. Rua Catão Roxo, 2501, Ribeirão Preto, CEP 14051-140, SP, Brazil.|Laboratory of Molecular Immunology, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA, Departamento de Computação e Matemática, Universidade de São Paulo. Av. Bandeirantes, 3900, Ribeirão Preto, CEP 14049-901 and National Institute of Science and Technology in Stem Cell and Cell Therapy and Center for Cell Based Therapy. Rua Catão Roxo, 2501, Ribeirão Preto, CEP 14051-140, SP, Brazil.|Laboratory of Molecular Immunology, The Rockefeller University, 1230 York Avenue, New York, NY 10065, USA, Departamento de Computação e Matemática, Universidade de São Paulo. Av. Bandeirantes, 3900, Ribeirão Preto, CEP 14049-901 and National Institute of Science and Technology in Stem Cell and Cell Therapy and Center for Cell Based Therapy. Rua Catão Roxo, 2501, Ribeirão Preto, CEP 14051-140, SP, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil', 0, 'B-Lymphocytes|Biometry|Chromosome Breakpoints|Cluster Analysis|Cytidine Deaminase|DNA Repair|Genomics|High-Throughput Nucleotide Sequencing|Models, Statistical|Translocation, Genetic', 'Journal Article', '10.1093/bioinformatics/btu351', '24860160', 'The detection of genomic regions unusually rich in a given pattern is an important undertaking in the analysis of next-generation sequencing data. Recent studies of chromosomal translocations in activated B lymphocytes have identified regions that are frequently translocated to c-myc oncogene. A quantitative method for the identification of translocation hotspots was crucial to this study. Here we improve this analysis by using a simple probabilistic model and the framework provided by scan statistics to define the number and location of translocation breakpoint hotspots. A key feature of our method is that it provides a global chromosome-wide nominal control level to clustering, as opposed to previous methods based on local criteria. While being motivated by a specific application, the detection of unusual clusters is a widespread problem in bioinformatics. We expect our method to be useful in the analysis of data from other experimental approaches such as of ChIP-seq and 4C-seq.'),
(78428, 2014, 'bio', 'GT-Scan: identifying unique genomic targets', 'OBrien, Aidan|Bailey, Timothy L', 'Genomics and Computational Biology, Institute for Molecular Bioscience, The University of Queensland, Brisbane, Qld. 4072, Australia.|Genomics and Computational Biology, Institute for Molecular Bioscience, The University of Queensland, Brisbane, Qld. 4072, Australia.', 'Australia|Australia', 0, 'Clustered Regularly Interspaced Short Palindromic Repeats|Computational Biology|Endonucleases|Genetic Engineering|Genome, Human|Humans|Internet', 'Journal Article', '10.1093/bioinformatics/btu354', '24860161', 'A number of technologies, including CRISPR/Cas, transcription activator-like effector nucleases and zinc-finger nucleases, allow the user to target a chosen locus for genome editing or regulatory interference. Specificity, however, is a major problem, and the targeted locus must be chosen with care to avoid inadvertently affecting other loci (off-targets) in the genome. To address this we have created Genome Target Scan (GT-Scan), a flexible web-based tool that ranks all potential targets in a user-selected region of a genome in terms of how many off-targets they have. GT-Scan gives the user flexibility to define the desired characteristics of targets and off-targets via a simple target rule, and its interactive output allows detailed inspection of each of the most promising candidate targets. GT-Scan can be used to identify optimal targets for CRISPR/Cas systems, but its flexibility gives it potential to be adapted to other genome-targeting technologies as well.'),
(78429, 2014, 'bio', 'SSpro/ACCpro 5: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, machine learning and structural similarity', 'Magnan, Christophe N|Baldi, Pierre', 'Department of Computer Science and Institute for Genomics and Bioinformatics, University of California, Irvine, CA 92697, USA Department of Computer Science and Institute for Genomics and Bioinformatics, University of California, Irvine, CA 92697, USA.|Department of Computer Science and Institute for Genomics and Bioinformatics, University of California, Irvine, CA 92697, USA Department of Computer Science and Institute for Genomics and Bioinformatics, University of California, Irvine, CA 92697, USA.', 'United States|United States', 148, 'Artificial Intelligence|Computational Biology|Protein Structure, Secondary|Proteins|Solvents', 'Journal Article', '10.1093/bioinformatics/btu352', '24860169', 'Accurately predicting protein secondary structure and relative solvent accessibility is important for the study of protein evolution, structure and function and as a component of protein 3D structure prediction pipelines. Most predictors use a combination of machine learning and profiles, and thus must be retrained and assessed periodically as the number of available protein sequences and structures continues to grow.'),
(78430, 2014, 'bio', 'MIPgen: optimized modeling and design of molecular inversion probes for targeted resequencing', 'Boyle, Evan A|ORoak, Brian J|Martin, Beth K|Kumar, Akash|Shendure, Jay', 'Department of Genome Sciences, University of Washington, Seattle, WA 98105 and Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98105 and Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98105 and Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98105 and Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98105 and Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA.', 'United States|United States|United States|United States|United States', 78, 'Algorithms|Computational Biology|Computer Simulation|DNA Probes|Humans|Models, Statistical|Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btu353', '24867941', 'Molecular inversion probes (MIPs) enable cost-effective multiplex targeted gene resequencing in large cohorts. However, the design of individual MIPs is a critical parameter governing the performance of this technology with respect to capture uniformity and specificity. MIPgen is a user-friendly package that simplifies the process of designing custom MIP assays to arbitrary targets. New logistic and SVM-derived models enable in silico predictions of assay success, and assay redesign exhibits improved coverage uniformity relative to previous methods, which in turn improves the utility of MIPs for cost-effective targeted sequencing for candidate gene validation and for diagnostic sequencing in a clinical setting.'),
(78431, 2014, 'bio', 'keeSeek: searching distant non-existing words in genomes for PCR-based applications', 'Falda, Marco|Fontana, Paolo|Barzon, Luisa|Toppo, Stefano|Lavezzo, Enrico', 'Department of Molecular Medicine, University of Padova, Padova, I-35131, Italy and Department of Computational Biology, Edmund Mach Foundation, S. Michele AllAdige, I-38010 (TN), Italy.|Department of Molecular Medicine, University of Padova, Padova, I-35131, Italy and Department of Computational Biology, Edmund Mach Foundation, S. Michele AllAdige, I-38010 (TN), Italy.|Department of Molecular Medicine, University of Padova, Padova, I-35131, Italy and Department of Computational Biology, Edmund Mach Foundation, S. Michele AllAdige, I-38010 (TN), Italy.|Department of Molecular Medicine, University of Padova, Padova, I-35131, Italy and Department of Computational Biology, Edmund Mach Foundation, S. Michele AllAdige, I-38010 (TN), Italy.|Department of Molecular Medicine, University of Padova, Padova, I-35131, Italy and Department of Computational Biology, Edmund Mach Foundation, S. Michele AllAdige, I-38010 (TN), Italy.', 'Italy|Italy|Italy|Italy|Italy', 1, 'Algorithms|Arabidopsis|Base Sequence|DNA Primers|Data Mining|Genomics|Mycobacterium tuberculosis|Polymerase Chain Reaction|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu312', '24867942', 'The search for short words that are absent in the genome of one or more organisms (neverwords, also known as nullomers) is attracting growing interest because of the impact they may have in recent molecular biology applications. keeSeek is able to find absent sequences with primer-like features, which can be used as unique labels for exogenously inserted DNA fragments to recover their exact position into the genome using PCR techniques. The main differences with respect to previously developed tools for neverwords generation are (i) calculation of the distance from the reference genome, in terms of number of mismatches, and selection of the most distant sequences that will have a low probability to anneal unspecifically, (ii) application of a series of filters to discard candidates not suitable to be used as PCR primers. KeeSeek has been implemented in C++ and CUDA (Compute Unified Device Architecture) to work in a General-Purpose Computing on Graphics Processing Units (GPGPU) environment.'),
(78432, 2014, 'bio', 'CWig: compressed representation of Wiggle/BedGraph format', 'Huy Hoang, Do|Sung, Wing-Kin', 'Department of Computational and Systems Biology, Genome Institute of Singapore, Singapore 138672 and Department of Computer Science, School of Computing, National University of Singapore, Singapore 117417.|Department of Computational and Systems Biology, Genome Institute of Singapore, Singapore 138672 and Department of Computer Science, School of Computing, National University of Singapore, Singapore 117417 Department of Computational and Systems Biology, Genome Institute of Singapore, Singapore 138672 and Department of Computer Science, School of Computing, National University of Singapore, Singapore 117417.', 'Singapore|Singapore', 2, 'DNA Copy Number Variations|Data Compression|Data Mining|Databases, Genetic|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btu330', '24867943', 'BigWig, a format to represent read density data, is one of the most popular data types. They can represent the peak intensity in ChIP-seq, the transcript expression in RNA-seq, the copy number variation in whole genome sequencing, etc. UCSC Encode project uses the bigWig format heavily for storage and visualization. Of 5.2 TB Encode hg19 database, 1.6 TB (31% of the total space) is used to store bigWig files. BigWig format not only saves a lot of space but also supports fast queries that are crucial for interactive analysis and browsing. In our benchmark, bigWig often has similar size to the gzipped raw data, while is still able to support xe2x88xbc 5000 random queries per second.'),
(78433, 2014, 'bio', 'MPBind: a Meta-motif-based statistical framework and pipeline to Predict Binding potential of SELEX-derived aptamers', 'Jiang, Peng|Meyer, Susanne|Hou, Zhonggang|Propson, Nicholas E|Soh, H Tom|Thomson, James A|Stewart, Ron', 'Regenerative Biology, Morgridge Institute for Research, Madison, WI 53707, Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, CA 93106, Departments of Mechanical Engineering and Materials, University of California, Santa Barbara, CA 93106 and Department of Cell and Regenerative Biology, University of Wisconsin, Madison, WI 53706, USA.|Regenerative Biology, Morgridge Institute for Research, Madison, WI 53707, Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, CA 93106, Departments of Mechanical Engineering and Materials, University of California, Santa Barbara, CA 93106 and Department of Cell and Regenerative Biology, University of Wisconsin, Madison, WI 53706, USA.|Regenerative Biology, Morgridge Institute for Research, Madison, WI 53707, Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, CA 93106, Departments of Mechanical Engineering and Materials, University of California, Santa Barbara, CA 93106 and Department of Cell and Regenerative Biology, University of Wisconsin, Madison, WI 53706, USA.|Regenerative Biology, Morgridge Institute for Research, Madison, WI 53707, Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, CA 93106, Departments of Mechanical Engineering and Materials, University of California, Santa Barbara, CA 93106 and Department of Cell and Regenerative Biology, University of Wisconsin, Madison, WI 53706, USA.|Regenerative Biology, Morgridge Institute for Research, Madison, WI 53707, Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, CA 93106, Departments of Mechanical Engineering and Materials, University of California, Santa Barbara, CA 93106 and Department of Cell and Regenerative Biology, University of Wisconsin, Madison, WI 53706, USA.|Regenerative Biology, Morgridge Institute for Research, Madison, WI 53707, Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, CA 93106, Departments of Mechanical Engineering and Materials, University of California, Santa Barbara, CA 93106 and Department of Cell and Regenerative Biology, University of Wisconsin, Madison, WI 53706, USA Regenerative Biology, Morgridge Institute for Research, Madison, WI 53707, Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, CA 93106, Departments of Mechanical Engineering and Materials, University of California, Santa Barbara, CA 93106 and Department of Cell and Regenerative Biology, University of Wisconsin, Madison, WI 53706, USA Regenerative Biology, Morgridge Institute for Research, Madison, WI 53707, Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, CA 93106, Departments of Mechanical Engineering and Materials, University of California, Santa Barbara, CA 93106 and Department of Cell and Regenerative Biology, University of Wisconsin, Madison, WI 53706, USA.|Regenerative Biology, Morgridge Institute for Research, Madison, WI 53707, Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, CA 93106, Departments of Mechanical Engineering and Materials, University of California, Santa Barbara, CA 93106 and Department of Cell and Regenerative Biology, University of Wisconsin, Madison, WI 53706, USA.', 'United States|United States|United States|United States|United States|United States|United States', 23, 'Aptamers, Nucleotide|Computational Biology|Embryonic Stem Cells|Humans|Ligands|Oligonucleotides|SELEX Aptamer Technique|Sequence Analysis|Software|Substrate Specificity', 'Journal Article', '10.1093/bioinformatics/btu348', '24872422', 'Aptamers are synthetic antibodies that can bind to target molecules with high affinity and specificity. Aptamers are chemically synthesized and their discovery can be performed completely in vitro, rather than relying on in vivo biological processes, making them well-suited for high-throughput discovery. However, a large fraction of the most enriched aptamers in Systematic Evolution of Ligands by EXponential enrichment (SELEX) rounds display poor binding activity. Here, we present MPBind, a Meta-motif-based statistical framework and pipeline to Predict the BIND: ing potential of SELEX-derived aptamers. Using human embryonic stem cell SELEX-Seq data, MPBind achieved high prediction accuracy for binding potential. Further analysis showed that MPBind is robust to both polymerase chain reaction amplification bias and incomplete sequencing of aptamer pools. These two biases usually confound aptamer analysis.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(78434, 2014, 'bio', 'Massifquant: open-source Kalman filter-based XC-MS isotope trace feature detection', 'Conley, Christopher J|Smith, Rob|Torgrip, Ralf J O|Taylor, Ryan M|Tautenhahn, Ralf|Prince, John T', 'Department of Statistics, University of California Davis, Davis, CA 95616, Department of Computer Science, Brigham Young University, Provo, UT 84606, USA, Department of Analytical Chemistry, Stockholm University, SE-106 91, Stockholm, Sweden, Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84606, Department of Chemistry, Department of Molecular Biology and Center for Metabolomics, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Statistics, University of California Davis, Davis, CA 95616, Department of Computer Science, Brigham Young University, Provo, UT 84606, USA, Department of Analytical Chemistry, Stockholm University, SE-106 91, Stockholm, Sweden, Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84606, Department of Chemistry, Department of Molecular Biology and Center for Metabolomics, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Statistics, University of California Davis, Davis, CA 95616, Department of Computer Science, Brigham Young University, Provo, UT 84606, USA, Department of Analytical Chemistry, Stockholm University, SE-106 91, Stockholm, Sweden, Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84606, Department of Chemistry, Department of Molecular Biology and Center for Metabolomics, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Statistics, University of California Davis, Davis, CA 95616, Department of Computer Science, Brigham Young University, Provo, UT 84606, USA, Department of Analytical Chemistry, Stockholm University, SE-106 91, Stockholm, Sweden, Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84606, Department of Chemistry, Department of Molecular Biology and Center for Metabolomics, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Statistics, University of California Davis, Davis, CA 95616, Department of Computer Science, Brigham Young University, Provo, UT 84606, USA, Department of Analytical Chemistry, Stockholm University, SE-106 91, Stockholm, Sweden, Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84606, Department of Chemistry, Department of Molecular Biology and Center for Metabolomics, The Scripps Research Institute, La Jolla, CA 92037, USA Department of Statistics, University of California Davis, Davis, CA 95616, Department of Computer Science, Brigham Young University, Provo, UT 84606, USA, Department of Analytical Chemistry, Stockholm University, SE-106 91, Stockholm, Sweden, Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84606, Department of Chemistry, Department of Molecular Biology and Center for Metabolomics, The Scripps Research Institute, La Jolla, CA 92037, USA Department of Statistics, University of California Davis, Davis, CA 95616, Department of Computer Science, Brigham Young University, Provo, UT 84606, USA, Department of Analytical Chemistry, Stockholm University, SE-106 91, Stockholm, Sweden, Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84606, Department of Chemistry, Department of Molecular Biology and Center for Metabolomics, The Scripps Research Institute, La Jolla, CA 92037, USA.|Department of Statistics, University of California Davis, Davis, CA 95616, Department of Computer Science, Brigham Young University, Provo, UT 84606, USA, Department of Analytical Chemistry, Stockholm University, SE-106 91, Stockholm, Sweden, Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84606, Department of Chemistry, Department of Molecular Biology and Center for Metabolomics, The Scripps Research Institute, La Jolla, CA 92037, USA.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 19, 'Chromatography, Liquid|Computational Biology|Data Mining|Gas Chromatography-Mass Spectrometry|Isotopes|Software|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btu359', '24872423', 'Isotope trace (IT) detection is a fundamental step for liquid or gas chromatography mass spectrometry (XC-MS) data analysis that faces a multitude of technical challenges on complex samples. The Kalman filter (KF) application to IT detection addresses some of these challenges, it discriminates closely eluting ITs in the m/z dimension, flexibly handles heteroscedastic m/z variances and does not bin the m/z axis. Yet, the behavior of this KF application has not been fully characterized, as no cost-free open-source implementation exists and incomplete evaluation standards for IT detection persist.'),
(78435, 2014, 'bio', 'CODOC: efficient access, analysis and compression of depth of coverage signals', 'Popitsch, Niko', 'Center for Integrative Bioinformatics Vienna (CIBIV), Max F Perutz Laboratories, University of Vienna and Medical University of Vienna, Dr. Bohrgasse 9, 1030 Vienna, Austria.', 'Austria', 0, 'Algorithms|Data Compression|Data Mining|High-Throughput Nucleotide Sequencing|Statistics as Topic|Time Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu362', '24872424', 'Current data formats for the representation of depth of coverage data (DOC), a central resource for interpreting, filtering or detecting novel features in high-throughput sequencing datasets, were primarily designed for visualization purposes. This limits their applicability in stand-alone analyses of these data, mainly owing to inaccurate representation or mediocre data compression. CODOC is a novel data format and comprehensive application programming interface for efficient representation, access and analysis of DOC data. CODOC compresses these data xe2x88xbc 4-32xc3x97 better than the best current comparable method by exploiting specific data characteristics while at the same time enabling more-exact signal recovery for lossy compression and very fast query answering times.'),
(78436, 2014, 'bio', 'AlphaMPSim: flexible simulation of multi-parent crosses', 'Hickey, John M|Gorjanc, Gregor|Hearne, Sarah|Huang, Bevan E', 'The Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, Scotland, UK, Genetic Resources Program, International Maize and Wheat Improvement Center (CIMMYT), Apdo. 06600 México D.F. and CSIRO Computational Informatics and Food Futures National Research Flagship, Dutton Park, QLD 4001, Australia.|The Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, Scotland, UK, Genetic Resources Program, International Maize and Wheat Improvement Center (CIMMYT), Apdo. 06600 México D.F. and CSIRO Computational Informatics and Food Futures National Research Flagship, Dutton Park, QLD 4001, Australia.|The Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, Scotland, UK, Genetic Resources Program, International Maize and Wheat Improvement Center (CIMMYT), Apdo. 06600 México D.F. and CSIRO Computational Informatics and Food Futures National Research Flagship, Dutton Park, QLD 4001, Australia.|The Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, Scotland, UK, Genetic Resources Program, International Maize and Wheat Improvement Center (CIMMYT), Apdo. 06600 México D.F. and CSIRO Computational Informatics and Food Futures National Research Flagship, Dutton Park, QLD 4001, Australia.', 'Australia|Australia|Australia|Australia', 5, 'Genomics|Haplotypes|Hybridization, Genetic|Inbreeding|Models, Genetic|Phenotype|Software', 'Journal Article', '10.1093/bioinformatics/btu206', '24872425', 'Multi-parent crosses of recombinant inbred lines exist in many species for fine-scale analysis of genome structure and marker-trait association. These populations encompass a wide range of crossing designs with varying potential. AlphaMPSim is a flexible simulation program that is efficiently designed for comparison of alternative designs for traits with varying genetic architectures and biallelic markers with densities up to full sequence. A large pool of founder haplotypes can be supplied by the user, or generated via integration with external coalescent simulation programs such as MaCS. From these, diverse founders for multi-parent designs can be generated automatically, and users can compare designs generated from diverse pedigrees. Full tracking of identity by descent status of alleles within the pedigree is undertaken, and output files are compatible with commonly available analysis packages in R.'),
(78437, 2014, 'bio', 'MoDPepInt: an interactive web server for prediction of modular domain-peptide interactions', 'Kundu, Kousik|Mann, Martin|Costa, Fabrizio|Backofen, Rolf', 'Bioinformatics Group, Department of Computer Science, 79110 Freiburg and Centre for Biological Signalling Studies (BIOSS), 79104 Freiburg, University of Freiburg, Germany.|Bioinformatics Group, Department of Computer Science, 79110 Freiburg and Centre for Biological Signalling Studies (BIOSS), 79104 Freiburg, University of Freiburg, Germany.|Bioinformatics Group, Department of Computer Science, 79110 Freiburg and Centre for Biological Signalling Studies (BIOSS), 79104 Freiburg, University of Freiburg, Germany.|Bioinformatics Group, Department of Computer Science, 79110 Freiburg and Centre for Biological Signalling Studies (BIOSS), 79104 Freiburg, University of Freiburg, Germany Bioinformatics Group, Department of Computer Science, 79110 Freiburg and Centre for Biological Signalling Studies (BIOSS), 79104 Freiburg, University of Freiburg, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Animals|Computational Biology|Humans|Internet|PDZ Domains|Peptides|Protein Binding|Software|Support Vector Machine|User-Computer Interface|src Homology Domains', 'Journal Article', '10.1093/bioinformatics/btu350', '24872426', 'MoDPepInt (Modular Domain Peptide Interaction) is a new easy-to-use web server for the prediction of binding partners for modular protein domains. Currently, we offer models for SH2, SH3 and PDZ domains via the tools SH2PepInt, SH3PepInt and PDZPepInt, respectively. More specifically, our server offers predictions for 51 SH2 human domains and 69 SH3 human domains via single domain models, and predictions for 226 PDZ domains across several species, via 43 multidomain models. All models are based on support vector machines with different kernel functions ranging from polynomial, to Gaussian, to advanced graph kernels. In this way, we model non-linear interactions between amino acid residues. Results were validated on manually curated datasets achieving competitive performance against various state-of-the-art approaches.'),
(78438, 2014, 'bio', 'DualAligner: a dual alignment-based strategy to align protein interaction networks', 'Seah, Boon-Siew|Bhowmick, Sourav S|Dewey, C Forbes', 'Division of Software and Information Systems, School of Computer Engineering, Nanyang Technological University, Singapore-MIT Alliance, Nanyang Technological University, Singapore 639798 and Biological Engineering Department, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA Division of Software and Information Systems, School of Computer Engineering, Nanyang Technological University, Singapore-MIT Alliance, Nanyang Technological University, Singapore 639798 and Biological Engineering Department, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.|Division of Software and Information Systems, School of Computer Engineering, Nanyang Technological University, Singapore-MIT Alliance, Nanyang Technological University, Singapore 639798 and Biological Engineering Department, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA Division of Software and Information Systems, School of Computer Engineering, Nanyang Technological University, Singapore-MIT Alliance, Nanyang Technological University, Singapore 639798 and Biological Engineering Department, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.|Division of Software and Information Systems, School of Computer Engineering, Nanyang Technological University, Singapore-MIT Alliance, Nanyang Technological University, Singapore 639798 and Biological Engineering Department, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA Division of Software and Information Systems, School of Computer Engineering, Nanyang Technological University, Singapore-MIT Alliance, Nanyang Technological University, Singapore 639798 and Biological Engineering Department, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.', 'Singapore|Singapore|Singapore', 12, 'Algorithms|Animals|Computational Biology|Gene Ontology|Humans|Molecular Sequence Annotation|Protein Interaction Mapping|Proteins', 'Journal Article', '10.1093/bioinformatics/btu358', '24872427', 'Given the growth of large-scale protein-protein interaction (PPI) networks obtained across multiple species and conditions, network alignment is now an important research problem. Network alignment performs comparative analysis across multiple PPI networks to understand their connections and relationships. However, PPI data in high-throughput experiments still suffer from significant false-positive and false-negatives rates. Consequently, high-confidence network alignment across entire PPI networks is not possible. At best, local network alignment attempts to alleviate this problem by completely ignoring low-confidence mappings, global network alignment, on the other hand, pairs all proteins regardless. To this end, we propose an alternative strategy: instead of full alignment across the entire network or completely ignoring low-confidence regions, we aim to perform highly specific protein-to-protein alignments where data confidence is high, and fall back on broader functional region-to-region alignment where detailed protein-protein alignment cannot be ascertained. The basic idea is to provide an alignment of multiple granularities to allow biological predictions at varying specificity.'),
(78439, 2014, 'bio', 'CAVER Analyst 10: graphic tool for interactive visualization and analysis of tunnels and channels in protein structures', 'Kozlikova, Barbora|Sebestova, Eva|Sustr, Vilem|Brezovsky, Jan|Strnad, Ondrej|Daniel, Lukas|Bednar, David|Pavelka, Antonin|Manak, Martin|Bezdeka, Martin|Benes, Petr|Kotry, Matus|Gora, Artur|Damborsky, Jiri|Sochor, Jiri', 'Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.|Department of Computer Graphics and Design, Human Computer Interaction Laboratory, Faculty of Informatics, Masaryk University, Botanicka 68a, 602 00 Brno, Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00 Brno and Department of Computer Science and Engineering, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Plzen, Czech Republic.', '-|-|-|-|-|-|-|-|-|-|-|-|-|-|-', 98, 'Binding Sites|Computational Biology|Computer Graphics|Ligands|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btu364', '24876375', 'The transport of ligands, ions or solvent molecules into proteins with buried binding sites or through the membrane is enabled by protein tunnels and channels. CAVER Analyst is a software tool for calculation, analysis and real-time visualization of access tunnels and channels in static and dynamic protein structures. It provides an intuitive graphic user interface for setting up the calculation and interactive exploration of identified tunnels/channels and their characteristics.'),
(78440, 2014, 'bio', 'Reference-free prediction of rearrangement breakpoint reads', 'Wijaya, Edward|Shimizu, Kana|Asai, Kiyoshi|Hamada, Michiaki', 'Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Osaka 565-0871, Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562 and Department of Electrical Engineering and Bioscience, Faculty of Science and Engineering, Waseda University, 55N-06-10, 3-4-1, Okubo Shinjuku-ku, Tokyo 169-8555, Japan.|Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Osaka 565-0871, Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562 and Department of Electrical Engineering and Bioscience, Faculty of Science and Engineering, Waseda University, 55N-06-10, 3-4-1, Okubo Shinjuku-ku, Tokyo 169-8555, Japan.|Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Osaka 565-0871, Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562 and Department of Electrical Engineering and Bioscience, Faculty of Science and Engineering, Waseda University, 55N-06-10, 3-4-1, Okubo Shinjuku-ku, Tokyo 169-8555, Japan Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Osaka 565-0871, Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562 and Department of Electrical Engineering and Bioscience, Faculty of Science and Engineering, Waseda University, 55N-06-10, 3-4-1, Okubo Shinjuku-ku, Tokyo 169-8555, Japan.|Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Osaka 565-0871, Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562 and Department of Electrical Engineering and Bioscience, Faculty of Science and Engineering, Waseda University, 55N-06-10, 3-4-1, Okubo Shinjuku-ku, Tokyo 169-8555, Japan Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Osaka 565-0871, Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562 and Department of Electrical Engineering and Bioscience, Faculty of Science and Engineering, Waseda University, 55N-06-10, 3-4-1, Okubo Shinjuku-ku, Tokyo 169-8555, Japan.', 'Japan|Japan|Japan|Japan', 0, 'Algorithms|Chromosome Breakpoints|Genomics|High-Throughput Nucleotide Sequencing|Humans|Male|Prostatic Neoplasms|Sequence Analysis, DNA|Software|Translocation, Genetic', 'Journal Article', '10.1093/bioinformatics/btu360', '24876376', 'Chromosome rearrangement events are triggered by atypical breaking and rejoining of DNA molecules, which are observed in many cancer-related diseases. The detection of rearrangement is typically done by using short reads generated by next-generation sequencing (NGS) and combining the reads with knowledge of a reference genome. Because structural variations and genomes differ from one person to another, intermediate comparison via a reference genome may lead to loss of information.'),
(78441, 2014, 'bio', 'PatternCNV: a versatile tool for detecting copy number changes from exome sequencing data', 'Wang, Chen|Evans, Jared M|Bhagwate, Aditya V|Prodduturi, Naresh|Sarangi, Vivekananda|Middha, Mridu|Sicotte, Hugues|Vedell, Peter T|Hart, Steven N|Oliver, Gavin R|Kocher, Jean-Pierre A|Maurer, Matthew J|Novak, Anne J|Slager, Susan L|Cerhan, James R|Asmann, Yan W', 'Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.|Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Division of Epidemiology, Department of Health Sciences Research, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 and Department of Health Sciences Research, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|DNA Copy Number Variations|Exome|Exons|Genomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btu363', '24876377', 'Exome sequencing (exome-seq) data, which are typically used for calling exonic mutations, have also been utilized in detecting DNA copy number variations (CNVs). Despite the existence of several CNV detection tools, there is still a great need for a sensitive and an accurate CNV-calling algorithm with built-in QC steps, and does not require a paired reference for each sample.'),
(78442, 2014, 'bio', 'EuGene-PP: a next-generation automated annotation pipeline for prokaryotic genomes', 'Sallet, Erika|Gouzy, Jérôme|Schiex, Thomas', 'Laboratoire Interactions Plantes Micro-organismes (LIPM) UMR441/2594, INRA/CNRS, F-31320 and INRA, Unité de Mathématiques et Informatique Appliques de Toulouse, UR 875, Castanet-Tolosan F-31326, France.|Laboratoire Interactions Plantes Micro-organismes (LIPM) UMR441/2594, INRA/CNRS, F-31320 and INRA, Unité de Mathématiques et Informatique Appliques de Toulouse, UR 875, Castanet-Tolosan F-31326, France.|Laboratoire Interactions Plantes Micro-organismes (LIPM) UMR441/2594, INRA/CNRS, F-31320 and INRA, Unité de Mathématiques et Informatique Appliques de Toulouse, UR 875, Castanet-Tolosan F-31326, France.', 'France|France|France', 17, 'Automation|Bacteria|Genome, Bacterial|Genomics|Molecular Sequence Annotation|Sequence Analysis, RNA|Software|Transcription Initiation Site', 'Journal Article', '10.1093/bioinformatics/btu366', '24880686', 'It is now easy and increasingly usual to produce oriented RNA-Seq data as a prokaryotic genome is being sequenced. However, this information is usually just used for expression quantification. EuGene-PP is a fully automated pipeline for structural annotation of prokaryotic genomes integrating protein similarities, statistical information and any oriented expression information (RNA-Seq or tiling arrays) through a variety of file formats to produce a qualitatively enriched annotation including coding regions but also (possibly antisense) non-coding genes and transcription start sites.'),
(78443, 2014, 'bio', 'Tedna: a transposable element de novo assembler', 'Zytnicki, Matthias|Akhunov, Eduard|Quesneville, Hadi', 'INRA, URGI, Plant Breeding and Biology, Versailles 78026, France and Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA.|INRA, URGI, Plant Breeding and Biology, Versailles 78026, France and Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA.|INRA, URGI, Plant Breeding and Biology, Versailles 78026, France and Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA.', 'France|France|France', 0, 'Arabidopsis|DNA Transposable Elements|Genomics|Repetitive Sequences, Nucleic Acid|Sequence Analysis, DNA|Triticum', 'Journal Article', '10.1093/bioinformatics/btu365', '24894500', 'Recent technological advances are allowing many laboratories to sequence their research organisms. Available de novo assemblers leave repetitive portions of the genome poorly assembled. Some genomes contain high proportions of transposable elements, and transposable elements appear to be a major force behind diversity and adaptation. Few de novo assemblers for transposable elements exist, and most have either been designed for small genomes or 454 reads.'),
(78444, 2014, 'bio', 'RAREMETAL: fast and powerful meta-analysis for rare variants', 'Feng, Shuang|Liu, Dajiang|Zhan, Xiaowei|Wing, Mary Kate|Abecasis, Gonçalo R', 'Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.|Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.|Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.|Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.|Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Computational Biology|Data Interpretation, Statistical|Genome-Wide Association Study|Genotype|Humans|Linkage Disequilibrium|Models, Statistical|Programming Languages|Quantitative Trait Loci|Reproducibility of Results|Software', 'Journal Article', '10.1093/bioinformatics/btu367', '24894501', 'RAREMETAL is a computationally efficient tool for meta-analysis of rare variants genotyped using sequencing or arrays. RAREMETAL facilitates analyses of individual studies, accommodates a variety of input file formats, handles related and unrelated individuals, executes both single variant and burden tests and performs conditional association analyses.'),
(78445, 2014, 'bio', 'PePr: a peak-calling prioritization pipeline to identify consistent or differential peaks from replicated ChIP-Seq data', 'Zhang, Yanxiao|Lin, Yu-Hsuan|Johnson, Timothy D|Rozek, Laura S|Sartor, Maureen A', 'Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, Department of Biostatistics and Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.', 'United States|United States|United States|United States|United States', 47, 'Algorithms|Animals|Cell Line, Tumor|Chromatin Immunoprecipitation|Epigenomics|Genomics|High-Throughput Nucleotide Sequencing|Mice|Nucleotide Motifs|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btu372', '24894502', 'ChIP-Seq is the standard method to identify genome-wide DNA-binding sites for transcription factors (TFs) and histone modifications. There is a growing need to analyze experiments with biological replicates, especially for epigenomic experiments where variation among biological samples can be substantial. However, tools that can perform group comparisons are currently lacking.'),
(78446, 2014, 'bio', 'Next maSigPro: updating maSigPro bioconductor package for RNA-seq time series', 'Nueda, María José|Tarazona, Sonia|Conesa, Ana', 'Statistics and Operational Research Department, University of Alicante, 03690, Alicante, Spain, Genomics of Gene Expression Laboratory, Prince Felipe Research Centre, 46012 Valencia, Spain and Applied Statistics, Operational Research and Quality Department, Polytechnic University of Valencia, 46020 Valencia, Spain.|Statistics and Operational Research Department, University of Alicante, 03690, Alicante, Spain, Genomics of Gene Expression Laboratory, Prince Felipe Research Centre, 46012 Valencia, Spain and Applied Statistics, Operational Research and Quality Department, Polytechnic University of Valencia, 46020 Valencia, Spain Statistics and Operational Research Department, University of Alicante, 03690, Alicante, Spain, Genomics of Gene Expression Laboratory, Prince Felipe Research Centre, 46012 Valencia, Spain and Applied Statistics, Operational Research and Quality Department, Polytechnic University of Valencia, 46020 Valencia, Spain.|Statistics and Operational Research Department, University of Alicante, 03690, Alicante, Spain, Genomics of Gene Expression Laboratory, Prince Felipe Research Centre, 46012 Valencia, Spain and Applied Statistics, Operational Research and Quality Department, Polytechnic University of Valencia, 46020 Valencia, Spain.', 'Spain|Spain|Spain', 0, 'Algorithms|Computational Biology|Gene Expression Profiling|Linear Models|Sequence Analysis, RNA|Software|Time Factors', 'Journal Article', '10.1093/bioinformatics/btu333', '24894503', 'The widespread adoption of RNA-seq to quantitatively measure gene expression has increased the scope of sequencing experimental designs to include time-course experiments. maSigPro is an R package specifically suited for the analysis of time-course gene expression data, which was developed originally for microarrays and hence was limited in its application to count data.'),
(78447, 2014, 'bio', 'Mirsynergy: detecting synergistic miRNA regulatory modules by overlapping neighbourhood expansion', 'Li, Yue|Liang, Cheng|Wong, Ka-Chun|Luo, Jiawei|Zhang, Zhaolei', 'Department of Computer Science, The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada, College of Information Science and Engineering, Hunan University, Changsha, Hunan, 410082, China and Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada Department of Computer Science, The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada, College of Information Science and Engineering, Hunan University, Changsha, Hunan, 410082, China and Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada.|Department of Computer Science, The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada, College of Information Science and Engineering, Hunan University, Changsha, Hunan, 410082, China and Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada.|Department of Computer Science, The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada, College of Information Science and Engineering, Hunan University, Changsha, Hunan, 410082, China and Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada Department of Computer Science, The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada, College of Information Science and Engineering, Hunan University, Changsha, Hunan, 410082, China and Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada.|Department of Computer Science, The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada, College of Information Science and Engineering, Hunan University, Changsha, Hunan, 410082, China and Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada.|Department of Computer Science, The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada, College of Information Science and Engineering, Hunan University, Changsha, Hunan, 410082, China and Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada Department of Computer Science, The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada, College of Information Science and Engineering, Hunan University, Changsha, Hunan, 410082, China and Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada Department of Computer Science, The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada, College of Information Science and Engineering, Hunan University, Changsha, Hunan, 410082, China and Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada.', 'Canada|Canada|Canada|Canada|Canada', 53, 'Algorithms|Binding Sites|Cluster Analysis|Computational Biology|Epistasis, Genetic|Female|Gene Regulatory Networks|Humans|MicroRNAs|Neoplasms|RNA, Messenger|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btu373', '24894504', 'Identification of microRNA regulatory modules (MiRMs) will aid deciphering aberrant transcriptional regulatory network in cancer but is computationally challenging. Existing methods are stochastic or require a fixed number of regulatory modules.');
