INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(74458, 2009, 'bio', 'DNAPlotter: circular and linear interactive genome visualization', 'Carver, Tim|Thomson, Nick|Bleasby, Alan|Berriman, Matthew|Parkhill, Julian', 'Wellcome Trust Sanger Institute, CB10 1SA and European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. artemis@sanger.ac.uk|Wellcome Trust Sanger Institute, CB10 1SA and European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. artemis@sanger.ac.uk|Wellcome Trust Sanger Institute, CB10 1SA and European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. artemis@sanger.ac.uk|Wellcome Trust Sanger Institute, CB10 1SA and European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. artemis@sanger.ac.uk|Wellcome Trust Sanger Institute, CB10 1SA and European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. artemis@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 475, 'Computational Biology|Genome|Salmonella typhi|Software', 'Journal Article', '10.1093/bioinformatics/btn578', '18990721', 'DNAPlotter is an interactive Java application for generating circular and linear representations of genomes. Making use of the Artemis libraries to provide a user-friendly method of loading in sequence files (EMBL, GenBank, GFF) as well as data from relational databases, it filters features of interest to display on separate user-definable tracks. It can be used to produce publication quality images for papers or web pages.'),
(74459, 2009, 'bio', 'A novel signaling pathway impact analysis', 'Tarca, Adi Laurentiu|Draghici, Sorin|Khatri, Purvesh|Hassan, Sonia S|Mittal, Pooja|Kim, Jung-Sun|Kim, Chong Jai|Kusanovic, Juan Pedro|Romero, Roberto', 'Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA.|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA.|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA.|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA.|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA.|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA.|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA.|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA.|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Colorectal Neoplasms|Computational Biology|Databases, Genetic|False Positive Reactions|Female|Humans|Labor, Obstetric|Models, Genetic|Pregnancy|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btn577', '18990722', 'Gene expression class comparison studies may identify hundreds or thousands of genes as differentially expressed (DE) between sample groups. Gaining biological insight from the result of such experiments can be approached, for instance, by identifying the signaling pathways impacted by the observed changes. Most of the existing pathway analysis methods focus on either the number of DE genes observed in a given pathway (enrichment analysis methods), or on the correlation between the pathway genes and the class of the samples (functional class scoring methods). Both approaches treat the pathways as simple sets of genes, disregarding the complex gene interactions that these pathways are built to describe.'),
(74460, 2009, 'bio', 'RANKPROP: a web server for protein remote homology detection', 'Melvin, Iain|Weston, Jason|Leslie, Christina|Noble, William Stafford', 'NEC Laboratories of America, Princeton, NJ, USA. iain@nec-labs.com|NEC Laboratories of America, Princeton, NJ, USA. iain@nec-labs.com|NEC Laboratories of America, Princeton, NJ, USA. iain@nec-labs.com|NEC Laboratories of America, Princeton, NJ, USA. iain@nec-labs.com', 'United States|United States|United States|United States', 16, 'Algorithms|Computational Biology|Databases, Protein|Internet|ROC Curve|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/btn567', '18990723', 'We present a large-scale implementation of the Rankprop protein homology ranking algorithm in the form of an openly accessible web server. We use the NRDB40 PSI-BLAST all-versus-all protein similarity network of 1.1 million proteins to construct the graph for the Rankprop algorithm, whereas previously, results were only reported for a database of 108 000 proteins. We also describe two algorithmic improvements to the original algorithm, including propagation from multiple homologs of the query and better normalization of ranking scores, that lead to higher accuracy and to scores with a probabilistic interpretation.'),
(74461, 2009, 'bio', 'Human genomes as email attachments', 'Christley, Scott|Lu, Yiming|Li, Chen|Xie, Xiaohui', 'Department of Computer Science, University of California Irvine, Irvine, CA 92697, USA.|Department of Computer Science, University of California Irvine, Irvine, CA 92697, USA.|Department of Computer Science, University of California Irvine, Irvine, CA 92697, USA.|Department of Computer Science, University of California Irvine, Irvine, CA 92697, USA.', 'United States|United States|United States|United States', 98, 'Algorithms|Data Compression|Databases, Genetic|Electronic Mail|Genome, Human|Humans', 'Journal Article', '10.1093/bioinformatics/btn582', '18996942', 'The amount of genomic sequence data being generated and made available through public databases continues to increase at an ever-expanding rate. Downloading, copying, sharing and manipulating these large datasets are becoming difficult and time consuming for researchers. We need to consider using advanced compression techniques as part of a standard data format for genomic data. The inherent structure of genome data allows for more efficient lossless compression than can be obtained through the use of generic compression programs. We apply a series of techniques to James Watsons genome that in combination reduce it to a mere 4MB, small enough to be sent as an email attachment.'),
(74462, 2009, 'bio', 'Pan-specific MHC class I predictors: a benchmark of HLA class I pan-specific prediction methods', 'Zhang, Hao|Lundegaard, Claus|Nielsen, Morten', 'Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby 2800, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby 2800, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby 2800, Denmark.', 'Denmark|Denmark|Denmark', 81, 'Alleles|Area Under Curve|Computational Biology|Databases, Protein|HLA Antigens|Histocompatibility Antigens Class I|Humans|Ligands|Peptides|Protein Binding|Statistics, Nonparametric', 'Journal Article', '10.1093/bioinformatics/btn579', '18996943', 'MHC:peptide binding plays a central role in activating the immune surveillance. Computational approaches to determine T-cell epitopes restricted to any given major histocompatibility complex (MHC) molecule are of special practical value in the development of for instance vaccines with broad population coverage against emerging pathogens. Methods have recently been published that are able to predict peptide binding to any human MHC class I molecule. In contrast to conventional allele-specific methods, these methods do allow for extrapolation to uncharacterized MHC molecules. These pan-specific human lymphocyte antigen (HLA) predictors have not previously been compared using independent evaluation sets.'),
(74463, 2009, 'bio', 'Discovery of phosphorylation motif mixtures in phosphoproteomics data', 'Ritz, Anna|Shakhnarovich, Gregory|Salomon, Arthur R|Raphael, Benjamin J', 'Department of Computer Science, Brown University, Toyota Technological Institute at Chicago, Chicago, IL, USA. aritz@cs.brown.edu|Department of Computer Science, Brown University, Toyota Technological Institute at Chicago, Chicago, IL, USA. aritz@cs.brown.edu|Department of Computer Science, Brown University, Toyota Technological Institute at Chicago, Chicago, IL, USA. aritz@cs.brown.edu|Department of Computer Science, Brown University, Toyota Technological Institute at Chicago, Chicago, IL, USA. aritz@cs.brown.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Animals|Cell Line, Tumor|Databases, Protein|Humans|Mice|Molecular Sequence Data|Phosphoproteins|Phosphorylation|Proteomics|ROC Curve|Receptor, ErbB-2|Reproducibility of Results', 'Journal Article', '10.1093/bioinformatics/btn569', '18996944', 'Modification of proteins via phosphorylation is a primary mechanism for signal transduction in cells. Phosphorylation sites on proteins are determined in part through particular patterns, or motifs, present in the amino acid sequence.'),
(74464, 2009, 'bio', 'ProtorP: a protein-protein interaction analysis server', 'Reynolds, Christopher|Damerell, David|Jones, Susan', 'Department of Biochemistry, School of Life Sciences, John Maynard Smith Building, University of Sussex, Falmer, Brighton BN1 9QG, UK.|Department of Biochemistry, School of Life Sciences, John Maynard Smith Building, University of Sussex, Falmer, Brighton BN1 9QG, UK.|Department of Biochemistry, School of Life Sciences, John Maynard Smith Building, University of Sussex, Falmer, Brighton BN1 9QG, UK.', 'United Kingdom|United Kingdom|United Kingdom', 158, 'Binding Sites|Databases, Protein|Internet|Protein Interaction Mapping|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn584', '19001476', 'The PROTORP server analyses protein-protein associations in 3D structures. The server calculates a series of physical and chemical parameters of the protein interaction sites that contribute to the binding energy of the association. These parameters include, size and shape, intermolecular bonding, residue and atom composition and secondary structure contributions. The server is flexible, in that it allows users to analyse individual protein associations or large datasets of associations deposited in the PDB, or upload and analyse proprietary files. The properties calculated can be compared with parameter distributions for non-homologous datasets of different classes of protein associations provided on the server website. The server provides an efficient way of characterizing protein-protein associations of new or existing proteins, and a means of putting these values in the context of previously observed associations.'),
(74465, 2009, 'bio', 'Decomposition of complex microbial behaviors into resource-based stress responses', 'Carlson, Ross P', 'Department of Chemical and Biological Engineering, Center for Biofilm Engineering and Thermal Biology Institute, Montana State University, Bozeman, MT 59717, USA. rossc@biofilms.montana.edu', 'United States', 28, 'Adaptation, Physiological|Computational Biology|Ecosystem|Escherichia coli|Least-Squares Analysis|Metabolic Networks and Pathways|Models, Biological|Stress, Physiological', 'Journal Article', '10.1093/bioinformatics/btn589', '19008248', 'Highly redundant metabolic networks and experimental data from cultures likely adapting simultaneously to multiple stresses can complicate the analysis of cellular behaviors. It is proposed that the explicit consideration of these factors is critical to understanding the competitive basis of microbial strategies.'),
(74466, 2009, 'bio', 'Predicting DNA recognition by Cys2His2 zinc finger proteins', 'Persikov, Anton V|Osada, Robert|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, USA.|Lewis-Sigler Institute for Integrative Genomics and Department of Computer Science, Princeton University, Princeton, NJ 08544, USA.', 'United States|United States|United States', 69, 'Amino Acid Sequence|Base Sequence|Computational Biology|Cysteine|DNA|DNA-Binding Proteins|Databases, Nucleic Acid|Early Growth Response Protein 1|Histidine|Models, Biological|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Zinc Fingers', 'Journal Article', '10.1093/bioinformatics/btn580', '19008249', 'Cys(2)His(2) zinc finger (ZF) proteins represent the largest class of eukaryotic transcription factors. Their modular structure and well-conserved protein-DNA interface allow the development of computational approaches for predicting their DNA-binding preferences even when no binding sites are known for a particular protein. The canonical model for ZF protein-DNA interaction consists of only four amino acid nucleotide contacts per zinc finger domain.'),
(74467, 2009, 'bio', 'MINOMICS: visualizing prokaryote transcriptomics and proteomics data in a genomic context', 'Brouwer, Rutger W W|van Hijum, Sacha A F T|Kuipers, Oscar P', 'Department of Molecular Genetics Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN, Haren, The Netherlands.|Department of Molecular Genetics Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN, Haren, The Netherlands.|Department of Molecular Genetics Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN, Haren, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 11, 'Computational Biology|Gene Expression Profiling|Genome|Internet|Prokaryotic Cells|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btn588', '19008250', 'We have developed MINOMICS, a tool that allows facile and in-depth visualization of prokaryotic transcriptomic and proteomic data in conjunction with genomics data. MINOMICS generates interactive linear genome maps in which multiple experimental datasets are displayed together with operon, regulatory motif, transcriptional promoter and transcriptional terminator information.'),
(74468, 2009, 'bio', 'Prediction of DNA-binding residues in proteins from amino acid sequences using a random forest model with a hybrid feature', 'Wu, Jiansheng|Liu, Hongde|Duan, Xueye|Ding, Yan|Wu, Hongtao|Bai, Yunfei|Sun, Xiao', 'State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China.|State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China.|State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China.|State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China.|State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China.|State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China.|State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China.', 'China|China|China|China|China|China|China', 101, 'Algorithms|Amino Acid Sequence|Amino Acids|Computational Biology|DNA|DNA-Binding Proteins|Databases, Protein|Models, Molecular|Protein Binding|ROC Curve', 'Journal Article', '10.1093/bioinformatics/btn583', '19008251', 'In this work, we aim to develop a computational approach for predicting DNA-binding sites in proteins from amino acid sequences. To avoid overfitting with this method, all available DNA-binding proteins from the Protein Data Bank (PDB) are used to construct the models. The random forest (RF) algorithm is used because it is fast and has robust performance for different parameter values. A novel hybrid feature is presented which incorporates evolutionary information of the amino acid sequence, secondary structure (SS) information and orthogonal binary vector (OBV) information which reflects the characteristics of 20 kinds of amino acids for two physical-chemical properties (dipoles and volumes of the side chains). The numbers of binding and non-binding residues in proteins are highly unbalanced, so a novel scheme is proposed to deal with the problem of imbalanced datasets by downsizing the majority class.'),
(74469, 2009, 'bio', 'The SNPMaP package for R: a framework for genome-wide association using DNA pooling on microarrays', 'Davis, Oliver S P|Plomin, Robert|Schalkwyk, Leonard C', 'Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Kings College London, London, UK. snpmap@iop.kcl.ac.uk|Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Kings College London, London, UK. snpmap@iop.kcl.ac.uk|Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Kings College London, London, UK. snpmap@iop.kcl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 23, 'DNA|Gene Frequency|Genome|Genome-Wide Association Study|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btn587', '19008252', 'Large-scale genome-wide association (GWA) studies using thousands of high-density SNP microarrays are becoming an essential tool in the search for loci related to heritable variation in many phenotypes. However, the cost of GWA remains beyond the reach of many researchers. Fortunately, the majority of statistical power can still be obtained by estimating allele frequencies from DNA pools, reducing the cost to that of tens, rather than thousands of arrays. We present a set of software tools for processing SNPMaP (SNP microarrays and pooling) data from CEL files to Relative Allele Scores in the rich R statistical computing environment.'),
(74470, 2009, 'bio', 'Combining multiple positive training sets to generate confidence scores for protein-protein interactions', 'Yu, Jingkai|Finley, Russell L', 'Center for Molecular Medicine and Genetics and Department of Biochemistry and Molecular Biology, School of Medicine, Wayne State University, 540 East Canfield, Detroit, MI 48201, USA.|Center for Molecular Medicine and Genetics and Department of Biochemistry and Molecular Biology, School of Medicine, Wayne State University, 540 East Canfield, Detroit, MI 48201, USA.', 'United States|United States', 36, 'Animals|Computational Biology|Confidence Intervals|Databases, Protein|Drosophila melanogaster|Humans|Principal Component Analysis|Protein Interaction Mapping', 'Journal Article', '10.1093/bioinformatics/btn597', '19010802', 'High-throughput experimental and computational methods are generating a wealth of protein-protein interaction data for a variety of organisms. However, data produced by current state-of-the-art methods include many false positives, which can hinder the analyses needed to derive biological insights. One way to address this problem is to assign confidence scores that reflect the reliability and biological significance of each interaction. Most previously described scoring methods use a set of likely true positives to train a model to score all interactions in a dataset. A single positive training set, however, may be biased and not representative of true interaction space.'),
(74471, 2009, 'bio', 'Genetic algorithms for simultaneous variable and sample selection in metabonomics', 'Cavill, Rachel|Keun, Hector C|Holmes, Elaine|Lindon, John C|Nicholson, Jeremy K|Ebbels, Timothy M D', 'Department of Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology and Anaesthetics, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, UK. r.cavill@imperial.ac.uk|Department of Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology and Anaesthetics, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, UK. r.cavill@imperial.ac.uk|Department of Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology and Anaesthetics, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, UK. r.cavill@imperial.ac.uk|Department of Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology and Anaesthetics, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, UK. r.cavill@imperial.ac.uk|Department of Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology and Anaesthetics, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, UK. r.cavill@imperial.ac.uk|Department of Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology and Anaesthetics, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, UK. r.cavill@imperial.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Databases, Genetic|Metabolomics|Principal Component Analysis|Rats|Rats, Sprague-Dawley|Time Factors', 'Journal Article', '10.1093/bioinformatics/btn586', '19010803', 'Metabolic profiles derived from high resolution (1)H-NMR data are complex, therefore statistical and machine learning approaches are vital for extracting useful information and biological insights. Focused modelling on targeted subsets of metabolites and samples can improve the predictive ability of models, and techniques such as genetic algorithms (GAs) have a proven utility in feature selection problems. The Consortium for Metabonomic Toxicology (COMET) obtained temporal NMR spectra of urine from rats treated with model toxins and stressors. Here, we develop a GA approach which simultaneously selects sets of samples and spectral regions from the COMET database to build robust, predictive classifiers of liver and kidney toxicity.'),
(74472, 2009, 'bio', 'CRONOS: the cross-reference navigation server', 'Waegele, Brigitte|Dunger-Kaltenbach, Irmtraud|Fobo, Gisela|Montrone, Corinna|Mewes, H-Werner|Ruepp, Andreas', 'Institute for Bioinformatics and Systems Biology (MIPS), Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. brigitte.waegele@helmholtz-muenchen.de|Institute for Bioinformatics and Systems Biology (MIPS), Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. brigitte.waegele@helmholtz-muenchen.de|Institute for Bioinformatics and Systems Biology (MIPS), Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. brigitte.waegele@helmholtz-muenchen.de|Institute for Bioinformatics and Systems Biology (MIPS), Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. brigitte.waegele@helmholtz-muenchen.de|Institute for Bioinformatics and Systems Biology (MIPS), Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. brigitte.waegele@helmholtz-muenchen.de|Institute for Bioinformatics and Systems Biology (MIPS), Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. brigitte.waegele@helmholtz-muenchen.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 14, 'Animals|Computational Biology|Genes|Humans|Internet|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btn590', '19010804', 'Cross-mapping of gene and protein identifiers between different databases is a tedious and time-consuming task. To overcome this, we developed CRONOS, a cross-reference server that contains entries from five mammalian organisms presented by major gene and protein information resources. Sequence similarity analysis of the mapped entries shows that the cross-references are highly accurate. In total, up to 18 different identifier types can be used for identification of cross-references. The quality of the mapping could be improved substantially by exclusion of ambiguous gene and protein names which were manually validated. Organism-specific lists of ambiguous terms, which are valuable for a variety of bioinformatics applications like text mining are available for download.'),
(74473, 2009, 'bio', 'Align human interactome with phenome to identify causative genes and networks underlying disease families', 'Wu, Xuebing|Liu, Qifang|Jiang, Rui', 'MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.', 'China|China|China', 74, 'Computational Biology|Crohn Disease|Disease|Gene Regulatory Networks|Genome, Human|Humans|Phenotype', 'Journal Article', '10.1093/bioinformatics/btn593', '19010805', 'Understanding the complexity in gene-phenotype relationship is vital for revealing the genetic basis of common diseases. Recent studies on the basis of human interactome and phenome not only uncovers prevalent phenotypic overlap and genetic overlap between diseases, but also reveals a modular organization of the genetic landscape of human diseases, providing new opportunities to reduce the complexity in dissecting the gene-phenotype association.'),
(74474, 2009, 'bio', 'Phospholipid scramblases and Tubby-like proteins belong to a new superfamily of membrane tethered transcription factors', 'Bateman, Alex|Finn, Robert D|Sims, Peter J|Wiedmer, Therese|Biegert, Andreas|Söding, Johannes', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. agb@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. agb@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. agb@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. agb@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. agb@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. agb@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 43, 'Amino Acid Sequence|Arabidopsis Proteins|Cell Membrane|Crystallography, X-Ray|Databases, Protein|Membrane Proteins|Models, Molecular|Molecular Sequence Data|Phospholipid Transfer Proteins|Protein Conformation|Sequence Alignment|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btn595', '19010806', 'Phospholipid scramblases (PLSCRs) constitute a family of cytoplasmic membrane-associated proteins that were identified based upon their capacity to mediate a Ca(2+)-dependent bidirectional movement of phospholipids across membrane bilayers, thereby collapsing the normally asymmetric distribution of such lipids in cell membranes. The exact function and mechanism(s) of these proteins nevertheless remains obscure: data from several laboratories now suggest that in addition to their putative role in mediating transbilayer flip/flop of membrane lipids, the PLSCRs may also function to regulate diverse processes including signaling, apoptosis, cell proliferation and transcription. A major impediment to deducing the molecular details underlying the seemingly disparate biology of these proteins is the current absence of any representative molecular structures to provide guidance to the experimental investigation of their function.'),
(74475, 2009, 'bio', 'Selection of oligonucleotides for whole-genome microarrays with semi-automatic update', 'Golfier, G|Lemoine, S|van Miltenberg, A|Bendjoudi, A|Rossier, J|Le Crom, S|Potier, M-C', 'Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France.|Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France.|Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France.|Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France.|Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France.|Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France.|Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France.', 'France|France|France|France|France|France|France', 6, 'Algorithms|Automation|Computational Biology|Databases, Nucleic Acid|Genome|Oligonucleotide Array Sequence Analysis|Oligonucleotides|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn573', '19015129', 'Oligonucleotide microarray probes are designed to match specific transcripts present in databases that are regularly updated. As a consequence probes should be checked every new database release. We thus developed an informatics tool allowing the semi-automatic update of probe collections of long oligonucleotides and applied it to the mouse RefSeq database.'),
(74476, 2009, 'bio', 'Prediction of translation initiation site for microbial genomes with TriTISA', 'Hu, Gang-Qing|Zheng, Xiaobin|Zhu, Huai-Qiu|She, Zhen-Su', 'State Key Lab for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering and Center for Theoretical Biology, Peking University, Beijing 100871, China.|State Key Lab for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering and Center for Theoretical Biology, Peking University, Beijing 100871, China.|State Key Lab for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering and Center for Theoretical Biology, Peking University, Beijing 100871, China.|State Key Lab for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering and Center for Theoretical Biology, Peking University, Beijing 100871, China.', 'China|China|China|China', 0, 'Base Sequence|Computational Biology|Genome, Bacterial|Protein Biosynthesis|Software', 'Journal Article', '10.1093/bioinformatics/btn576', '19015130', 'We report a new and simple method, TriTISA, for accurate prediction of translation initiation site (TIS) of microbial genomes. TriTISA classifies all candidate TISs into three categories based on evolutionary properties, and characterizes them in terms of Markov models. Then, it employs a Bayesian methodology for the selection of true TIS with a non-supervised, iterative procedure. Assessment on experimentally verified TIS data shows that TriTISA is overall better than all other methods of the state-of-the-art for microbial genome TIS prediction. In particular, TriTISA is shown to have a robust accuracy independent of the quality of initial annotation.'),
(74477, 2009, 'bio', 'Genetic association analysis with FAMHAP: a major program update', 'Herold, Christine|Becker, Tim', 'Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Sigmund-Freud-Str. 25, D-53105 Bonn, Germany. herold@imbie.meb.uni-bonn.de|Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Sigmund-Freud-Str. 25, D-53105 Bonn, Germany. herold@imbie.meb.uni-bonn.de', 'Germany|Germany', 52, 'Computational Biology|Genome-Wide Association Study|Haplotypes|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btn581', '19015131', 'FAMHAP is an established software for haplotype association analysis of nuclear families. We have released a major update that comprises various new features for case-control data. Furthermore, weprovide an additional program runFamhap that allows users to start the same method repeatedly for varying sets of genetic markers. In addition, a platform-independent graphical user interface (GUI) was developed to simplify the usage of both FAMHAP and runFamhap. The runFamhap program greatly facilitates the application of FAMHAP to genome-wide association studies (GWAS) and supports flexible genome-wide haplotype analysis. As an example, we describe application to HapMap data.'),
(74478, 2009, 'bio', 'Power enhancement via multivariate outlier testing with gene expression arrays', 'Asare, Adam L|Gao, Zhong|Carey, Vincent J|Wang, Richard|Seyfert-Margolis, Vicki', 'Immune Tolerance Network, University of California - San Francisco, San Francisco, CA 94143, USA. aasare@immunetolerance.org|Immune Tolerance Network, University of California - San Francisco, San Francisco, CA 94143, USA. aasare@immunetolerance.org|Immune Tolerance Network, University of California - San Francisco, San Francisco, CA 94143, USA. aasare@immunetolerance.org|Immune Tolerance Network, University of California - San Francisco, San Francisco, CA 94143, USA. aasare@immunetolerance.org|Immune Tolerance Network, University of California - San Francisco, San Francisco, CA 94143, USA. aasare@immunetolerance.org', 'United States|United States|United States|United States|United States', 0, 'Ambrosia|Clinical Trials as Topic|Gene Expression Profiling|Gene Expression Regulation|Humans|Hypersensitivity|Multivariate Analysis|Oligonucleotide Array Sequence Analysis|Principal Component Analysis', 'Journal Article', '10.1093/bioinformatics/btn591', '19015138', 'As the use of microarrays in human studies continues to increase, stringent quality assurance is necessary to ensure accurate experimental interpretation. We present a formal approach for microarray quality assessment that is based on dimension reduction of established measures of signal and noise components of expression followed by parametric multivariate outlier testing.'),
(74479, 2009, 'bio', 'EchoLOCATION: an in silico analysis of the subcellular locations of Escherichia coli proteins and comparison with experimentally derived locations', 'Horler, Richard S P|Butcher, Andrew|Papangelopoulos, Nikitas|Ashton, Peter D|Thomas, Gavin H', 'Department of Biology (Area 10), University of York, York, UK.|Department of Biology (Area 10), University of York, York, UK.|Department of Biology (Area 10), University of York, York, UK.|Department of Biology (Area 10), University of York, York, UK.|Department of Biology (Area 10), University of York, York, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 19, 'Algorithms|Bacterial Outer Membrane Proteins|Databases, Protein|Escherichia coli|Escherichia coli Proteins|Models, Biological|Periplasm|Proteome|Proteomics', 'Comparative Study', '10.1093/bioinformatics/btn596', '19015139', 'EchoLOCATION is a database that provides a comprehensive analysis of the subcellular locations of Escherichia coli K-12 proteins. Locations are predicted by integrating data from a range of publicly available algorithms combined with extensive curation of experimental literature. The data can be searched in a variety of ways and can generate lists of subcellular proteomes for analysis. Experimental evidence supports the locations of over 500 envelope proteins (periplasm, inner and outer membrane). From analysis of disagreements between in silico predictions and experimental data, we provide an analysis of protein types where subcellular prediction algorithms are currently not accurate.'),
(74480, 2009, 'bio', 'SIRIUS: decomposing isotope patterns for metabolite identification', 'Böcker, Sebastian|Letzel, Matthias C|Lipták, Zsuzsanna|Pervukhin, Anton', 'Lehrstuhl für Bioinformatik, Friedrich-Schiller-Universität Jena, Jena, Germany.|Lehrstuhl für Bioinformatik, Friedrich-Schiller-Universität Jena, Jena, Germany.|Lehrstuhl für Bioinformatik, Friedrich-Schiller-Universität Jena, Jena, Germany.|Lehrstuhl für Bioinformatik, Friedrich-Schiller-Universität Jena, Jena, Germany.', 'Germany|Germany|Germany|Germany', 168, 'Algorithms|Isotopes|Mass Spectrometry|Metabolomics|Molecular Weight|Software', 'Journal Article', '10.1093/bioinformatics/btn603', '19015140', 'High-resolution mass spectrometry (MS) is among the most widely used technologies in metabolomics. Metabolites participate in almost all cellular processes, but most metabolites still remain uncharacterized. Determination of the sum formula is a crucial step in the identification of an unknown metabolite, as it reduces its possible structures to a hopefully manageable set.'),
(74481, 2009, 'bio', 'Training set expansion: an approach to improving the reconstruction of biological networks from limited and uneven reliable interactions', 'Yip, Kevin Y|Gerstein, Mark', 'Department of Computer Science, Yale University, New Haven, CT 06511, USA.|Department of Computer Science, Yale University, New Haven, CT 06511, USA.', 'United States|United States', 0, 'Algorithms|Computational Biology|Gene Regulatory Networks|Models, Biological|Protein Interaction Mapping|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btn602', '19015141', 'An important problem in systems biology is reconstructing complete networks of interactions between biological objects by extrapolating from a few known interactions as examples. While there are many computational techniques proposed for this network reconstruction task, their accuracy is consistently limited by the small number of high-confidence examples, and the uneven distribution of these examples across the potential interaction space, with some objects having many known interactions and others few.'),
(74482, 2009, 'bio', 'MotifMap: a human genome-wide map of candidate regulatory motif sites', 'Xie, Xiaohui|Rigor, Paul|Baldi, Pierre', 'Department of Computer Sciences, University of California, Irvine, CA 92697, USA. xhx@ics.uci.edu|Department of Computer Sciences, University of California, Irvine, CA 92697, USA. xhx@ics.uci.edu|Department of Computer Sciences, University of California, Irvine, CA 92697, USA. xhx@ics.uci.edu', 'United States|United States|United States', 73, 'Algorithms|Animals|Bayes Theorem|Databases, Genetic|Genome|Genome, Human|Humans|Internet|Phylogeny|Polymorphism, Single Nucleotide|Regulatory Sequences, Nucleic Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn605', '19017655', 'Achieving a comprehensive map of all the regulatory elements encoded in the human genome is a fundamental challenge of biomedical research. So far, only a small fraction of the regulatory elements have been characterized, and there is great interest in applying computational techniques to systematically discover these elements. Such efforts, however, have been significantly hindered by the overwhelming size of non-coding DNA regions and the statistical variability and complex spatial organizations of mammalian regulatory elements.'),
(74483, 2008, 'bio', 'Motif Tool Manager: a web-based framework for motif discovery', 'Phan, Vinhthuy|Furlotte, Nicholas A', 'Department of Computer Science, The Bioinformatics Program and The W. Harry Feinstone Center for Genomics Research, The University of Memphis, Memphis, TN 38152, USA. vphan@memphis.edu|Department of Computer Science, The Bioinformatics Program and The W. Harry Feinstone Center for Genomics Research, The University of Memphis, Memphis, TN 38152, USA. vphan@memphis.edu', 'United States|United States', 2, 'Algorithms|DNA|Internet|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btn559', '19017656', 'Motif Tool Manager is a web-based framework for comparing and combining different approaches to discover novel DNA motifs. It comes with a set of five well-known approaches to motif discovery. It provides an easy mechanism for adding new motif finding tools to the framework through a web-interface and a minimal setup of the tools on the server. Users can execute the tools through the web-based framework and compare results from such executions. The framework provides a basic mechanism for identifying the most similar motif candidates found by a majority of themotif finding tools.'),
(74484, 2009, 'bio', 'Complexity reduction in context-dependent DNA substitution models', 'Majoros, William H|Ohler, Uwe', 'Institute for Genome Sciences & Policy, Duke University, Durham, NC, USA. bmajoros@duke.edu|Institute for Genome Sciences & Policy, Duke University, Durham, NC, USA. bmajoros@duke.edu', 'United States|United States', 0, 'Algorithms|Bayes Theorem|Computer Simulation|DNA|Genome|Models, Genetic|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btn598', '19017657', 'The modeling of conservation patterns in genomic DNA has become increasingly popular for a number of bioinformatic applications. While several systems developed to date incorporate context-dependence in their substitution models, the impact on computational complexity and generalization ability of the resulting higher order models invites the question of whether simpler approaches to context modeling might permit appreciable reductions in model complexity and computational cost, without sacrificing prediction accuracy.'),
(74485, 2009, 'bio', 'Bag of Peaks: interpretation of NMR spectrometry', 'Brelstaff, Gavin|Bicego, Manuele|Culeddu, Nicola|Chessa, Matilde', 'Biocomputing, CRS4, Sardinia, Italy. gjb@crs4.it|Biocomputing, CRS4, Sardinia, Italy. gjb@crs4.it|Biocomputing, CRS4, Sardinia, Italy. gjb@crs4.it|Biocomputing, CRS4, Sardinia, Italy. gjb@crs4.it', 'Italy|Italy|Italy|Italy', 14, 'Algorithms|Child|Diabetes Mellitus, Type 1|Humans|Nuclear Magnetic Resonance, Biomolecular|Principal Component Analysis', 'Journal Article', '10.1093/bioinformatics/btn599', '19017658', 'The analysis of high-resolution proton nuclear magnetic resonance (NMR) spectrometry can assist human experts to implicate metabolites expressed by diseased biofluids. Here, we explore an intermediate representation, between spectral trace and classifier, able to furnish a communicative interface between expert and machine. This representation permits equivalent, or better, classification accuracies than either principal component analysis (PCA) or multi-dimensional scaling (MDS). In the training phase, the peaks in each trace are detected and clustered in order to compile a common dictionary, which could be visualized and adjusted by an expert. The dictionary is used to characterize each trace with a fixed-length feature vector, termed Bag of Peaks, ready to be classified with classical supervised methods.'),
(74486, 2009, 'bio', 'CleaveLand: a pipeline for using degradome data to find cleaved small RNA targets', 'Addo-Quaye, Charles|Miller, Webb|Axtell, Michael J', 'Department of Computer Science and Engineering and Department of Biology, Pennsylvania State University, University Park, PA 16802, USA.|Department of Computer Science and Engineering and Department of Biology, Pennsylvania State University, University Park, PA 16802, USA.|Department of Computer Science and Engineering and Department of Biology, Pennsylvania State University, University Park, PA 16802, USA.', 'United States|United States|United States', 323, 'Base Sequence|Computational Biology|MicroRNAs|Molecular Sequence Data|RNA Stability|Software', 'Journal Article', '10.1093/bioinformatics/btn604', '19017659', 'MicroRNAs (miRNAs) are approximately 20- to 22-nt long endogenous RNA sequences that play a critical role in the regulation of gene expression in eukaryotic genomes. Confident identification of miRNA targets is vital to understand their functions. Currently available computational algorithms for miRNA target prediction have diverse degrees of sensitivity and specificity and as a consequence each predicted target generally requires experimental confirmation. miRNAs and other small RNAs that direct endonucleolytic cleavage of target mRNAs produce diagnostic uncapped, polyadenylated mRNA fragments. Degradome sequencing [also known as PARE (parallel analysis of RNA ends) and GMUCT (genome-wide mapping of uncapped transcripts)] samples the 5-ends of uncapped mRNAs and can be used to discover in vivo miRNA targets independent of computational predictions. Here, we describe a generalizable computational pipeline, CleaveLand, for the detection of cleaved miRNA targets from degradome data. CleaveLand takes as input degradome sequences, small RNAs and an mRNA database and outputs small RNA targets. CleaveLand can thus be applied to degradome data from any species provided a set of mRNA transcripts and a set of query miRNAs or other small RNAs are available.'),
(74487, 2009, 'bio', 'A practical method for exact computation of subtree prune and regraft distance', 'Wu, Yufeng', 'Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA. ywu@engr.uconn.edu', 'United States', 0, 'Computational Biology|Databases, Genetic|Phylogeny|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn606', '19019848', 'Subtree prune and regraft (SPR) is one kind of tree rearrangements that has seen applications in solving several computational biology problems. The minimum number of rooted SPR ((r)SPR) operations needed to transform one rooted binary tree to another is called the (r)SPR distance between the two trees. Computing the (r)SPR distance has been actively studied in recent years. Currently, there is a lack of practical software tools for computing the (r)SPR distance for relatively large trees with large (r)SPR distance.'),
(74488, 2009, 'bio', 'A multivariate test of association', 'Ferreira, Manuel A R|Purcell, Shaun M', 'Department of Psychiatry, Massachusetts General Hospital, Boston, USA. manuel.ferreira@qimr.edu.au|Department of Psychiatry, Massachusetts General Hospital, Boston, USA. manuel.ferreira@qimr.edu.au', 'United States|United States', 147, 'Genetic Predisposition to Disease|Humans|Multivariate Analysis', 'Journal Article', '10.1093/bioinformatics/btn563', '19019849', 'Although genetic association studies often test multiple, related phenotypes, few formal multivariate tests of association are available. We describe a test of association that can be efficiently applied to large population-based designs.'),
(74489, 2009, 'bio', 'Phylogenetic inference under recombination using Bayesian stochastic topology selection', 'Webb, Alex|Hancock, John M|Holmes, Chris C', 'Department of Statistics, Oxford, UK.|Department of Statistics, Oxford, UK.|Department of Statistics, Oxford, UK.', 'United Kingdom|United Kingdom|United Kingdom', 12, 'Algorithms|Animals|Bayes Theorem|Genome|Markov Chains|Mice|Phylogeny|Recombination, Genetic|Selection, Genetic|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btn607', '19028720', 'Conventional phylogenetic analysis for characterizing the relatedness between taxa typically assumes that a single relationship exists between species at every site along the genome. This assumption fails to take into account recombination which is a fundamental process for generating diversity and can lead to spurious results. Recombination induces a localized phylogenetic structure which may vary along the genome. Here, we generalize a hidden Markov model (HMM) to infer changes in phylogeny along multiple sequence alignments while accounting for rate heterogeneity, the hidden states refer to the unobserved phylogenic topology underlying the relatedness at a genomic location. The dimensionality of the number of hidden states (topologies) and their structure are random (not known a priori) and are sampled using Markov chain Monte Carlo algorithms. The HMM structure allows us to analytically integrate out over all possible changepoints in topologies as well as all the unknown branch lengths.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(74490, 2009, 'bio', 'GWAS GUI: graphical browser for the results of whole-genome association studies with high-dimensional phenotypes', 'Chen, Wei|Liang, Liming|Abecasis, Gonçalo R', 'Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA. weich@umich.edu|Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA. weich@umich.edu|Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA. weich@umich.edu', 'United States|United States|United States', 6, 'Computational Biology|Computer Graphics|Genome|Genome-Wide Association Study|Internet|Phenotype|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn600', '19028721', 'We describe an interactive package that provides graphical overviews of the results of whole-genome association studies in datasets with rich multi-dimensional phenotypic information, such as global surveys of gene expression. Windows, Linux and Mac binaries are available from our website.'),
(74491, 2009, 'bio', 'Prioritizing risk pathways: a novel association approach to searching for disease pathways fusing SNPs and pathways', 'Chen, Lina|Zhang, Liangcai|Zhao, Yan|Xu, Liangde|Shang, Yukui|Wang, Qian|Li, Wan|Wang, Hong|Li, Xia', 'College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenlina@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenlina@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenlina@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenlina@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenlina@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenlina@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenlina@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenlina@ems.hrbmu.edu.cn|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenlina@ems.hrbmu.edu.cn', 'China|China|China|China|China|China|China|China|China', 0, 'Gene Regulatory Networks|Genetic Predisposition to Disease|Genome, Human|Genotype|Humans|Odds Ratio|Polymorphism, Single Nucleotide|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btn613', '19029127', 'Complex diseases are generally thought to be under the influence of one or more mutated risk genes as well as genetic and environmental factors. Many traditional methods have been developed to identify susceptibility genes assuming a single-gene disease model (single-locus methods). Pathway-based approaches, combined with traditional methods, consider the joint effects of genetic factor and biologic network context. With the accumulation of high-throughput SNP datasets and human biologic pathways, it becomes feasible to search for risk pathways associated with complex diseases using bioinformatics methods. By analyzing the contribution of genetic factor and biologic network context in KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, we proposed an approach to prioritize risk pathways for complex diseases: Prioritizing Risk Pathways fusing SNPs and pathways (PRP). A risk-scoring (RS) measurement was used to prioritize risk biologic pathways. This could help to demonstrate the pathogenesis of complex diseases from a new perspective and provide new hypotheses. We introduced this approach to five complex diseases and found that these five diseases not only share common risk pathways, but also have their specific risk pathways, which is verified by literature retrieval.'),
(74492, 2009, 'bio', 'Impact of allelic dropout on evidential value of forensic DNA profiles using RMNE', 'Van Nieuwerburgh, F|Goetghebeur, E|Vandewoestyne, M|Deforce, D', 'Laboratory for Pharmaceutical Biotechnology, Ghent University, Ghent, Belgium.|Laboratory for Pharmaceutical Biotechnology, Ghent University, Ghent, Belgium.|Laboratory for Pharmaceutical Biotechnology, Ghent University, Ghent, Belgium.|Laboratory for Pharmaceutical Biotechnology, Ghent University, Ghent, Belgium.', 'Belgium|Belgium|Belgium|Belgium', 0, 'Alleles|DNA|DNA Fingerprinting|Forensic Medicine|Likelihood Functions', 'Journal Article', '10.1093/bioinformatics/btn608', '19029128', 'Two methods are commonly used to report on evidence carried by forensic DNA profiles: the Random Man Not Excluded (RMNE) approach and the likelihood ratio (LR) approach. It is often claimed a major advantage of the LR method that dropout can be assessed probabilistically.'),
(74493, 2009, 'bio', 'KEPE--a motif frequently superimposed on sumoylation sites in metazoan chromatin proteins and transcription factors', 'Diella, Francesca|Chabanis, Sophie|Luck, Katja|Chica, Claudia|Ramu, Chenna|Nerlov, Claus|Gibson, Toby J', 'Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.|Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.|Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.|Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.|Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.|Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.|Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Amino Acid Motifs|Amino Acid Sequence|Animals|Chromatin|Conserved Sequence|Databases, Protein|Gene Expression Regulation|Humans|Molecular Sequence Data|Mutation|Nucleoproteins|Proteome|Saccharomyces cerevisiae|Small Ubiquitin-Related Modifier Proteins|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btn594', '19033273', 'We noted that the sumoylation site in C/EBP homologues is conserved beyond the canonical consensus sequence for sumoylation. Therefore, we investigated whether this pattern might define a more general protein motif.'),
(74494, 2009, 'bio', 'AmiGO: online access to ontology and annotation data', 'Carbon, Seth|Ireland, Amelia|Mungall, Christopher J|Shu, ShengQiang|Marshall, Brad|Lewis, Suzanna|AmiGO Hub|Web Presence Working Group', 'Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. sjcarbon@berkeleybop.org|Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. sjcarbon@berkeleybop.org|Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. sjcarbon@berkeleybop.org|Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. sjcarbon@berkeleybop.org|Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. sjcarbon@berkeleybop.org|Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. sjcarbon@berkeleybop.org|Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. sjcarbon@berkeleybop.org|Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. sjcarbon@berkeleybop.org', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Computational Biology|Databases, Genetic|Information Storage and Retrieval|Internet|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn615', '19033274', 'AmiGO is a web application that allows users to query, browse and visualize ontologies and related gene product annotation (association) data. AmiGO can be used online at the Gene Ontology (GO) website to access the data provided by the GO Consortium, it can also be downloaded and installed to browse local ontologies and annotations. AmiGO is free open source software developed and maintained by the GO Consortium.'),
(74495, 2009, 'bio', 'LRpath: a logistic regression approach for identifying enriched biological groups in gene expression data', 'Sartor, Maureen A|Leikauf, George D|Medvedovic, Mario', 'Center for Computational Medicine and Biology, University of Michigan, Ann Arbor, MI, USA.|Center for Computational Medicine and Biology, University of Michigan, Ann Arbor, MI, USA.|Center for Computational Medicine and Biology, University of Michigan, Ann Arbor, MI, USA.', 'United States|United States|United States', 0, 'Algorithms|Computer Simulation|Databases, Genetic|Gene Expression|Gene Expression Profiling|Logistic Models|Oligonucleotide Array Sequence Analysis|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btn592', '19038984', 'The elucidation of biological pathways enriched with differentially expressed genes has become an integral part of the analysis and interpretation of microarray data. Several statistical methods are commonly used in this context, but the question of the optimal approach has still not been resolved.'),
(74496, 2009, 'bio', 'Sparse combinatorial inference with an application in cancer biology', 'Mukherjee, Sach|Pelech, Steven|Neve, Richard M|Kuo, Wen-Lin|Ziyad, Safiyyah|Spellman, Paul T|Gray, Joe W|Speed, Terence P', 'Department of Statistics, University of Warwick, Coventry, UK. s.n.mukherjee@warwick.ac.uk|Department of Statistics, University of Warwick, Coventry, UK. s.n.mukherjee@warwick.ac.uk|Department of Statistics, University of Warwick, Coventry, UK. s.n.mukherjee@warwick.ac.uk|Department of Statistics, University of Warwick, Coventry, UK. s.n.mukherjee@warwick.ac.uk|Department of Statistics, University of Warwick, Coventry, UK. s.n.mukherjee@warwick.ac.uk|Department of Statistics, University of Warwick, Coventry, UK. s.n.mukherjee@warwick.ac.uk|Department of Statistics, University of Warwick, Coventry, UK. s.n.mukherjee@warwick.ac.uk|Department of Statistics, University of Warwick, Coventry, UK. s.n.mukherjee@warwick.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 16, 'Algorithms|Computational Biology|Models, Statistical|Neoplasms|Proteins', 'Journal Article', '10.1093/bioinformatics/btn611', '19038985', 'Combinatorial effects, in which several variables jointly influence an output or response, play an important role in biological systems. In many settings, Boolean functions provide a natural way to describe such influences. However, biochemical data using which we may wish to characterize such influences are usually subject to much variability. Furthermore, in high-throughput biological settings Boolean relationships of interest are very often sparse, in the sense of being embedded in an overall dataset of higher dimensionality. This motivates a need for statistical methods capable of making inferences regarding Boolean functions under conditions of noise and sparsity.'),
(74497, 2009, 'bio', 'Identification of structurally conserved residues of proteins in absence of structural homologs using neural network ensemble', 'Pugalenthi, Ganesan|Tang, Ke|Suganthan, P N|Chakrabarti, Saikat', 'School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.|School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.|School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.|School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.', 'Singapore|Singapore|Singapore|Singapore', 0, 'Computational Biology|Conserved Sequence|Databases, Protein|Neural Networks (Computer)|Protein Conformation|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1093/bioinformatics/btn618', '19038986', 'So far various bioinformatics and machine learning techniques applied for identification of sequence and functionally conserved residues in proteins. Although few computational methods are available for the prediction of structurally conserved residues from protein structure, almost all methods require homologous structural information and structure-based alignments, which still prove to be a bottleneck in protein structure comparison studies. In this work, we developed a neural network approach for identification of structurally important residues from a single protein structure without using homologous structural information and structural alignment.'),
(74498, 2009, 'bio', 'MFEprimer: multiple factor evaluation of the specificity of PCR primers', 'Qu, Wubin|Shen, Zhiyong|Zhao, Dongsheng|Yang, Yi|Zhang, Chenggang', 'Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing, China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing, China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing, China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing, China.|Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing, China.', 'China|China|China|China|China', 36, 'Computational Biology|DNA Primers|Databases, Nucleic Acid|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btn614', '19038987', 'We developed a program named MFEprimer for evaluating the specificity of PCR primers based on multiple factors, including sequence similarity, stability at the 3-end of the primer, melting temperature, GC content and number of binding sites between the primer and DNA templates. MFEprimer can help the user to select more suitable primers before running either standard or multiplex PCR reactions. The cDNA and genomic DNA databases of 10 widely used species, as well as user custom databases, were used as DNA templates for analyzing primers specificity. Furthermore, we maintained a Primer3Plus server with a modified Primer3Manager for one-stop primer design and specificity checking.'),
(74499, 2009, 'bio', 'MAGETabulator, a suite of tools to support the microarray data format MAGE-TAB', 'Rayner, Tim F|Rezwan, Faisal Ibne|Lukk, Margus|Bradley, Xiangqun Zheng|Farne, Anna|Holloway, Ele|Malone, James|Williams, Eleanor|Parkinson, Helen', 'EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK. tfrayner@gmail.com|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK. tfrayner@gmail.com|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK. tfrayner@gmail.com|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK. tfrayner@gmail.com|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK. tfrayner@gmail.com|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK. tfrayner@gmail.com|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK. tfrayner@gmail.com|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK. tfrayner@gmail.com|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK. tfrayner@gmail.com', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Software|Software Validation', 'Journal Article', '10.1093/bioinformatics/btn617', '19038988', 'The MAGE-TAB format for microarray data representation and exchange has been proposed by the microarray community to replace the more complex MAGE-ML format. We present a suite of tools to support MAGE-TAB generation and validation, conversion between existing formats for data exchange, visualization of the experiment designs encoded by MAGE-TAB documents and the mining of such documents for semantic content.'),
(74500, 2009, 'bio', 'Gene-disease relationship discovery based on model-driven data integration and database view definition', 'Yilmaz, S|Jonveaux, P|Bicep, C|Pierron, L|Smaïl-Tabbone, M|Devignes, M D', 'Laboratory for Human Genetics, Nancy Medical Faculty, Vandoeuvre-les-Nancy, France.|Laboratory for Human Genetics, Nancy Medical Faculty, Vandoeuvre-les-Nancy, France.|Laboratory for Human Genetics, Nancy Medical Faculty, Vandoeuvre-les-Nancy, France.|Laboratory for Human Genetics, Nancy Medical Faculty, Vandoeuvre-les-Nancy, France.|Laboratory for Human Genetics, Nancy Medical Faculty, Vandoeuvre-les-Nancy, France.|Laboratory for Human Genetics, Nancy Medical Faculty, Vandoeuvre-les-Nancy, France.', 'France|France|France|France|France|France', 0, 'Algorithms|Animals|Computational Biology|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Genetic Predisposition to Disease|Genomics|Humans', 'Journal Article', '10.1093/bioinformatics/btn612', '19042916', 'Computational methods are widely used to discover gene-disease relationships hidden in vast masses of available genomic and post-genomic data. In most current methods, a similarity measure is calculated between gene annotations and known disease genes or disease descriptions. However, more explicit gene-disease relationships are required for better insights into the molecular bases of diseases, especially for complex multi-gene diseases.'),
(74501, 2009, 'bio', 'Programs for calculating the statistical powers of detecting susceptibility genes in case-control studies based on multistage designs', 'Kitamura, Nobutaka|Akazawa, Kouhei|Miyashita, Akinori|Kuwano, Ryozo|Toyabe, Shin-ichi|Nakamura, Junichiro|Nakamura, Norihito|Sato, Tatsuhiko|Hoque, M Aminul', 'Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan. nktmr@m12.alpha-net.ne.jp|Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan. nktmr@m12.alpha-net.ne.jp|Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan. nktmr@m12.alpha-net.ne.jp|Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan. nktmr@m12.alpha-net.ne.jp|Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan. nktmr@m12.alpha-net.ne.jp|Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan. nktmr@m12.alpha-net.ne.jp|Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan. nktmr@m12.alpha-net.ne.jp|Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan. nktmr@m12.alpha-net.ne.jp|Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan. nktmr@m12.alpha-net.ne.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 3, 'Algorithms|Case-Control Studies|Genetic Predisposition to Disease|Genome-Wide Association Study|Humans|Models, Statistical|Polymorphism, Single Nucleotide|Predictive Value of Tests|Software', 'Journal Article', '10.1093/bioinformatics/btn616', '19043077', 'A two-stage association study is the most commonly used method among multistage designs to efficiently identify disease susceptibility genes. Recently, some SNP studies have utilized more than two stages to detect disease genes. However, there are few available programs for calculating statistical powers and positive predictive values (PPVs) of arbitrary n-stage designs.'),
(74502, 2009, 'bio', 'Gene expression trends and protein features effectively complement each other in gene function prediction', 'Wabnik, Krzysztof|Hvidsten, Torgeir R|Kedzierska, Anna|Van Leene, Jelle|De Jaeger, Geert|Beemster, Gerrit T S|Komorowski, Jan|Kuiper, Martin T R', 'Department of Plant Systems Biology, VIB Technologiepark 927, 9052 Gent, Belgium. krwab@psb.ugent.be|Department of Plant Systems Biology, VIB Technologiepark 927, 9052 Gent, Belgium. krwab@psb.ugent.be|Department of Plant Systems Biology, VIB Technologiepark 927, 9052 Gent, Belgium. krwab@psb.ugent.be|Department of Plant Systems Biology, VIB Technologiepark 927, 9052 Gent, Belgium. krwab@psb.ugent.be|Department of Plant Systems Biology, VIB Technologiepark 927, 9052 Gent, Belgium. krwab@psb.ugent.be|Department of Plant Systems Biology, VIB Technologiepark 927, 9052 Gent, Belgium. krwab@psb.ugent.be|Department of Plant Systems Biology, VIB Technologiepark 927, 9052 Gent, Belgium. krwab@psb.ugent.be|Department of Plant Systems Biology, VIB Technologiepark 927, 9052 Gent, Belgium. krwab@psb.ugent.be', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 6, 'Computational Biology|Databases, Genetic|Databases, Protein|Gene Expression|Gene Expression Profiling|Genome|Genomics|Proteins', 'Journal Article', '10.1093/bioinformatics/btn625', '19050035', 'Genome-scale omics data constitute a potentially rich source of information about biological systems and their function. There is a plethora of tools and methods available to mine omics data. However, the diversity and complexity of different omics data types is a stumbling block for multi-data integration, hence there is a dire need for additional methods to exploit potential synergy from integrated orthogonal data. Rough Sets provide an efficient means to use complex information in classification approaches. Here, we set out to explore the possibilities of Rough Sets to incorporate diverse information sources in a functional classification of unknown genes.'),
(74503, 2009, 'bio', 'Computationally feasible estimation of haplotype frequencies from pooled DNA with and without Hardy-Weinberg equilibrium', 'Kuk, Anthony Y C|Zhang, Han|Yang, Yaning', 'Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546. stakuka@nus.edu.sg|Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546. stakuka@nus.edu.sg|Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546. stakuka@nus.edu.sg', 'Singapore|Singapore|Singapore', 12, 'Algorithms|Computational Biology|Computer Simulation|DNA|Gene Frequency|Genome-Wide Association Study|Haplotypes', 'Journal Article', '10.1093/bioinformatics/btn623', '19050036', 'Pooling large number of DNA samples is a common practice in association study, especially for initial screening. However, the use of expectation-maximization (EM)-type algorithms in estimating haplotype distributions for even moderate pool sizes is hampered by the computational complexity involved. A novel constrained EM algorithm called PoooL has been proposed recently to bypass the difficulty via the use of asymptotic normality of the pooled allele frequencies. The resulting estimates are, however, not maximum likelihood estimates and hence not optimal. Furthermore, the assumption of Hardy-Weinberg equilibrium (HWE) made may not be realistic in practice.'),
(74504, 2009, 'bio', 'Reference alignment of SNP microarray signals for copy number analysis of tumors', 'Pounds, Stan|Cheng, Cheng|Mullighan, Charles|Raimondi, Susana C|Shurtleff, Sheila|Downing, James R', 'Department of Biostatistics, St. Jude Childrens Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA. stanley.pounds@stjude.org|Department of Biostatistics, St. Jude Childrens Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA. stanley.pounds@stjude.org|Department of Biostatistics, St. Jude Childrens Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA. stanley.pounds@stjude.org|Department of Biostatistics, St. Jude Childrens Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA. stanley.pounds@stjude.org|Department of Biostatistics, St. Jude Childrens Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA. stanley.pounds@stjude.org|Department of Biostatistics, St. Jude Childrens Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA. stanley.pounds@stjude.org', 'United States|United States|United States|United States|United States|United States', 41, 'Algorithms|Biomarkers, Tumor|Chromosome Aberrations|Cluster Analysis|Computational Biology|Gene Dosage|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btn624', '19052058', 'A new procedure to align single nucleotide polymorphism (SNP) microarray signals for copy number analysis is proposed. For each individual array, this reference alignment procedure (RAP) uses a set of selected markers as internal references to direct the signal alignment. RAP aligns the signals so that each array has a similar signal distribution among its reference markers. An accompanying reference selection algorithm (RSA) uses genotype calls and initial signal intensities to choose two-copy markers as the internal references for each array. After RSA and RAP are applied, each array has a similar distribution of signals of two-copy markers so that across-array signal comparisons are biologically meaningful. An upper bound for a statistical metric of signal misalignment is derived and provides a theoretical basis to choose RSA-RAP over other alignment procedures for copy number analysis of cancers. In our study of acute lymphoblastic leukemia, RSA-RAP gives copy number analysis results that show substantially better concordance with cytogenetics than do two other alignment procedures.'),
(74505, 2009, 'bio', 'Estimation of errors introduced by confocal imaging into the data on segmentation gene expression in Drosophila', 'Myasnikova, Ekaterina|Surkova, Svetlana|Panok, Lena|Samsonova, Maria|Reinitz, John', 'St Petersburg State Polytechnic University, St Petersburg, 195251, Russia. myasnikova@spbcas.ru|St Petersburg State Polytechnic University, St Petersburg, 195251, Russia. myasnikova@spbcas.ru|St Petersburg State Polytechnic University, St Petersburg, 195251, Russia. myasnikova@spbcas.ru|St Petersburg State Polytechnic University, St Petersburg, 195251, Russia. myasnikova@spbcas.ru|St Petersburg State Polytechnic University, St Petersburg, 195251, Russia. myasnikova@spbcas.ru', '-|-|-|-|-', 0, 'Animals|Blastoderm|Drosophila|Gene Expression|Gene Expression Profiling|Genes, Insect|Image Processing, Computer-Assisted|Microscopy, Confocal|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/btn620', '19052059', 'Currently the confocal scanning microscopy of fluorescently tagged molecules is extensively employed to acquire quantitative data on gene expression at cellular resolution. Following this approach, we generated a large dataset on the expression of segmentation genes in the Drosophila blastoderm, that is widely used in systems biology studies. As data accuracy is of critical importance for the success of studies in this field, we took a shot to evaluate possible errors introduced in the data by acquisition and processing methods. This article deals with errors introduced by confocal microscope.'),
(74506, 2009, 'bio', 'A predictive model for identifying mini-regulatory modules in the mouse genome', 'Yaragatti, Mahesh|Sandler, Ted|Ungar, Lyle', 'Biotechnology Program, CIS, University of Pennsylvania, 3330 Walnut Street, Philadelphia, PA 19104, USA. myar@seas.upenn.edu|Biotechnology Program, CIS, University of Pennsylvania, 3330 Walnut Street, Philadelphia, PA 19104, USA. myar@seas.upenn.edu|Biotechnology Program, CIS, University of Pennsylvania, 3330 Walnut Street, Philadelphia, PA 19104, USA. myar@seas.upenn.edu', 'United States|United States|United States', 0, 'Algorithms|Animals|Computational Biology|Databases, Nucleic Acid|Expressed Sequence Tags|Genome|Genomics|Mice|RNA, Messenger|Regulatory Sequences, Nucleic Acid', 'Journal Article', '10.1093/bioinformatics/btn622', '19052060', 'Rapidly advancing genome technology has allowed access to a large number of diverse genomes and annotation data. We have defined a systems model that integrates assembly data, comparative genomics, gene predictions, mRNA and EST alignments and physiological tissue expression. Using these as predictive parameters, we engineered a machine learning approach to decipher putative active regions in the genome.'),
(74507, 2009, 'bio', 'Aneuploidy prediction and tumor classification with heterogeneous hidden conditional random fields', 'Barutcuoglu, Zafer|Airoldi, Edoardo M|Dumeaux, Vanessa|Schapire, Robert E|Troyanskaya, Olga G', 'Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ 08540, USA.|Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ 08540, USA.|Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ 08540, USA.|Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ 08540, USA.|Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ 08540, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Aneuploidy|Comparative Genomic Hybridization|Computational Biology|Gene Dosage|Neoplasms|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btn585', '19052061', 'The heterogeneity of cancer cannot always be recognized by tumor morphology, but may be reflected by the underlying genetic aberrations. Array comparative genome hybridization (array-CGH) methods provide high-throughput data on genetic copy numbers, but determining the clinically relevant copy number changes remains a challenge. Conventional classification methods for linking recurrent alterations to clinical outcome ignore sequential correlations in selecting relevant features. Conversely, existing sequence classification methods can only model overall copy number instability, without regard to any particular position in the genome.'),
(74508, 2009, 'bio', 'Sequence progressive alignment, a framework for practical large-scale probabilistic consistency alignment', 'Paten, Benedict|Herrero, Javier|Beal, Kathryn|Birney, Ewan', 'Department of Engineering, University of California, Santa Cruz CA, USA. benedict@soe.ucsc.edu|Department of Engineering, University of California, Santa Cruz CA, USA. benedict@soe.ucsc.edu|Department of Engineering, University of California, Santa Cruz CA, USA. benedict@soe.ucsc.edu|Department of Engineering, University of California, Santa Cruz CA, USA. benedict@soe.ucsc.edu', 'United States|United States|United States|United States', 40, 'Algorithms|Computational Biology|Databases, Protein|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btn630', '19056777', 'Multiple sequence alignment is a cornerstone of comparative genomics. Much work has been done to improve methods for this task, particularly for the alignment of small sequences, and especially for amino acid sequences. However, less work has been done in making promising methods that work on the small-scale practically for the alignment of much larger genomic sequences.'),
(74509, 2009, 'bio', 'Identification of microRNA regulatory modules in Arabidopsis via a probabilistic graphical model', 'Joung, Je-Gun|Fei, Zhangjun', 'Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY 14853, USA.|Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY 14853, USA.', 'United States|United States', 0, 'Arabidopsis|Computer Simulation|Databases, Genetic|Gene Expression Profiling|Gene Regulatory Networks|MicroRNAs|Models, Statistical|Promoter Regions, Genetic', 'Journal Article', '10.1093/bioinformatics/btn626', '19056778', 'MicroRNAs miRNAs play important roles in gene regulation and are regarded as key components in gene regulatory pathways. Systematically understanding functional roles of miRNAs is essential to define core transcriptional units regulating key biological processes. Here, we propose a method based on the probabilistic graphical model to identify the regulatory modules of miRNAs and the core regulatory motifs involved in their ability to regulate gene expression.'),
(74510, 2009, 'bio', 'Structural profiles of human miRNA families from pairwise clustering', 'Kaczkowski, Bogumixc5x82|Torarinsson, Elfar|Reiche, Kristin|Havgaard, Jakob Hull|Stadler, Peter F|Gorodkin, Jan', 'Division of Genetics and Bioinformatics, IBHV, University of Copenhagen, Frederiksberg C, Denmark.|Division of Genetics and Bioinformatics, IBHV, University of Copenhagen, Frederiksberg C, Denmark.|Division of Genetics and Bioinformatics, IBHV, University of Copenhagen, Frederiksberg C, Denmark.|Division of Genetics and Bioinformatics, IBHV, University of Copenhagen, Frederiksberg C, Denmark.|Division of Genetics and Bioinformatics, IBHV, University of Copenhagen, Frederiksberg C, Denmark.|Division of Genetics and Bioinformatics, IBHV, University of Copenhagen, Frederiksberg C, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 42, 'Base Sequence|Cluster Analysis|Computational Biology|Databases, Genetic|Genome, Human|Humans|MicroRNAs|Molecular Sequence Data|Nucleic Acid Conformation|Software', 'Journal Article', '10.1093/bioinformatics/btn628', '19059941', 'MicroRNAs (miRNAs) are a group of small, approximately 21 nt long, riboregulators inhibiting gene expression at a post-transcriptional level. Their most distinctive structural feature is the foldback hairpin of their precursor pre-miRNAs. Even though each pre-miRNA deposited in miRBase has its secondary structure already predicted, little is known about the patterns of structural conservation among pre-miRNAs. We address this issue by clustering the human pre-miRNA sequences based on pairwise, sequence and secondary structure alignment using FOLDALIGN, followed by global multiple alignment of obtained clusters by WAR. As a result, the common secondary structure was successfully determined for four FOLDALIGN clusters: the RF00027 structural family of the Rfam database and three clusters with previously undescribed consensus structures.'),
(74511, 2009, 'bio', 'Detecting glycan cancer biomarkers in serum samples using MALDI FT-ICR mass spectrometry data', 'Barkauskas, Donald A|An, Hyun Joo|Kronewitter, Scott R|de Leoz, Maria Lorna|Chew, Helen K|de Vere White, Ralph W|Leiserowitz, Gary S|Miyamoto, Suzanne|Lebrilla, Carlito B|Rocke, David M', 'Graduate Group in Biostatistics with a Designated Emphasis in Biotechnology, School of Medicine, University of California, Davis, CA 95616, USA. barkda@wald.ucdavis.edu|Graduate Group in Biostatistics with a Designated Emphasis in Biotechnology, School of Medicine, University of California, Davis, CA 95616, USA. barkda@wald.ucdavis.edu|Graduate Group in Biostatistics with a Designated Emphasis in Biotechnology, School of Medicine, University of California, Davis, CA 95616, USA. barkda@wald.ucdavis.edu|Graduate Group in Biostatistics with a Designated Emphasis in Biotechnology, School of Medicine, University of California, Davis, CA 95616, USA. barkda@wald.ucdavis.edu|Graduate Group in Biostatistics with a Designated Emphasis in Biotechnology, School of Medicine, University of California, Davis, CA 95616, USA. barkda@wald.ucdavis.edu|Graduate Group in Biostatistics with a Designated Emphasis in Biotechnology, School of Medicine, University of California, Davis, CA 95616, USA. barkda@wald.ucdavis.edu|Graduate Group in Biostatistics with a Designated Emphasis in Biotechnology, School of Medicine, University of California, Davis, CA 95616, USA. barkda@wald.ucdavis.edu|Graduate Group in Biostatistics with a Designated Emphasis in Biotechnology, School of Medicine, University of California, Davis, CA 95616, USA. barkda@wald.ucdavis.edu|Graduate Group in Biostatistics with a Designated Emphasis in Biotechnology, School of Medicine, University of California, Davis, CA 95616, USA. barkda@wald.ucdavis.edu|Graduate Group in Biostatistics with a Designated Emphasis in Biotechnology, School of Medicine, University of California, Davis, CA 95616, USA. barkda@wald.ucdavis.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 32, 'Algorithms|Biomarkers, Tumor|Cyclotrons|Fourier Analysis|Humans|Neoplasms|Polysaccharides|Software|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Journal Article', '10.1093/bioinformatics/btn610', '19073586', 'The development of better tests to detect cancer in its earliest stages is one of the most sought-after goals in medicine. Especially important are minimally invasive tests that require only blood or urine samples. By profiling oligosaccharides cleaved from glycosylated proteins shed by tumor cells into the blood stream, we hope to determine glycan profiles that will help identify cancer patients using a simple blood test. The data in this article were generated using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI FT-ICR MS). We have developed novel methods for analyzing this type of mass spectrometry data and applied it to eight datasets from three different types of cancer (breast, ovarian and prostate).'),
(74512, 2009, 'bio', 'Glycan family analysis for deducing N-glycan topology from single MS', 'Goldberg, David|Bern, Marshall|North, Simon J|Haslam, Stuart M|Dell, Anne', 'Palo Alto Research Center, 3333 Coyote Hill Rd, Palo Alto CA 94304, USA. goldberg@parc.com|Palo Alto Research Center, 3333 Coyote Hill Rd, Palo Alto CA 94304, USA. goldberg@parc.com|Palo Alto Research Center, 3333 Coyote Hill Rd, Palo Alto CA 94304, USA. goldberg@parc.com|Palo Alto Research Center, 3333 Coyote Hill Rd, Palo Alto CA 94304, USA. goldberg@parc.com|Palo Alto Research Center, 3333 Coyote Hill Rd, Palo Alto CA 94304, USA. goldberg@parc.com', 'United States|United States|United States|United States|United States', 24, 'Algorithms|Animals|Computational Biology|Humans|Mass Spectrometry|Models, Biological|Polysaccharides|Proteomics', 'Journal Article', '10.1093/bioinformatics/btn636', '19073587', 'In the past few years, mass spectrometry (MS) has emerged as the premier tool for identification and quantification of biological molecules such as peptides and glycans. There are two basic strategies: single-MS, which uses a single round of mass analysis, and MS/MS (or higher order MS(n)), which adds one or more additional rounds of mass analysis, interspersed with fragmentation steps. Single-MS offers higher throughput, broader mass coverage and more direct quantitation, but generally much weaker identification. Single-MS, however, does work fairly well for the case of N-glycan identification, which are more constrained than other biological polymers. We previously demonstrated single-MS identification of N-glycans to the level of cartoons (monosaccharide composition and topology) by a system that incorporates an experts detailed knowledge of the biological sample. In this article, we explore the possibility of ab initio single-MS N-glycan identification, with the goal of extending single-MS, or primarily-single-MS, identification to non-expert users, novel conditions and unstudied tissues.'),
(74513, 2009, 'bio', 'Matrix correlations for high-dimensional data: the modified RV-coefficient', 'Smilde, A K|Kiers, H A L|Bijlsma, S|Rubingh, C M|van Erk, M J', 'Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands. a.k.smilde@uva.nl|Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands. a.k.smilde@uva.nl|Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands. a.k.smilde@uva.nl|Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands. a.k.smilde@uva.nl|Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands. a.k.smilde@uva.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 110, 'Algorithms|Computer Simulation|Genomics|Metabolomics', 'Journal Article', '10.1093/bioinformatics/btn634', '19073588', 'Modern functional genomics generates high-dimensional datasets. It is often convenient to have a single simple number characterizing the relationship between pairs of such high-dimensional datasets in a comprehensive way. Matrix correlations are such numbers and are appealing since they can be interpreted in the same way as Pearsons correlations familiar to biologists. The high-dimensionality of functional genomics data is, however, problematic for existing matrix correlations. The motivation of this article is 2-fold: (i) we introduce the idea of matrix correlations to the bioinformatics community and (ii) we give an improvement of the most promising matrix correlation coefficient (the RV-coefficient) circumventing the problems of high-dimensional data.'),
(74514, 2009, 'bio', 'SIMoNe: Statistical Inference for MOdular NEtworks', 'Chiquet, Julien|Smith, Alexander|Grasseau, Gilles|Matias, Catherine|Ambroise, Christophe', 'UMR CNRS 8071 Statistique et Génome, 523, place des Terrasses, F-91000 Evry, France. julien.chiquet@genopole.cnrs.fr|UMR CNRS 8071 Statistique et Génome, 523, place des Terrasses, F-91000 Evry, France. julien.chiquet@genopole.cnrs.fr|UMR CNRS 8071 Statistique et Génome, 523, place des Terrasses, F-91000 Evry, France. julien.chiquet@genopole.cnrs.fr|UMR CNRS 8071 Statistique et Génome, 523, place des Terrasses, F-91000 Evry, France. julien.chiquet@genopole.cnrs.fr|UMR CNRS 8071 Statistique et Génome, 523, place des Terrasses, F-91000 Evry, France. julien.chiquet@genopole.cnrs.fr', 'France|France|France|France|France', 23, 'Algorithms|Computer Simulation|Databases, Genetic|Gene Expression Profiling|Gene Regulatory Networks|Software', 'Journal Article', '10.1093/bioinformatics/btn637', '19073589', 'The R package SIMoNe (Statistical Inference for MOdular NEtworks) enables inference of gene-regulatory networks based on partial correlation coefficients from microarray experiments. Modelling gene expression data with a Gaussian graphical model (hereafter GGM), the algorithm estimates non-zero entries of the concentration matrix, in a sparse and possibly high-dimensional setting. Its originality lies in the fact that it searches for a latent modular structure to drive the inference procedure through adaptive penalization of the concentration matrix.'),
(74515, 2009, 'bio', 'PASTAA: identifying transcription factors associated with sets of co-regulated genes', 'Roider, Helge G|Manke, Thomas|OKeeffe, Sean|Vingron, Martin|Haas, Stefan A', 'Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin. roider@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin. roider@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin. roider@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin. roider@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin. roider@molgen.mpg.de', '-|-|-|-|-', 92, 'Binding Sites|Chromatin Immunoprecipitation|Databases, Genetic|Expressed Sequence Tags|Gene Expression Profiling|Gene Expression Regulation|Promoter Regions, Genetic|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btn627', '19073590', 'A major challenge in regulatory genomics is the identification of associations between functional categories of genes (e.g. tissues, metabolic pathways) and their regulating transcription factors (TFs). While, for a limited number of categories, the regulating TFs are already known, still for many functional categories the responsible factors remain to be elucidated.'),
(74516, 2009, 'bio', 'ARCS-Motif: discovering correlated motifs from unaligned biological sequences', 'Zhang, Shijie|Su, Wei|Yang, Jiong', 'Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA.|Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA.|Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA.', 'United States|United States|United States', 5, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Conserved Sequence|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btn609', '19073591', 'The goal of motif discovery is to detect novel, unknown, and important signals from biology sequences. In most models, the importance of a motif is equal to the sum of the similarity of every single position. In 2006, Song et al. introduced Aggregated Related Column Score (ARCS) measure which includes correlation information to the evaluation of motif importance. The paper showed that the ARCS measure is superior to other measures. Due to the complicated nature of the ARCS motif model, we cannot directly apply existing sequential motif discovery methods to find motifs with high ARCS values.'),
(74517, 2009, 'bio', 'Better bioinformatics through usability analysis', 'Bolchini, Davide|Finkelstein, Anthony|Perrone, Vito|Nagl, Sylvia', 'Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK. dbolchin@iupui.edu|Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK. dbolchin@iupui.edu|Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK. dbolchin@iupui.edu|Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK. dbolchin@iupui.edu', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 48, 'Computational Biology|Databases, Genetic|Information Storage and Retrieval|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn633', '19073592', 'Improving the usability of bioinformatics resources enables researchers to find, interact with, share, compare and manipulate important information more effectively and efficiently. It thus enables researchers to gain improved insights into biological processes with the potential, ultimately, of yielding new scientific results. Usability barriers can pose significant obstacles to a satisfactory user experience and force researchers to spend unnecessary time and effort to complete their tasks. The number of online biological databases available is growing and there is an expanding community of diverse users. In this context there is an increasing need to ensure the highest standards of usability.'),
(74518, 2009, 'bio', 'Evaluating contributions of natural language parsers to protein-protein interaction extraction', 'Miyao, Yusuke|Sagae, Kenji|Saetre, Rune|Matsuzaki, Takuya|Tsujii, Junichi', 'Department of Computer Science, University of Tokyo, Tokyo, Japan. yusuke@is.s.u-tokyo.ac.jp|Department of Computer Science, University of Tokyo, Tokyo, Japan. yusuke@is.s.u-tokyo.ac.jp|Department of Computer Science, University of Tokyo, Tokyo, Japan. yusuke@is.s.u-tokyo.ac.jp|Department of Computer Science, University of Tokyo, Tokyo, Japan. yusuke@is.s.u-tokyo.ac.jp|Department of Computer Science, University of Tokyo, Tokyo, Japan. yusuke@is.s.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan|Japan', 104, 'Algorithms|Databases, Protein|Natural Language Processing|Protein Interaction Mapping|Proteins', 'Evaluation Studies', '10.1093/bioinformatics/btn631', '19073593', 'While text mining technologies for biomedical research have gained popularity as a way to take advantage of the explosive growth of information in text form in biomedical papers, selecting appropriate natural language processing (NLP) tools is still difficult for researchers who are not familiar with recent advances in NLP. This article provides a comparative evaluation of several state-of-the-art natural language parsers, focusing on the task of extracting protein-protein interaction (PPI) from biomedical papers. We measure how each parser, and its output representation, contributes to accuracy improvement when the parser is used as a component in a PPI system.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(74519, 2009, 'bio', 'Simulation of crosstalk between small GTPase RhoA and EGFR-ERK signaling pathway via MEKK1', 'Li, Hu|Ung, Choong Yong|Ma, Xiao Hua|Li, Bao Wen|Low, Boon Chuan|Cao, Zhi Wei|Chen, Yu Zong', 'Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543.|Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543.|Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543.|Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543.|Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543.|Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543.|Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 25, 'Animals|Computer Simulation|ErbB Receptors|Extracellular Signal-Regulated MAP Kinases|Humans|MAP Kinase Kinase Kinase 1|Models, Theoretical|Monomeric GTP-Binding Proteins|Reproducibility of Results|Signal Transduction|rhoA GTP-Binding Protein', 'Journal Article', '10.1093/bioinformatics/btn635', '19074159', 'Small GTPase RhoA regulates cell-cycle progression via several mechanisms. Apart from its actions via ROCK, RhoA has recently been found to activate a scaffold protein MEKK1 known to promote ERK activation. We examined whether RhoA can substantially affect ERK activity via this MEKK1-mediated crosstalk between RhoA and EGFR-ERK pathway. By extending the published EGFR-ERK simulation models represented by ordinary differential equations, we developed a simulation model that includes this crosstalk, which was validated with a number of experimental findings and published simulation results.'),
(74520, 2009, 'bio', 'NOEnet--use of NOE networks for NMR resonance assignment of proteins with known 3D structure', 'Stratmann, Dirk|van Heijenoort, Carine|Guittet, Eric', 'Laboratoire de Chimie et Biologie Structurales, ICSN-CNRS, Gif-sur-Yvette, France.|Laboratoire de Chimie et Biologie Structurales, ICSN-CNRS, Gif-sur-Yvette, France.|Laboratoire de Chimie et Biologie Structurales, ICSN-CNRS, Gif-sur-Yvette, France.', 'France|France|France', 15, 'Algorithms|Databases, Protein|Models, Molecular|Nuclear Magnetic Resonance, Biomolecular|Protein Conformation|Proteins', 'Journal Article', '10.1093/bioinformatics/btn638', '19074506', 'A prerequisite for any protein study by NMR is the assignment of the resonances from the (15)N-(1)H HSQC spectrum to their corresponding atoms of the protein backbone. Usually, this assignment is obtained by analyzing triple resonance NMR experiments. An alternative assignment strategy exploits the information given by an already available 3D structure of the same or a homologous protein. Up to now, the algorithms that have been developed around the structure-based assignment strategy have the important drawbacks that they cannot guarantee a high assignment accuracy near to 100%.'),
(74521, 2009, 'bio', 'ISMB 2008 conference report', 'Sansom, Clare', 'Laboratoire de Chimie et Biologie Structurales, ICSN-CNRS, Gif-sur-Yvette, France.', 'France', 0, 'Algorithms|Animals|Awards and Prizes|Computational Biology|Disease|Escherichia coli|Humans|Mammals|Saccharomyces cerevisiae|Sequence Analysis, DNA|Societies, Scientific', 'Congress', '10.1093/bioinformatics/btn619', '19074507', '-'),
(74522, 2009, 'bio', 'rHVDM: an R package to predict the activity and targets of a transcription factor', 'Barenco, M|Papouli, E|Shah, S|Brewer, D|Miller, C J|Hubank, M', 'Institute of Child Health, University College London, 30 Guilford street, London WC1N 1EH, UK. m.barenco@ucl.ac.uk|Institute of Child Health, University College London, 30 Guilford street, London WC1N 1EH, UK. m.barenco@ucl.ac.uk|Institute of Child Health, University College London, 30 Guilford street, London WC1N 1EH, UK. m.barenco@ucl.ac.uk|Institute of Child Health, University College London, 30 Guilford street, London WC1N 1EH, UK. m.barenco@ucl.ac.uk|Institute of Child Health, University College London, 30 Guilford street, London WC1N 1EH, UK. m.barenco@ucl.ac.uk|Institute of Child Health, University College London, 30 Guilford street, London WC1N 1EH, UK. m.barenco@ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 4, 'Algorithms|Gene Expression Profiling|Internet|Software|Transcription Factors|Tumor Suppressor Protein p53', 'Journal Article', '10.1093/bioinformatics/btn639', '19074958', 'Highly parallel genomic platforms like microarrays often present researchers with long lists of differentially expressed genes but contain little or no information on how these genes are regulated. rHVDM is a novel R package which uses gene expression time course data to predict the activity and targets of a transcription factor. In the first step, rHVDM uses a small number of known targets to derive the activity profile of a given transcription factor. Then, in a subsequent step, this activity profile is used to predict other putative targets of that transcription factor. A dynamic and mechanistic model of gene expression is at the heart of the technique. Measurement error is taken into account during the process, which allows an objective assessment of the robustness of fit and, therefore, the quality of the predictions. The package relies on efficient algorithms and vectorization to accomplish potentially time consuming tasks including optimization and differential equation integration. We demonstrate the efficiency and accuracy of rHVDM by examining the activity of the tumour-suppressing transcription factor, p53.'),
(74523, 2009, 'bio', 'ATOM: a powerful gene-based association test by combining optimally weighted markers', 'Li, Mingyao|Wang, Kai|Grant, Struan F A|Hakonarson, Hakon|Li, Chun', 'Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, The Childrens Hospital of Philadelphia, Philadelphia, PA 19104, USA. mingyao@mail.med.upenn.edu|Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, The Childrens Hospital of Philadelphia, Philadelphia, PA 19104, USA. mingyao@mail.med.upenn.edu|Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, The Childrens Hospital of Philadelphia, Philadelphia, PA 19104, USA. mingyao@mail.med.upenn.edu|Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, The Childrens Hospital of Philadelphia, Philadelphia, PA 19104, USA. mingyao@mail.med.upenn.edu|Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, The Childrens Hospital of Philadelphia, Philadelphia, PA 19104, USA. mingyao@mail.med.upenn.edu', 'United States|United States|United States|United States|United States', 40, 'Genetic Markers|Genetic Predisposition to Disease|Genome-Wide Association Study|Genotype|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Quantitative Trait Loci', 'Journal Article', '10.1093/bioinformatics/btn641', '19074959', 'Large-scale candidate-gene and genome-wide association studies genotype multiple SNPs within or surrounding a gene, including both tag and functional SNPs. The immense amount of data generated in these studies poses new challenges to analysis. One particularly challenging yet important question is how to best use all genetic information to test whether a gene or a region is associated with the trait of interest.'),
(74524, 2009, 'bio', 'Predicting the binding preference of transcription factors to individual DNA k-mers', 'Alleyne, Trevis M|Peña-Castillo, Lourdes|Badis, Gwenael|Talukder, Shaheynoor|Berger, Michael F|Gehrke, Andrew R|Philippakis, Anthony A|Bulyk, Martha L|Morris, Quaid D|Hughes, Timothy R', 'Department of Molecular Genetics, Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada.|Department of Molecular Genetics, Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada.|Department of Molecular Genetics, Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada.|Department of Molecular Genetics, Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada.|Department of Molecular Genetics, Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada.|Department of Molecular Genetics, Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada.|Department of Molecular Genetics, Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada.|Department of Molecular Genetics, Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada.|Department of Molecular Genetics, Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada.|Department of Molecular Genetics, Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 19, 'Binding Sites|Computational Biology|DNA|Sequence Analysis, DNA|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/btn645', '19088121', 'Recognition of specific DNA sequences is a central mechanism by which transcription factors (TFs) control gene expression. Many TF-binding preferences, however, are unknown or poorly characterized, in part due to the difficulty associated with determining their specificity experimentally, and an incomplete understanding of the mechanisms governing sequence specificity. New techniques that estimate the affinity of TFs to all possible k-mers provide a new opportunity to study DNA-protein interaction mechanisms, and may facilitate inference of binding preferences for members of a given TF family when such information is available for other family members.'),
(74525, 2009, 'bio', 'A genetic programming-based approach to the classification of multiclass microarray datasets', 'Liu, Kun-Hong|Xu, Chun-Gui', 'School of Software, Xiamen University, Xiamen, Fujian, 361005, China. lkhqz@163.com|School of Software, Xiamen University, Xiamen, Fujian, 361005, China. lkhqz@163.com', 'China|China', 0, 'Algorithms|Classification|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sample Size', 'Journal Article', '10.1093/bioinformatics/btn644', '19088122', 'Feature selection approaches have been widely applied to deal with the small sample size problem in the analysis of micro-array datasets. For the multiclass problem, the proposed methods are based on the idea of selecting a gene subset to distinguish all classes. However, it will be more effective to solve a multiclass problem by splitting it into a set of two-class problems and solving each problem with a respective classification system.'),
(74526, 2009, 'bio', 'FastMap: fast eQTL mapping in homozygous populations', 'Gatti, Daniel M|Shabalin, Andrey A|Lam, Tieu-Chong|Wright, Fred A|Rusyn, Ivan|Nobel, Andrew B', 'Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina 27599, USA.|Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina 27599, USA.|Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina 27599, USA.|Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina 27599, USA.|Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina 27599, USA.|Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina 27599, USA.', 'United States|United States|United States|United States|United States|United States', 31, 'Algorithms|Animals|Gene Expression Profiling|Genome|Genotype|Homozygote|Mice|Quantitative Trait Loci|Software', 'Journal Article', '10.1093/bioinformatics/btn648', '19091771', 'Gene expression Quantitative Trait Locus (eQTL) mapping measures the association between transcript expression and genotype in order to find genomic locations likely to regulate transcript expression. The availability of both gene expression and high-density genotype data has improved our ability to perform eQTL mapping in inbred mouse and other homozygous populations. However, existing eQTL mapping software does not scale well when the number of transcripts and markers are on the order of 10(5) and 10(5)-10(6), respectively.'),
(74527, 2009, 'bio', 'Computational analysis of microRNA profiles and their target genes suggests significant involvement in breast cancer antiestrogen resistance', 'Xin, Fuxiao|Li, Meng|Balch, Curt|Thomson, Michael|Fan, Meiyun|Liu, Yunlong|Hammond, Scott M|Kim, Sun|Nephew, Kenneth P', 'School of Informatics, Indiana University, Bloomington, IN 47405, USA.|School of Informatics, Indiana University, Bloomington, IN 47405, USA.|School of Informatics, Indiana University, Bloomington, IN 47405, USA.|School of Informatics, Indiana University, Bloomington, IN 47405, USA.|School of Informatics, Indiana University, Bloomington, IN 47405, USA.|School of Informatics, Indiana University, Bloomington, IN 47405, USA.|School of Informatics, Indiana University, Bloomington, IN 47405, USA.|School of Informatics, Indiana University, Bloomington, IN 47405, USA.|School of Informatics, Indiana University, Bloomington, IN 47405, USA.', 'India|India|India|India|India|India|India|India|India', 0, 'Breast Neoplasms|Cell Line, Tumor|Computational Biology|Drug Resistance, Neoplasm|Estrogen Receptor Modulators|Female|Gene Expression Regulation, Neoplastic|Humans|MicroRNAs', 'Journal Article', '10.1093/bioinformatics/btn646', '19091772', 'Recent evidence shows significant involvement of microRNAs (miRNAs) in the initiation and progression of numerous cancers, however, the role of these in tumor drug resistance remains unknown.'),
(74528, 2009, 'bio', 'Precision and recall estimates for two-hybrid screens', 'Huang, Hailiang|Bader, Joel S', 'Department of Biomedical Engineering and High-Throughput Biology Center, Johns Hopkins University, Baltimore, MD, USA.|Department of Biomedical Engineering and High-Throughput Biology Center, Johns Hopkins University, Baltimore, MD, USA.', 'United States|United States', 48, 'Algorithms|Computer Simulation|Databases, Genetic|Models, Biological|Proteins|Two-Hybrid System Techniques', 'Journal Article', '10.1093/bioinformatics/btn640', '19091773', 'Yeast two-hybrid screens are an important method to map pairwise protein interactions. This method can generate spurious interactions (false discoveries), and true interactions can be missed (false negatives). Previously, we reported a capture-recapture estimator for bait-specific precision and recall. Here, we present an improved method that better accounts for heterogeneity in bait-specific error rates.'),
(74529, 2009, 'bio', 'Probabilistic assignment of formulas to mass peaks in metabolomics experiments', 'Rogers, Simon|Scheltema, Richard A|Girolami, Mark|Breitling, Rainer', 'Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, UK. srogers@dcs.gla.ac.uk|Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, UK. srogers@dcs.gla.ac.uk|Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, UK. srogers@dcs.gla.ac.uk|Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, UK. srogers@dcs.gla.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 67, 'Computer Simulation|Mass Spectrometry|Metabolomics|Proteome', 'Journal Article', '10.1093/bioinformatics/btn642', '19095699', 'High-accuracy mass spectrometry is a popular technology for high-throughput measurements of cellular metabolites (metabolomics). One of the major challenges is the correct identification of the observed mass peaks, including the assignment of their empirical formula, based on the measured mass.'),
(74530, 2009, 'bio', 'Prediction of RNA secondary structure using generalized centroid estimators', 'Hamada, Michiaki|Kiryu, Hisanori|Sato, Kengo|Mituyama, Toutai|Asai, Kiyoshi', 'Mizuho Information & Research Institute, Inc, 2-3 Kanda-Nishikicho, Chiyoda-ku, Tokyo 101-8443, Japan. hamada-michiaki@aist.go.jp|Mizuho Information & Research Institute, Inc, 2-3 Kanda-Nishikicho, Chiyoda-ku, Tokyo 101-8443, Japan. hamada-michiaki@aist.go.jp|Mizuho Information & Research Institute, Inc, 2-3 Kanda-Nishikicho, Chiyoda-ku, Tokyo 101-8443, Japan. hamada-michiaki@aist.go.jp|Mizuho Information & Research Institute, Inc, 2-3 Kanda-Nishikicho, Chiyoda-ku, Tokyo 101-8443, Japan. hamada-michiaki@aist.go.jp|Mizuho Information & Research Institute, Inc, 2-3 Kanda-Nishikicho, Chiyoda-ku, Tokyo 101-8443, Japan. hamada-michiaki@aist.go.jp', 'Japan|Japan|Japan|Japan|Japan', 0, 'Base Pairing|Base Sequence|Computational Biology|Databases, Genetic|Entropy|Molecular Sequence Data|Nucleic Acid Conformation|RNA|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btn601', '19095700', 'Recent studies have shown that the methods for predicting secondary structures of RNAs on the basis of posterior decoding of the base-pairing probabilities has an advantage with respect to prediction accuracy over the conventionally utilized minimum free energy methods. However, there is room for improvement in the objective functions presented in previous studies, which are maximized in the posterior decoding with respect to the accuracy measures for secondary structures.'),
(74531, 2009, 'bio', 'All hits all the time: parameter-free calculation of spaced seed sensitivity', 'Mak, Denise Y F|Benson, Gary', 'Graduate Program in Bioinformatics, Boston University, Boston, MA 02215, USA. dyfmak@bu.edu|Graduate Program in Bioinformatics, Boston University, Boston, MA 02215, USA. dyfmak@bu.edu', 'United States|United States', 7, 'Algorithms|DNA|DNA Repeat Expansion|Probability|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btn643', '19095701', 'Standard search techniques for DNA repeats start by identifying small matching words, or seeds, that may inhabit larger repeats. Recent innovations in seed structure include spaced seeds and indel seeds which are more sensitive than contiguous seeds. Evaluating seed sensitivity requires (i) specifying a homology model for alignments and (ii) assigning probabilities to those alignments. Optimal seed selection is resource intensive because all alternative seeds must be tested. Current methods require that the model and its probability parameters be specified in advance. When the parameters change, the entire calculation has to be rerun.'),
(74532, 2009, 'bio', 'Matching methods for observational microarray studies', 'Heller, Ruth|Manduchi, Elisabetta|Small, Dylan S', 'Department of Statistics, Wharton School, University of Pennsylvania, Philadelphia, PA 19104-6340, USA. ruheller@whatron.upenn.edu|Department of Statistics, Wharton School, University of Pennsylvania, Philadelphia, PA 19104-6340, USA. ruheller@whatron.upenn.edu|Department of Statistics, Wharton School, University of Pennsylvania, Philadelphia, PA 19104-6340, USA. ruheller@whatron.upenn.edu', 'United States|United States|United States', 14, 'Computational Biology|Down Syndrome|Gene Expression Profiling|Humans|Leukemia, Myeloid, Acute|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Journal Article', '10.1093/bioinformatics/btn650', '19098026', 'We address the problem of identifying differentially expressed genes between two conditions in the scenario where the data arise from an observational study, in which confounding factors are likely to be present.'),
(74533, 2009, 'bio', 'SNPnexus: a web database for functional annotation of newly discovered and public domain single nucleotide polymorphisms', 'Chelala, Claude|Khan, Arshad|Lemoine, Nicholas R', 'Centre for Molecular Oncology and Imaging, Institute of Cancer & CR-UK Clinical Centre, Barts & The London School of Medicine (QMUL), Charterhouse Square, London EC1M 6BQ, UK. claude.chelala@cancer.org.uk|Centre for Molecular Oncology and Imaging, Institute of Cancer & CR-UK Clinical Centre, Barts & The London School of Medicine (QMUL), Charterhouse Square, London EC1M 6BQ, UK. claude.chelala@cancer.org.uk|Centre for Molecular Oncology and Imaging, Institute of Cancer & CR-UK Clinical Centre, Barts & The London School of Medicine (QMUL), Charterhouse Square, London EC1M 6BQ, UK. claude.chelala@cancer.org.uk', 'United Kingdom|United Kingdom|United Kingdom', 123, 'Databases, Nucleic Acid|Genotype|Internet|Polymorphism, Single Nucleotide|Regulatory Elements, Transcriptional', 'Journal Article', '10.1093/bioinformatics/btn653', '19098027', 'Design a new computational tool allowing scientists to functionally annotate newly discovered and public domain single nucleotide polymorphisms in order to help in prioritizing targets in further disease studies and large-scale genotyping projects.'),
(74534, 2009, 'bio', 'PuMA: Bayesian analysis of partitioned (and unpartitioned) model adequacy', 'Brown, Jeremy M|ElDabaje, Robert', 'Section of Integrative Biology, Center for Computational Biology and Bioinformatics, University of Texas - Austin, Austin, TX 78712, USA. jembrown@mail.utexas.edu|Section of Integrative Biology, Center for Computational Biology and Bioinformatics, University of Texas - Austin, Austin, TX 78712, USA. jembrown@mail.utexas.edu', 'United States|United States', 21, 'Base Sequence|Bayes Theorem|Evolution, Molecular|Internet|Phylogeny|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btn651', '19098028', 'The accuracy of Bayesian phylogenetic inference using molecular data depends on the use of proper models of sequence evolution. Although choosing the best model available from a pool of alternatives has become standard practice in statistical phylogenetics, assessment of the chosen models adequacy is rare. Programs for Bayesian phylogenetic inference have recently begun to implement models of sequence evolution that account for heterogeneity across sites beyond variation in rates of evolution, yet no program exists to assess the adequacy of these models. PuMA implements a posterior predictive simulation approach to assessing the adequacy of partitioned, unpartitioned and mixture models of DNA sequence evolution in a Bayesian context. Assessment of model adequacy allows empirical phylogeneticists to have appropriate confidence in their results and guides efforts to improve models of sequence evolution.'),
(74535, 2009, 'bio', 'SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies', 'Yang, Can|He, Zengyou|Wan, Xiang|Yang, Qiang|Xue, Hong|Yu, Weichuan', 'Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China. eeyang@ust.hk|Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China. eeyang@ust.hk|Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China. eeyang@ust.hk|Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China. eeyang@ust.hk|Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China. eeyang@ust.hk|Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China. eeyang@ust.hk', 'China|China|China|China|China|China', 125, 'Algorithms|Epistasis, Genetic|Genome|Genome-Wide Association Study|Genomics|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btn652', '19098029', 'Hundreds of thousands of single nucleotide polymorphisms (SNPs) are available for genome-wide association (GWA) studies nowadays. The epistatic interactions of SNPs are believed to be very important in determining individual susceptibility to complex diseases. However, existing methods for SNP interaction discovery either suffer from high computation complexity or perform poorly when marginal effects of disease loci are weak or absent. Hence, it is desirable to develop an effective method to search epistatic interactions in genome-wide scale.'),
(74536, 2009, 'bio', 'SAFEGUI: resampling-based tests of categorical significance in gene expression data made easy', 'Gatti, Daniel M|Sypa, Myroslav|Rusyn, Ivan|Wright, Fred A|Barry, William T', 'Department of Environmental Sciences & Engineering, Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA.|Department of Environmental Sciences & Engineering, Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA.|Department of Environmental Sciences & Engineering, Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA.|Department of Environmental Sciences & Engineering, Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA.|Department of Environmental Sciences & Engineering, Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA.', 'United States|United States|United States|United States|United States', 3, 'Algorithms|Computational Biology|Computer Graphics|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn655', '19098030', 'A large number of websites and applications perform significance testing for gene categories/pathways in microarray data. Many of these packages fail to account for expression correlation between transcripts, with a resultant inflation in Type I error. Array permutation and other resampling-based approaches have been proposed as solutions to this problem. SAFEGUI provides a user-friendly graphical interface for the assessment of categorical significance in microarray studies, while properly accounting for the effects of correlations among genes. SAFEGUI incorporates both permutation and more recently proposed bootstrap algorithms that are demonstrated to be more powerful in detecting differential expression across categories of genes.'),
(74537, 2009, 'bio', 'The analysis of inconsistencies between cytogenetic annotations and sequence mapping by defining the imprecision zones of cytogenetic banding', 'Yen, Kuo-Ho|Ho, Chung-Liang|Lee, Chiang', 'Department of Computer Science and Information Engineering, Institute of Molecular Medicine, National Cheng Kung University, Tainan, Taiwan.|Department of Computer Science and Information Engineering, Institute of Molecular Medicine, National Cheng Kung University, Tainan, Taiwan.|Department of Computer Science and Information Engineering, Institute of Molecular Medicine, National Cheng Kung University, Tainan, Taiwan.', '-|-|-', 1, 'Algorithms|Chromosome Banding|Chromosome Mapping|Computational Biology|Genome, Human|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btn649', '19098301', 'In current databases, there are many genes with inconsistent mapping positions between their cytogenetic annotations and sequence map positions. However, not all inconsistencies are the same. Some of them may be problematic which should be corrected in the future, while others may result from the imprecise nature of chromosomal banding which may be tolerable. It is important to stratify the cytogenetic position information into different confidence groups with the recognition of the impreciseness of cytogenetic banding.'),
(74538, 2009, 'bio', 'AnnotationSketch: a genome annotation drawing library', 'Steinbiss, Sascha|Gremme, Gordon|Schärfer, Christin|Mader, Malte|Kurtz, Stefan', 'Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany. steinbiss@zbh.uni-hamburg.de|Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany. steinbiss@zbh.uni-hamburg.de|Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany. steinbiss@zbh.uni-hamburg.de|Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany. steinbiss@zbh.uni-hamburg.de|Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany. steinbiss@zbh.uni-hamburg.de', 'Germany|Germany|Germany|Germany|Germany', 21, 'Computer Graphics|Databases, Factual|Gene Expression Profiling|Genome|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn657', '19106120', 'To analyse the vast amount of genome annotation data available today, a visual representation of genomic features in a given sequence range is required. We developed a C library which provides layout and drawing capabilities for annotation features. It supports several common input and output formats and can easily be integrated into custom C applications. To exemplify the use of AnnotationSketch in other languages, we provide bindings to the scripting languages Ruby, Python and Lua.'),
(74539, 2009, 'bio', 'arrayQualityMetrics--a bioconductor package for quality assessment of microarray data', 'Kauffmann, Audrey|Gentleman, Robert|Huber, Wolfgang', 'EMBL European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. audrey@ebi.ac.uk|EMBL European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. audrey@ebi.ac.uk|EMBL European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. audrey@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 508, 'Algorithms|Computational Biology|Data Interpretation, Statistical|Internet|Oligonucleotide Array Sequence Analysis|Quality Control|Software', 'Journal Article', '10.1093/bioinformatics/btn647', '19106121', 'The assessment of data quality is a major concern in microarray analysis. arrayQualityMetrics is a Bioconductor package that provides a report with diagnostic plots for one or two colour microarray data. The quality metrics assess reproducibility, identify apparent outlier arrays and compute measures of signal-to-noise ratio. The tool handles most current microarray technologies and is amenable to use in automated analysis pipelines or for automatic report generation, as well as for use by individuals. The diagnosis of quality remains, in principle, a context-dependent judgement, but our tool provides powerful, automated, objective and comprehensive instruments on which to base a decision.'),
(74540, 2009, 'bio', 'Differential dependency network analysis to identify condition-specific topological changes in biological networks', 'Zhang, Bai|Li, Huai|Riggins, Rebecca B|Zhan, Ming|Xuan, Jianhua|Zhang, Zhen|Hoffman, Eric P|Clarke, Robert|Wang, Yue', 'Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.|Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 86, 'Algorithms|Animals|Computational Biology|Gene Expression Profiling|Gene Regulatory Networks|Humans|Mice', 'Journal Article', '10.1093/bioinformatics/btn660', '19112081', 'Significant efforts have been made to acquire data under different conditions and to construct static networks that can explain various gene regulation mechanisms. However, gene regulatory networks are dynamic and condition-specific, under different conditions, networks exhibit different regulation patterns accompanied by different transcriptional network topologies. Thus, an investigation on the topological changes in transcriptional networks can facilitate the understanding of cell development or provide novel insights into the pathophysiology of certain diseases, and help identify the key genetic players that could serve as biomarkers or drug targets.'),
(74541, 2009, 'bio', 'Can sugars be produced from fatty acids? A test case for pathway analysis tools', 'de Figueiredo, Luis F|Schuster, Stefan|Kaleta, Christoph|Fell, David A', 'Department of Bioinformatics, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany. ldpf@minet.uni-jena.de|Department of Bioinformatics, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany. ldpf@minet.uni-jena.de|Department of Bioinformatics, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany. ldpf@minet.uni-jena.de|Department of Bioinformatics, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany. ldpf@minet.uni-jena.de', 'Germany|Germany|Germany|Germany', 34, 'Acetyl Coenzyme A|Amino Acids|Carbohydrates|Citric Acid Cycle|Computational Biology|Fatty Acids|Gluconeogenesis|Glycolysis|Glyoxylates|Humans|Metabolic Networks and Pathways|Models, Biological|Software', 'Corrected and Republished Article', '10.1093/bioinformatics/btn621', '19117076', 'In recent years, several methods have been proposed for determining metabolic pathways in an automated way based on network topology. The aim of this work is to analyse these methods by tackling a concrete example relevant in biochemistry. It concerns the question whether even-chain fatty acids, being the most important constituents of lipids, can be converted into sugars at steady state. It was proved five decades ago that this conversion using the Krebs cycle is impossible unless the enzymes of the glyoxylate shunt (or alternative bypasses) are present in the system. Using this example, we can compare the various methods in pathway analysis.'),
(74542, 2009, 'bio', 'A divide-and-conquer approach to analyze underdetermined biochemical models', 'Kotte, Oliver|Heinemann, Matthias', 'Institute of Molecular Systems Biology, ETH Zurich, Switzerland.|Institute of Molecular Systems Biology, ETH Zurich, Switzerland.', 'Switzerland|Switzerland', 18, 'Algorithms|Computational Biology|Models, Biological|Software', 'Journal Article', '10.1093/bioinformatics/btp004', '19126574', 'To obtain meaningful predictions from dynamic computational models, their uncertain parameter values need to be estimated from experimental data. Due to the usually large number of parameters compared to the available measurement data, these estimation problems are often underdetermined meaning that the solution is a multidimensional space. In this case, the challenge is yet to obtain a sound system understanding despite non-identifiable parameter values, e.g. through identifying those parameters that most sensitively determine the models behavior.'),
(74543, 2009, 'bio', 'The Flannotator--a gene and protein expression annotation tool for Drosophila melanogaster', 'Ryder, E|Spriggs, H|Drummond, E|St Johnston, D|Russell, S', 'Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK. e.ryder@gen.cam.ac.uk|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK. e.ryder@gen.cam.ac.uk|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK. e.ryder@gen.cam.ac.uk|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK. e.ryder@gen.cam.ac.uk|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK. e.ryder@gen.cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 15, 'Animals|Computational Biology|Databases, Genetic|Databases, Protein|Drosophila Proteins|Drosophila melanogaster|Genes, Insect|Internet|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp012', '19126575', 'Understanding developmental processes and building towards integrative systems biology require detailed knowledge of the spatio-temporal expression of genes and proteins. We have developed a software package for collecting, storing and searching the annotation of protein or gene expression patterns in Drosophila melanogaster. Using standard Drosophila anatomy and Gene Ontologies, the system can readily capture expression patterns at any stage of development and in all recognized tissue types as well as details of sub-cellular localization. The web-based system allows multiple groups to work in collaboration and share images and annotation.'),
(74544, 2009, 'bio', 'Host-parasite relations of bacteria and phages can be unveiled by oligostickiness, a measure of relaxed sequence similarity', 'Ahmed, Shamim|Saito, Ayumu|Suzuki, Miho|Nemoto, Naoto|Nishigaki, Koichi', 'Graduate School of Science and Engineering, Saitama University, Saitama 338-8570, Japan.|Graduate School of Science and Engineering, Saitama University, Saitama 338-8570, Japan.|Graduate School of Science and Engineering, Saitama University, Saitama 338-8570, Japan.|Graduate School of Science and Engineering, Saitama University, Saitama 338-8570, Japan.|Graduate School of Science and Engineering, Saitama University, Saitama 338-8570, Japan.', 'Japan|Japan|Japan|Japan|Japan', 2, 'Bacillus subtilis|Bacteria|Bacteriophages|Computational Biology|Escherichia coli|Genome, Bacterial|Genome, Viral|Host-Parasite Interactions|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btp003', '19126576', 'The recent metagenome analysis has been producing a large number of host-unassigned viruses. Although assigning viruses to their hosts is basically important not only for virology but also for prevention of epidemic, it has been a laborious and difficult task to date. The only effective method for this purpose has been to find them in a same microscopic view. Now, we tried a computational approach based on genome sequences of bacteria and phages, introducing a physicochemical parameter, SOSS (set of oligostickiness similarity score) derived from oligostickiness, a measure of binding affinity of oligonucleotides to template DNA.'),
(74545, 2009, 'bio', 'BioCichlid: central dogma-based 3D visualization system of time-course microarray data on a hierarchical biological network', 'Ishiwata, Ryosuke R|Morioka, Masaki S|Ogishima, Soichi|Tanaka, Hiroshi', 'Department of Computational Biology, School of Medical Sciences, Tokyo Medical and Dental University, Yushima 1-5-45, Bunkyo-ku, Tokyo 113-8510, Japan.|Department of Computational Biology, School of Medical Sciences, Tokyo Medical and Dental University, Yushima 1-5-45, Bunkyo-ku, Tokyo 113-8510, Japan.|Department of Computational Biology, School of Medical Sciences, Tokyo Medical and Dental University, Yushima 1-5-45, Bunkyo-ku, Tokyo 113-8510, Japan.|Department of Computational Biology, School of Medical Sciences, Tokyo Medical and Dental University, Yushima 1-5-45, Bunkyo-ku, Tokyo 113-8510, Japan.', 'Japan|Japan|Japan|Japan', 2, 'Computer Graphics|Gene Expression Profiling|Models, Biological|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp008', '19126577', 'BioCichlid is a 3D visualization system of time-course microarray data on molecular networks, aiming at interpretation of gene expression data by transcriptional relationships based on the central dogma with physical and genetic interactions. BioCichlid visualizes both physical (protein) and genetic (regulatory) network layers, and provides animation of time-course gene expression data on the genetic network layer. Transcriptional regulations are represented to bridge the physical network (transcription factors) and genetic network (regulated genes) layers, thus integrating promoter analysis into the pathway mapping. BioCichlid enhances the interpretation of microarray data and allows for revealing the underlying mechanisms causing differential gene expressions.'),
(74546, 2009, 'bio', 'DichroCalc--circular and linear dichroism online', 'Bulheller, Benjamin M|Hirst, Jonathan D', 'School of Chemistry, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.|School of Chemistry, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.', 'United Kingdom|United Kingdom', 82, 'Circular Dichroism|Databases, Protein|Internet|Protein Conformation|Protein Folding|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btp016', '19129206', 'Circular dichroism (CD) is widely used in studies of protein folding. The CD spectrum of a protein can be estimated from its structure alone, using the well-established matrix method. In the last decade, a related spectroscopy, linear dichroism (LD), has been increasingly applied to study the orientation of proteins in solution. However, matrix method calculations of LD spectra have not been presented before. DichroCalc makes both CD and LD calculations available in an easy-to-use fashion.'),
(74547, 2009, 'bio', 'A novel method for large tree visualization', 'Heard, Jeff|Kaufmann, William|Guan, Xiaojun', 'Renaissance Computing Institute, 100 Europa Drive, Chapel Hill, NC 27519, USA. jeff@renci.org|Renaissance Computing Institute, 100 Europa Drive, Chapel Hill, NC 27519, USA. jeff@renci.org|Renaissance Computing Institute, 100 Europa Drive, Chapel Hill, NC 27519, USA. jeff@renci.org', 'United States|United States|United States', 4, 'Classification|Cluster Analysis|Computer Graphics|Databases, Genetic|Gene Expression Profiling|Genomics|Proteomics|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn656', '19129207', 'Many genomic and proteomic analyses generate as a result a tree of genes or proteins. These trees are often large (containing tens of thousands of nodes and edges), and need a visualization tool to fully display all the information contained in the tree. Clustering analysis can be performed on these trees to obtain clusters of proteins, and we need an efficient way to visualize the clustering results. We present a novel tree visualization tool to help with such analyses.'),
(74548, 2009, 'bio', 'PanCGH: a genotype-calling algorithm for pangenome CGH data', 'Bayjanov, Jumamurat R|Wels, Michiel|Starrenburg, Marjo|van Hylckama Vlieg, Johan E T|Siezen, Roland J|Molenaar, Douwe', 'Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands. J.Bayjanov@cmbi.ru.nl|Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands. J.Bayjanov@cmbi.ru.nl|Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands. J.Bayjanov@cmbi.ru.nl|Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands. J.Bayjanov@cmbi.ru.nl|Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands. J.Bayjanov@cmbi.ru.nl|Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands. J.Bayjanov@cmbi.ru.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Cluster Analysis|Comparative Genomic Hybridization|Computational Biology|Databases, Protein|Evolution, Molecular|Genetic Variation|Genome, Bacterial|Genotype', 'Journal Article', '10.1093/bioinformatics/btn632', '19129208', 'Pangenome arrays contain DNA oligomers targeting several sequenced reference genomes from the same species. In microbiology, these can be employed to investigate the often high genetic variability within a species by comparative genome hybridization (CGH). The biological interpretation of pangenome CGH data depends on the ability to compare strains at a functional level, particularly by comparing the presence or absence of orthologous genes. Due to the high genetic variability, available genotype-calling algorithms can not be applied to pangenome CGH data.'),
(74549, 2009, 'bio', 'bioDBnet: the biological database network', 'Mudunuri, Uma|Che, Anney|Yi, Ming|Stephens, Robert M', 'Advanced Biomedical Computing Center, Advanced Technology Program, SAIC-Frederick Inc., NCI-Frederick, Frederick, MD 21702, USA.|Advanced Biomedical Computing Center, Advanced Technology Program, SAIC-Frederick Inc., NCI-Frederick, Frederick, MD 21702, USA.|Advanced Biomedical Computing Center, Advanced Technology Program, SAIC-Frederick Inc., NCI-Frederick, Frederick, MD 21702, USA.|Advanced Biomedical Computing Center, Advanced Technology Program, SAIC-Frederick Inc., NCI-Frederick, Frederick, MD 21702, USA.', 'United States|United States|United States|United States', 160, 'Databases, Genetic|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btn654', '19129209', 'bioDBnet is an online web resource that provides interconnected access to many types of biological databases. It has integrated many of the most commonly used biological databases and in its current state has 153 database identifiers (nodes) covering all aspects of biology including genes, proteins, pathways and other biological concepts. bioDBnet offers various ways to work with these databases including conversions, extensive database reports, custom navigation and has various tools to enhance the quality of the results. Importantly, the access to bioDBnet is updated regularly, providing access to the most recent releases of each individual database.'),
(74550, 2009, 'bio', 'Biodiversity informatics: automated approaches for documenting global biodiversity patterns and processes', 'Guralnick, Robert|Hill, Andrew', 'University of Colorado Museum of Natural History, University of Colorado Boulder, Boulder, CO 80309-0265, USA. robert.guralnick@colorado.edu|University of Colorado Museum of Natural History, University of Colorado Boulder, Boulder, CO 80309-0265, USA. robert.guralnick@colorado.edu', 'United States|United States', 0, 'Biodiversity|Databases, Factual|Documentation|Electronic Data Processing|Evolution, Molecular|Informatics|Phylogeny|Population Dynamics|Species Specificity', 'Journal Article', '10.1093/bioinformatics/btn659', '19129210', 'Data about biodiversity have been scattered in different formats in natural history collections, survey reports and the literature. A central challenge for the biodiversity informatics community is to provide the means to share and rapidly synthesize these data and the knowledge they provide us to build an easily accessible, unified global map of biodiversity. Such a map would provide raw and summary data and information on biodiversity and its change across the world at multiple scales.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(74551, 2009, 'bio', 'SCARF: maximizing next-generation EST assemblies for evolutionary and population genomic analyses', 'Barker, Michael S|Dlugosch, Katrina M|Reddy, A Chaitanya C|Amyotte, Sarah N|Rieseberg, Loren H', 'Botany Department, University of British Columbia, Vancouver, B.C. V6T 1Z4, Canada. msbarker@indiana.edu|Botany Department, University of British Columbia, Vancouver, B.C. V6T 1Z4, Canada. msbarker@indiana.edu|Botany Department, University of British Columbia, Vancouver, B.C. V6T 1Z4, Canada. msbarker@indiana.edu|Botany Department, University of British Columbia, Vancouver, B.C. V6T 1Z4, Canada. msbarker@indiana.edu|Botany Department, University of British Columbia, Vancouver, B.C. V6T 1Z4, Canada. msbarker@indiana.edu', 'Canada|Canada|Canada|Canada|Canada', 12, 'Centaurea|Databases, Genetic|Evolution, Molecular|Expressed Sequence Tags|Gene Expression Profiling|Genome|Genomics|Software', 'Journal Article', '10.1093/bioinformatics/btp011', '19129211', 'Scaffolded and Corrected Assembly of Roche 454 (SCARF) is a next-generation sequence assembly tool for evolutionary genomics that is designed especially for assembling 454 EST sequences against high-quality reference sequences from related species. The program was created to knit together 454 contigs that do not assemble during traditional de novo assembly, using a reference sequence library to orient the 454 sequences.'),
(74552, 2009, 'bio', 'Prequips--an extensible software platform for integration, visualization and analysis of LC-MS/MS proteomics data', 'Gehlenborg, Nils|Yan, Wei|Lee, Inyoul Y|Yoo, Hyuntae|Nieselt, Kay|Hwang, Daehee|Aebersold, Ruedi|Hood, Leroy', 'Institute for Systems Biology, Seattle, USA.|Institute for Systems Biology, Seattle, USA.|Institute for Systems Biology, Seattle, USA.|Institute for Systems Biology, Seattle, USA.|Institute for Systems Biology, Seattle, USA.|Institute for Systems Biology, Seattle, USA.|Institute for Systems Biology, Seattle, USA.|Institute for Systems Biology, Seattle, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 10, 'Chromatography, Liquid|Computational Biology|Computer Graphics|Databases, Protein|Internet|Proteins|Proteome|Proteomics|Software|Systems Biology|Tandem Mass Spectrometry|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp005', '19129212', 'We describe an integrative software platform, Prequips, for comparative proteomics-based systems biology analysis that: (i) integrates all information generated from mass spectrometry (MS)-based proteomics as well as from basic proteomics data analysis tools, (ii) visualizes such information for various proteomic analyses via graphical interfaces and (iii) links peptide and protein abundances to external tools often used in systems biology studies.'),
(74553, 2009, 'bio', 'Human microRNAs co-silence in well-separated groups and have different predicted essentialities', 'Boross, Gábor|Orosz, Katalin|Farkas, Illés J', 'Department of Biological Physics, Eötvös Loránd University and Statistical and Biological Physics Research Group and CellCom RET at the Hungarian Academy of Sciences, Budapest, Hungary.|Department of Biological Physics, Eötvös Loránd University and Statistical and Biological Physics Research Group and CellCom RET at the Hungarian Academy of Sciences, Budapest, Hungary.|Department of Biological Physics, Eötvös Loránd University and Statistical and Biological Physics Research Group and CellCom RET at the Hungarian Academy of Sciences, Budapest, Hungary.', 'Hungary|Hungary|Hungary', 30, 'Animals|Caenorhabditis elegans|Computational Biology|Humans|Mice|MicroRNAs|RNA Interference|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btp018', '19131366', 'Short regulating RNAs guide many cellular processes. Compared with transcription factor proteins they appear to provide more specialized control and their deletions are less frequently lethal.'),
(74554, 2009, 'bio', 'Non-negative matrix factorization of gene expression profiles: a plug-in for BRB-ArrayTools', 'Qi, Qihao|Zhao, Yingdong|Li, MingChung|Simon, Richard', 'Department of Biochemistry and Molecular Biology, Georgetown University School of Medicine, 3900 Reservoir Rd. NW, Washington, DC 20057-1455, USA.|Department of Biochemistry and Molecular Biology, Georgetown University School of Medicine, 3900 Reservoir Rd. NW, Washington, DC 20057-1455, USA.|Department of Biochemistry and Molecular Biology, Georgetown University School of Medicine, 3900 Reservoir Rd. NW, Washington, DC 20057-1455, USA.|Department of Biochemistry and Molecular Biology, Georgetown University School of Medicine, 3900 Reservoir Rd. NW, Washington, DC 20057-1455, USA.', 'United States|United States|United States|United States', 28, 'Algorithms|Cluster Analysis|Computer Graphics|Databases, Genetic|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btp009', '19131367', 'Non-negative matrix factorization (NMF) is an increasingly used algorithm for the analysis of complex high-dimensional data. BRB-ArrayTools is a widely used software system for the analysis of gene expression data with almost 9000 registered users in over 65 countries. We have developed a NMF analysis plug-in in BRB-ArrayTools for unsupervised sample clustering of microarray gene expression data. Our analysis tool also incorporates an algorithm for Semi-NMF which can handle both positive and negative elements for log-ratio data. Output includes a heat map of sample clusters and differentially expressed genes with extensive biological annotation. For comparison, output also includes the results of K-means clustering.'),
(74555, 2009, 'bio', 'Profiling model T-cell metagenomes with short reads', 'Warren, René L|Nelson, Brad H|Holt, Robert A', 'BC Cancer Agency, Michael Smith Genome Sciences Centre, 675 West 10th Avenue, Vancouver, BC V5Z 1L3, Canada. rwarren@bcgsc.ca|BC Cancer Agency, Michael Smith Genome Sciences Centre, 675 West 10th Avenue, Vancouver, BC V5Z 1L3, Canada. rwarren@bcgsc.ca|BC Cancer Agency, Michael Smith Genome Sciences Centre, 675 West 10th Avenue, Vancouver, BC V5Z 1L3, Canada. rwarren@bcgsc.ca', 'Canada|Canada|Canada', 33, 'Databases, Genetic|Gene Rearrangement, T-Lymphocyte|Genome|Receptors, Antigen, T-Cell|Sequence Analysis, DNA|Software|T-Lymphocytes', 'Journal Article', '10.1093/bioinformatics/btp010', '19136549', 'T-cell receptor (TCR) diversity in peripheral blood has not yet been fully profiled with sequence level resolution. Each T-cell clonotype expresses a unique receptor, generated by somatic recombination of TCR genes and the enormous potential for T-cell diversity makes repertoire analysis challenging. We developed a sequencing approach and assembly software (immuno-SSAKE or iSSAKE) for profiling T-cell metagenomes using short reads from the massively parallel sequencing platforms.'),
(74556, 2009, 'bio', 'Correcting for ascertainment bias in the inference of population structure', 'Guillot, Gilles|Foll, Matthieu', 'Centre for Ecological and Evolutionary Synthesis, Department of Biology, University of Oslo, P.O. Box 1066, Blindern 0316, Oslo, Norway. gilles.guillot@bio.uio.no|Centre for Ecological and Evolutionary Synthesis, Department of Biology, University of Oslo, P.O. Box 1066, Blindern 0316, Oslo, Norway. gilles.guillot@bio.uio.no', 'Norway|Norway', 21, 'Algorithms|Alleles|Computer Simulation|Gene Frequency|Genetics, Population|Markov Chains|Monte Carlo Method|Software', 'Journal Article', '10.1093/bioinformatics/btn665', '19136550', 'The ascertainment process of molecular markers amounts to disregard loci carrying alleles with low frequencies. This can result in strong biases in inferences under population genetics models if not properly taken into account by the inference algorithm. Attempting to model this censoring process in view of making inference of population structure (i.e.identifying clusters of individuals) brings up challenging numerical difficulties.'),
(74557, 2009, 'bio', 'Multiperm: shuffling multiple sequence alignments while approximately preserving dinucleotide frequencies', 'Anandam, Parvez|Torarinsson, Elfar|Ruzzo, Walter L', 'Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195-2350, USA. anandam@u.washington.edu|Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195-2350, USA. anandam@u.washington.edu|Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195-2350, USA. anandam@u.washington.edu', 'United States|United States|United States', 18, 'Algorithms|Computational Biology|Nucleotides|RNA|Sequence Alignment|Sequence Analysis, RNA|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btp006', '19136551', 'Assessing the statistical significance of structured RNA predicted from multiple sequence alignments relies on the existence of a good null model. We present here a random shuffling algorithm, Multiperm, that preserves not only the gap and local conservation structure in alignments of arbitrarily many sequences, but also the approximate dinucleotide frequencies. No shuffling algorithm that simultaneously preserves these three characteristics of a multiple (beyond pairwise) alignment has been available to date. As one benchmark, we show that it produces shuffled exonic sequences having folding free energy closer to native sequences than shuffled alignments that do not preserve dinucleotide frequencies.'),
(74558, 2009, 'bio', 'Masking residues using context-specific evolutionary conservation significantly improves short linear motif discovery', 'Davey, Norman E|Shields, Denis C|Edwards, Richard J', 'UCD Complex and Adaptive Systems Laboratory, UCD Conway Institute of Biomolecular and Biomedical Sciences, University College Dublin, Dublin 4, Ireland.|UCD Complex and Adaptive Systems Laboratory, UCD Conway Institute of Biomolecular and Biomedical Sciences, University College Dublin, Dublin 4, Ireland.|UCD Complex and Adaptive Systems Laboratory, UCD Conway Institute of Biomolecular and Biomedical Sciences, University College Dublin, Dublin 4, Ireland.', 'Ireland|Ireland|Ireland', 49, 'Algorithms|Computational Biology|Conserved Sequence|Databases, Protein|Evolution, Molecular|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btn664', '19136552', 'Short linear motifs (SLiMs) are important mediators of protein-protein interactions. Their short and degenerate nature presents a challenge for computational discovery. We sought to improve SLiM discovery by incorporating evolutionary information, since SLiMs are more conserved than surrounding residues.'),
(74559, 2009, 'bio', 'Module networks revisited: computational assessment and prioritization of model predictions', 'Joshi, Anagha|De Smet, Riet|Marchal, Kathleen|Van de Peer, Yves|Michoel, Tom', 'Department of Plant Systems Biology, VIB, Ghent University, Technologiepark 927, B-9052 Gent, Belgium.|Department of Plant Systems Biology, VIB, Ghent University, Technologiepark 927, B-9052 Gent, Belgium.|Department of Plant Systems Biology, VIB, Ghent University, Technologiepark 927, B-9052 Gent, Belgium.|Department of Plant Systems Biology, VIB, Ghent University, Technologiepark 927, B-9052 Gent, Belgium.|Department of Plant Systems Biology, VIB, Ghent University, Technologiepark 927, B-9052 Gent, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium', 70, 'Cluster Analysis|Computational Biology|Gene Regulatory Networks|Models, Genetic|Models, Statistical|Software', 'Journal Article', '10.1093/bioinformatics/btn658', '19136553', 'The solution of high-dimensional inference and prediction problems in computational biology is almost always a compromise between mathematical theory and practical constraints, such as limited computational resources. As time progresses, computational power increases but well-established inference methods often remain locked in their initial suboptimal solution.'),
(74560, 2009, 'bio', 'DTA: dihedral transition analysis for characterization of the effects of large main-chain dihedral changes in proteins', 'Nishima, Wataru|Qi, Guoying|Hayward, Steven|Kitao, Akio', 'Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Japan.|Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Japan.|Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Japan.|Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Japan.', 'Japan|Japan|Japan|Japan', 13, 'Databases, Protein|Models, Molecular|Protein Conformation|Proteins', 'Journal Article', '10.1093/bioinformatics/btp032', '19147660', 'The biological function of proteins is associated with a variety of motions, ranging from global domain motion to local motion of side chain. We propose a method, dihedral transition analysis (DTA), to identify significant dihedral angle changes between two distinct protein conformations and for characterization of the effect of these transitions on both local and global conformation.'),
(74561, 2009, 'bio', 'Principal component analysis of native ensembles of biomolecular structures (PCA_NEST): insights into functional dynamics', 'Yang, Lee-Wei|Eyal, Eran|Bahar, Ivet|Kitao, Akio', 'University of Tokyo, Institute of Molecular and Cellular Bioscience, Tokyo, Japan. lwy1@iam.u-tokyo.ac.jp|University of Tokyo, Institute of Molecular and Cellular Bioscience, Tokyo, Japan. lwy1@iam.u-tokyo.ac.jp|University of Tokyo, Institute of Molecular and Cellular Bioscience, Tokyo, Japan. lwy1@iam.u-tokyo.ac.jp|University of Tokyo, Institute of Molecular and Cellular Bioscience, Tokyo, Japan. lwy1@iam.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan', 84, 'Crystallography, X-Ray|Databases, Protein|Internet|Nuclear Magnetic Resonance, Biomolecular|Principal Component Analysis|Protein Conformation|Protein Folding|Proteins', 'Journal Article', '10.1093/bioinformatics/btp023', '19147661', 'To efficiently analyze the native ensemble of conformations accessible to proteins near their folded state and to extract essential information from observed distributions of conformations, reliable mathematical methods and computational tools are needed.'),
(74562, 2009, 'bio', 'A new cis-acting regulatory element driving gene expression in the zebrafish pineal gland', 'Alon, Shahar|Eisenberg, Eli|Jacob-Hirsch, Jasmine|Rechavi, Gideon|Vatine, Gad|Toyama, Reiko|Coon, Steven L|Klein, David C|Gothilf, Yoav', 'Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 12, 'Animals|Computational Biology|Gene Expression Regulation|Pineal Gland|Promoter Regions, Genetic|Regulatory Elements, Transcriptional|Zebrafish', 'Journal Article', '10.1093/bioinformatics/btp031', '19147662', 'The identification of functional cis-acting DNA regulatory elements is a crucial step towards understanding gene regulation. Ab initio motif detection algorithms have been extensively used in search of regulatory elements. Yet, their success in providing experimentally validated regulatory elements in vertebrates has been limited.'),
(74563, 2009, 'bio', 'A hierarchical model for incomplete alignments in phylogenetic inference', 'Cheng, Fuxia|Hartmann, Stefanie|Gupta, Mayetri|Ibrahim, Joseph G|Vision, Todd J', 'Department of Mathematics, Illinois State University, Normal, IL, USA.|Department of Mathematics, Illinois State University, Normal, IL, USA.|Department of Mathematics, Illinois State University, Normal, IL, USA.|Department of Mathematics, Illinois State University, Normal, IL, USA.|Department of Mathematics, Illinois State University, Normal, IL, USA.', 'United States|United States|United States|United States|United States', 3, 'Algorithms|Bayes Theorem|Computational Biology|Expressed Sequence Tags|Models, Statistical|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btp015', '19147663', 'Full-length DNA and protein sequences that span the entire length of a gene are ideally used for multiple sequence alignments (MSAs) and the subsequent inference of their relationships. Frequently, however, MSAs contain a substantial amount of missing data. For example, expressed sequence tags (ESTs), which are partial sequences of expressed genes, are the predominant source of sequence data for many organisms. The patterns of missing data typical for EST-derived alignments greatly compromise the accuracy of estimated phylogenies.'),
(74564, 2009, 'bio', 'MatrixDB, a database focused on extracellular protein-protein and protein-carbohydrate interactions', 'Chautard, Emilie|Ballut, Lionel|Thierry-Mieg, Nicolas|Ricard-Blum, Sylvie', 'UMR 5086 CNRS-Université Lyon 1, 7 passage du Vercors, 69367 Lyon Cedex 07, France.|UMR 5086 CNRS-Université Lyon 1, 7 passage du Vercors, 69367 Lyon Cedex 07, France.|UMR 5086 CNRS-Université Lyon 1, 7 passage du Vercors, 69367 Lyon Cedex 07, France.|UMR 5086 CNRS-Université Lyon 1, 7 passage du Vercors, 69367 Lyon Cedex 07, France.', 'France|France|France|France', 73, 'Binding Sites|Carbohydrates|Computational Biology|Database Management Systems|Databases, Protein|Extracellular Matrix|Extracellular Matrix Proteins', 'Journal Article', '10.1093/bioinformatics/btp025', '19147664', 'MatrixDB (http://matrixdb.ibcp.fr) is a database reporting mammalian protein-protein and protein-carbohydrate interactions involving extracellular molecules. It takes into account the full interaction repertoire of the extracellular matrix involving full-length molecules, fragments and multimers. The current version of MatrixDB contains 1972 interactions corresponding to 4412 experiments and involving 259 extracellular biomolecules.'),
(74565, 2009, 'bio', 'PROMOT: modular modeling for systems biology', 'Mirschel, Sebastian|Steinmetz, Katrin|Rempel, Michael|Ginkel, Martin|Gilles, Ernst Dieter', 'Systems Biology Group, Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany. mirschel@mpi-magdeburg.mpg.de|Systems Biology Group, Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany. mirschel@mpi-magdeburg.mpg.de|Systems Biology Group, Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany. mirschel@mpi-magdeburg.mpg.de|Systems Biology Group, Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany. mirschel@mpi-magdeburg.mpg.de|Systems Biology Group, Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany. mirschel@mpi-magdeburg.mpg.de', 'Germany|Germany|Germany|Germany|Germany', 63, 'Computational Biology|Computer Graphics|Databases, Factual|Logistic Models|Models, Biological|Software|Systems Biology|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp029', '19147665', 'The modeling tool PROMOT facilitates the efficient and comprehensible setup and editing of modular models coupled with customizable visual representations. Since its last major publication in 2003, PROMOT has gained new functionality in particular support of logical models, efficient editing, visual exploration, model validation and support for SBML.'),
(74566, 2009, 'bio', 'MSMAD: a computationally efficient method for the analysis of noisy array CGH data', 'Budinska, Eva|Gelnarova, Eva|Schimek, Michael G', 'Institute of Biostatistics and Analyses, Masaryk University, Kamenice 126/3, 625 00 Brno, Czech Republic. budinska@iba.muni.cz|Institute of Biostatistics and Analyses, Masaryk University, Kamenice 126/3, 625 00 Brno, Czech Republic. budinska@iba.muni.cz|Institute of Biostatistics and Analyses, Masaryk University, Kamenice 126/3, 625 00 Brno, Czech Republic. budinska@iba.muni.cz', '-|-|-', 8, 'Algorithms|Comparative Genomic Hybridization|Computational Biology|Oligonucleotide Array Sequence Analysis|Programming Languages', 'Evaluation Studies', '10.1093/bioinformatics/btp022', '19147666', 'Genome analysis has become one of the most important tools for understanding the complex process of cancerogenesis. With increasing resolution of CGH arrays, the demand for computationally efficient algorithms arises, which are effective in the detection of aberrations even in very noisy data.'),
(74567, 2009, 'bio', 'IslandViewer: an integrated interface for computational identification and visualization of genomic islands', 'Langille, Morgan G I|Brinkman, Fiona S L', 'Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada.|Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada.', 'Canada|Canada', 316, 'Computational Biology|Computer Graphics|Genomic Islands|Genomics|Internet|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp030', '19151094', 'Genomic islands (clusters of genes of probable horizontal origin, GIs) play a critical role in medically important adaptations of bacteria. Recently, several computational methods have been developed to predict GIs that utilize either sequence composition bias or comparative genomics approaches. IslandViewer is a web accessible application that provides the first user-friendly interface for obtaining precomputed GI predictions, or predictions from user-inputted sequence, using the most accurate methods for genomic island prediction: IslandPick, IslandPath-DIMOB and SIGI-HMM. The graphical interface allows easy viewing and downloading of island data in multiple formats, at both the chromosome and gene level, for method-specific, or overlapping, GI predictions.'),
(74568, 2009, 'bio', 'Jalview Version 2--a multiple sequence alignment editor and analysis workbench', 'Waterhouse, Andrew M|Procter, James B|Martin, David M A|Clamp, Michèle|Barton, Geoffrey J', 'School of Life Sciences Research, College of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK.|School of Life Sciences Research, College of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK.|School of Life Sciences Research, College of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK.|School of Life Sciences Research, College of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK.|School of Life Sciences Research, College of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Databases, Protein|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btp033', '19151095', 'Jalview Version 2 is a system for interactive WYSIWYG editing, analysis and annotation of multiple sequence alignments. Core features include keyboard and mouse-based editing, multiple views and alignment overviews, and linked structure display with Jmol. Jalview 2 is available in two forms: a lightweight Java applet for use in web applications, and a powerful desktop application that employs web services for sequence alignment, secondary structure prediction and the retrieval of alignments, sequences, annotation and structures from public databases and any DAS 1.53 compliant sequence or annotation server.'),
(74569, 2009, 'bio', 'CPSP-web-tools: a server for 3D lattice protein studies', 'Mann, Martin|Smith, Cameron|Rabbath, Mohamad|Edwards, Marlien|Will, Sebastian|Backofen, Rolf', 'Bioinformatics Group, University of Freiburg, Georges-Köhler-Allee 106, 79016 Freiburg, Germany. cpsp@informatik.uni-freiburg.de|Bioinformatics Group, University of Freiburg, Georges-Köhler-Allee 106, 79016 Freiburg, Germany. cpsp@informatik.uni-freiburg.de|Bioinformatics Group, University of Freiburg, Georges-Köhler-Allee 106, 79016 Freiburg, Germany. cpsp@informatik.uni-freiburg.de|Bioinformatics Group, University of Freiburg, Georges-Köhler-Allee 106, 79016 Freiburg, Germany. cpsp@informatik.uni-freiburg.de|Bioinformatics Group, University of Freiburg, Georges-Köhler-Allee 106, 79016 Freiburg, Germany. cpsp@informatik.uni-freiburg.de|Bioinformatics Group, University of Freiburg, Georges-Köhler-Allee 106, 79016 Freiburg, Germany. cpsp@informatik.uni-freiburg.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 18, 'Algorithms|Computational Biology|Hydrophobic and Hydrophilic Interactions|Internet|Models, Molecular|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btp034', '19151096', 'Studies on proteins are often restricted to highly simplified models to face the immense computational complexity of the associated problems. Constraint-based protein structure prediction (CPSP) tools is a package of very fast algorithms for ab initio optimal structure prediction and related problems in 3D HP-models [cubic and face centered cubic (FCC)]. Here, we present CPSP-web-tools, an interactive online interface of these programs for their immediate use. They include the first method for the direct prediction of optimal energies and structures in 3D HP side-chain models. This newest extension of the CPSP approach is described here for the first time.'),
(74570, 2009, 'bio', 'FrameDP: sensitive peptide detection on noisy matured sequences', 'Gouzy, Jérôme|Carrere, Sébastien|Schiex, Thomas', 'Laboratoire Interactions Plantes Micro-organismes (LIPM) UMR441/2594, INRA/CNRS, F-31320 Castanet Tolosan, France.|Laboratoire Interactions Plantes Micro-organismes (LIPM) UMR441/2594, INRA/CNRS, F-31320 Castanet Tolosan, France.|Laboratoire Interactions Plantes Micro-organismes (LIPM) UMR441/2594, INRA/CNRS, F-31320 Castanet Tolosan, France.', 'France|France|France', 0, 'Gene Expression Profiling|Internet|Peptides|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btp024', '19153134', 'Transcriptome sequencing represents a fundamental source of information for genome-wide studies and transcriptome analysis and will become increasingly important for expression analysis as new sequencing technologies takes over array technology. The identification of the protein-coding region in transcript sequences is a prerequisite for systematic amino acid-level analysis and more specifically for domain identification. In this article, we present FrameDP, a self-training integrative pipeline for predicting CDS in transcripts which can adapt itself to different levels of sequence qualities.'),
(74571, 2009, 'bio', 'The protein-small-molecule database, a non-redundant structural resource for the analysis of protein-ligand binding', 'Wallach, Izhar|Lilien, Ryan', 'Department of Computer Science, University of Toronto, Toronto, Ontario, Canada. izharw@cs.toronto.edu|Department of Computer Science, University of Toronto, Toronto, Ontario, Canada. izharw@cs.toronto.edu', 'Canada|Canada', 33, 'Binding Sites|Computational Biology|Databases, Protein|Ligands|Proteins', 'Journal Article', '10.1093/bioinformatics/btp035', '19153135', 'An enabling resource for drug discovery and protein function prediction is a large, accurate and actively maintained collection of protein/small-molecule complex structures. Models of binding are typically constructed from these structural libraries by generalizing the observed interaction patterns. Consequently, the quality of the model is dependent on the quality of the structural library. An ideal library should be non-biased and comprehensive, contain high-resolution structures and be actively maintained.'),
(74572, 2009, 'bio', 'Sequence-based prediction of protein interaction sites with an integrative method', 'Chen, Xue-wen|Jeong, Jong Cheol', 'Bioinformatics and Computational Life Sciences Laboratory, Information and Telecommunication Technology Center, University of Kansas, Lawrence, KS 66045, USA. xwchen@ku.edu|Bioinformatics and Computational Life Sciences Laboratory, Information and Telecommunication Technology Center, University of Kansas, Lawrence, KS 66045, USA. xwchen@ku.edu', 'United States|United States', 0, 'Algorithms|Binding Sites|Computational Biology|Databases, Protein|Models, Molecular|Protein Conformation|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btp039', '19153136', 'Identification of protein interaction sites has significant impact on understanding protein function, elucidating signal transduction networks and drug design studies. With the exponentially growing protein sequence data, predictive methods using sequence information only for protein interaction site prediction have drawn increasing interest. In this article, we propose a predictive model for identifying protein interaction sites. Without using any structure data, the proposed method extracts a wide range of features from protein sequences. A random forest-based integrative model is developed to effectively utilize these features and to deal with the imbalanced data classification problem commonly encountered in binding site predictions.'),
(74573, 2009, 'bio', 'Gclust: trans-kingdom classification of proteins using automatic individual threshold setting', 'Sato, Naoki', 'Department of Life Sciences, Graduate School of Arts and Sciences, University of Tokyo, Komaba, Meguro-ku, Tokyo, 153-8902, Japan. naokisat@bio.c.u-tokyo.ac.jp', 'Japan', 32, 'Cluster Analysis|Computational Biology|Internet|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btp047', '19158159', 'Trans-kingdom protein clustering remained difficult because of large sequence divergence between eukaryotes and prokaryotes and the presence of a transit sequence in organellar proteins. A large-scale protein clustering including such divergent organisms needs a heuristic to efficiently select similar proteins by setting a proper threshold for homologs of each protein. Here a method is described using two similarity measures and organism count.'),
(74574, 2009, 'bio', 'DSSTox chemical-index files for exposure-related experiments in ArrayExpress and Gene Expression Omnibus: enabling toxico-chemogenomics data linkages', 'Williams-DeVane, ClarLynda R|Wolf, Maritja A|Richard, Ann M', 'National Center for Computational Toxicology, Office of Research and Development, US EPA, Research Triangle Park, NC 27711, USA.|National Center for Computational Toxicology, Office of Research and Development, US EPA, Research Triangle Park, NC 27711, USA.|National Center for Computational Toxicology, Office of Research and Development, US EPA, Research Triangle Park, NC 27711, USA.', 'United States|United States|United States', 0, 'Computational Biology|Databases, Factual|Databases, Genetic|Gene Expression|Gene Expression Profiling|Genomics|Oligonucleotide Array Sequence Analysis|Software|Toxicogenetics', 'Journal Article', '10.1093/bioinformatics/btp042', '19158160', 'The Distributed Structure-Searchable Toxicity (DSSTox) ARYEXP and GEOGSE files are newly published, structure-annotated files of the chemical-associated and chemical exposure-related summary experimental content contained in the ArrayExpress Repository and Gene Expression Omnibus (GEO) Series (based on data extracted on September 20, 2008). ARYEXP and GEOGSE contain 887 and 1064 unique chemical substances mapped to 1835 and 2381 chemical exposure-related experiment accession IDs, respectively. The standardized files allow one to assess, compare and search the chemical content in each resource, in the context of the larger DSSTox toxicology data network, as well as across large public cheminformatics resources such as PubChem (http://pubchem.ncbi.nlm.nih.gov).'),
(74575, 2009, 'bio', 'Detecting gene clusters under evolutionary constraint in a large number of genomes', 'Ling, Xu|He, Xin|Xin, Dong', 'Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. xuling@uiuc.edu|Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. xuling@uiuc.edu|Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. xuling@uiuc.edu', 'United States|United States|United States', 36, 'Algorithms|Computational Biology|Escherichia coli|Evolution, Molecular|Genes, Bacterial|Genome|Genome, Bacterial|Multigene Family|Software', 'Journal Article', '10.1093/bioinformatics/btp027', '19158161', 'Spatial clusters of genes conserved across multiple genomes provide important clues to gene functions and evolution of genome organization. Existing methods of identifying these clusters often made restrictive assumptions, such as exact conservation of gene order, and relied on heuristic algorithms.'),
(74576, 2009, 'bio', 'Disperse--a software system for design of selector probes for exon resequencing applications', 'Stenberg, J|Zhang, M|Ji, H', 'Department of Medicine, Division of Oncology, Stanford University School of Medicine, Clark Center W300, 318 Campus Drive, Stanford, CA 94305-5440, USA.|Department of Medicine, Division of Oncology, Stanford University School of Medicine, Clark Center W300, 318 Campus Drive, Stanford, CA 94305-5440, USA.|Department of Medicine, Division of Oncology, Stanford University School of Medicine, Clark Center W300, 318 Campus Drive, Stanford, CA 94305-5440, USA.', 'United States|United States|United States', 0, 'Computational Biology|Exons|Genome|Oligonucleotide Probes|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btp001', '19158162', 'Selector probes enable the amplification of many selected regions of the genome in multiplex. Disperse is a software pipeline that automates the procedure of designing selector probes for exon resequencing applications.'),
(74577, 2009, 'bio', 'New evaluation measures for multifactor dimensionality reduction classifiers in gene-gene interaction analysis', 'Namkung, Junghyun|Kim, Kyunga|Yi, Sungon|Chung, Wonil|Kwon, Min-Seok|Park, Taesung', 'Bioinformatics Program, Seoul National University, Seoul 151-747, Korea.|Bioinformatics Program, Seoul National University, Seoul 151-747, Korea.|Bioinformatics Program, Seoul National University, Seoul 151-747, Korea.|Bioinformatics Program, Seoul National University, Seoul 151-747, Korea.|Bioinformatics Program, Seoul National University, Seoul 151-747, Korea.|Bioinformatics Program, Seoul National University, Seoul 151-747, Korea.', '-|-|-|-|-|-', 44, 'Computer Simulation|Gene Expression|Gene Frequency|Genetic Markers|Genetic Predisposition to Disease|Genotype', 'Evaluation Studies', '10.1093/bioinformatics/btn629', '19164302', 'Gene-gene interactions are important contributors to complex biological traits. Multifactor dimensionality reduction (MDR) is a method to analyze gene-gene interactions and has been applied to many genetics studies of complex diseases. In order to identify the best interaction model associated with disease susceptibility, MDR classifiers corresponding to interaction models has been constructed and evaluated as a predictor of disease status via a certain measure such as balanced accuracy (BA). It has been shown that the performance of MDR tends to depend on the choice of the evaluation measures.'),
(74578, 2009, 'bio', 'SIMPRO: simple protein homology detection method by using indirect signals', 'Jung, Inkyung|Kim, Dongsup', 'Department of Bio and Brain Engineering, KAIST, Daejeon 305-701, South Korea.|Department of Bio and Brain Engineering, KAIST, Daejeon 305-701, South Korea.', '-|-', 6, 'Algorithms|Computational Biology|Information Storage and Retrieval|Proteins|Reproducibility of Results|Sequence Homology, Amino Acid|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/btp048', '19164303', 'Detecting homologous proteins is one of the fundamental problems in computational biology. Many tools to solve this problem have been developed, but development of a simple, effective and generally applicable method is still desirable.'),
(74579, 2009, 'bio', 'Properties and identification of human protein drug targets', 'Bakheet, Tala M|Doig, Andrew J', 'Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Oxford Road, Manchester M13 9PT, UK.|Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Oxford Road, Manchester M13 9PT, UK.', 'United Kingdom|United Kingdom', 0, 'Amino Acid Sequence|Binding Sites|Computational Biology|Databases, Protein|Drug Discovery|Humans|Pharmaceutical Preparations|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btp002', '19164304', 'We analysed 148 human drug target proteins and 3573 non-drug targets to identify differences in their properties and to predict new potential drug targets.'),
(74580, 2009, 'bio', 'RNAither, an automated pipeline for the statistical analysis of high-throughput RNAi screens', 'Rieber, Nora|Knapp, Bettina|Eils, Roland|Kaderali, Lars', 'Viroquant Research Group Modeling, University of Heidelberg, Bioquant BQ26, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany. RNAither@gmx.de|Viroquant Research Group Modeling, University of Heidelberg, Bioquant BQ26, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany. RNAither@gmx.de|Viroquant Research Group Modeling, University of Heidelberg, Bioquant BQ26, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany. RNAither@gmx.de|Viroquant Research Group Modeling, University of Heidelberg, Bioquant BQ26, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany. RNAither@gmx.de', 'Germany|Germany|Germany|Germany', 35, 'Computational Biology|Data Interpretation, Statistical|Gene Expression Profiling|RNA Interference|RNA, Small Interfering|Software', 'Journal Article', '10.1093/bioinformatics/btp014', '19168909', 'We present RNAither, a package for the free statistical environment R which performs an analysis of high-throughput RNA interference (RNAi) knock-down experiments, generating lists of relevant genes and pathways out of raw experimental data. The library provides a quality assessment of the signal intensities, as well as a broad range of options for data normalization, different statistical tests for the identification of significant siRNAs, and a significance analysis of the biological processes involving corresponding genes. The results of the analysis are presented as a set of HTML pages. Additionally, all values and plots are available as either text files or pdf and png files.'),
(74581, 2009, 'bio', 'MOTIFATOR: detection and characterization of regulatory motifs using prokaryote transcriptome data', 'Blom, Evert-Jan|Roerdink, Jos B T M|Kuipers, Oscar P|van Hijum, Sacha A F T', 'Molecular Genetics, Groningen Biomolecular Sciences, University of Groningen, PO Box 800, 9700 AV Groningen, The Netherlands.|Molecular Genetics, Groningen Biomolecular Sciences, University of Groningen, PO Box 800, 9700 AV Groningen, The Netherlands.|Molecular Genetics, Groningen Biomolecular Sciences, University of Groningen, PO Box 800, 9700 AV Groningen, The Netherlands.|Molecular Genetics, Groningen Biomolecular Sciences, University of Groningen, PO Box 800, 9700 AV Groningen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Conserved Sequence|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Prokaryotic Cells|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btp013', '19168910', 'Unraveling regulatory mechanisms (e.g. identification of motifs in cis-regulatory regions) remains a major challenge in the analysis of transcriptome experiments. Existing applications identify putative motifs from gene lists obtained at rather arbitrary cutoff and require additional manual processing steps. Our standalone application MOTIFATOR identifies the most optimal parameters for motif discovery and creates an interactive visualization of the results. Discovered putative motifs are functionally characterized, thereby providing valuable insight in the biological processes that could be controlled by the motif.'),
(74582, 2009, 'bio', 'Sparse linear discriminant analysis for simultaneous testing for the significance of a gene set/pathway and gene selection', 'Wu, Michael C|Zhang, Lingsong|Wang, Zhaoxi|Christiani, David C|Lin, Xihong', 'Department of Biostatistics, Harvard School of Public Health, 655 Huntington Ave., Boston, MA 02115, USA.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Ave., Boston, MA 02115, USA.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Ave., Boston, MA 02115, USA.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Ave., Boston, MA 02115, USA.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Ave., Boston, MA 02115, USA.', 'United States|United States|United States|United States|United States', 76, 'Algorithms|Databases, Protein|Diabetes Mellitus|Discriminant Analysis|Gene Expression Profiling|Humans', 'Journal Article', '10.1093/bioinformatics/btp019', '19168911', 'Pathway and gene set-based approaches for the analysis of gene expression profiling experiments have become increasingly popular for addressing problems associated with individual gene analysis. Since most genes are not differently expressed, existing gene set tests, which consider all the genes within a gene set, are subject to considerable noise and power loss, a concern exacerbated in studies in which the degree of differential expression is moderate for truly differentially expressed genes. For a significantly differentially expressed pathway, it is also of substantial interest to select important genes that drive the differential expression of the pathway.'),
(74583, 2009, 'bio', 'Variable locus length in the human genome leads to ascertainment bias in functional inference for non-coding elements', 'Taher, Leila|Ovcharenko, Ivan', 'Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.|Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.', 'United States|United States', 21, 'Computational Biology|DNA, Intergenic|Databases, Genetic|Genome, Human|Humans', 'Journal Article', '10.1093/bioinformatics/btp043', '19168912', 'Several functional gene annotation databases have been developed in the recent years, and are widely used to infer the biological function of gene sets, by scrutinizing the attributes that appear over- and underrepresented. However, this strategy is not directly applicable to the study of non-coding DNA, as the non-coding sequence span varies greatly among different gene loci in the human genome and longer loci have a higher likelihood of being selected purely by chance. Therefore, conclusions involving the function of non-coding elements that are drawn based on the annotation of neighboring genes are often biased. We assessed the systematic bias in several particular Gene Ontology (GO) categories using the standard hypergeometric test, by randomly sampling non-coding elements from the human genome and inferring their function based on the functional annotation of the closest genes. While no category is expected to occur significantly over- or underrepresented for a random selection of elements, categories such as cell adhesion, nervous system development and transcription factor activities appeared to be systematically overrepresented, while others such as olfactory receptor activity-underrepresented.'),
(74584, 2009, 'bio', 'AssociationViewer: a scalable and integrated software tool for visualization of large-scale variation data in genomic context', 'Martin, Olivier|Valsesia, Armand|Telenti, Amalio|Xenarios, Ioannis|Stevenson, Brian J', 'Swiss Institute of Bioinformatics, Switzerland.|Swiss Institute of Bioinformatics, Switzerland.|Swiss Institute of Bioinformatics, Switzerland.|Swiss Institute of Bioinformatics, Switzerland.|Swiss Institute of Bioinformatics, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Computational Biology|Databases, Genetic|Genomics|Internet|Linkage Disequilibrium|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp017', '19168913', 'We present a tool designed for visualization of large-scale genetic and genomic data exemplified by results from genome-wide association studies. This software provides an integrated framework to facilitate the interpretation of SNP association studies in genomic context. Gene annotations can be retrieved from Ensembl, linkage disequilibrium data downloaded from HapMap and custom data imported in BED or WIG format. AssociationViewer integrates functionalities that enable the aggregation or intersection of data tracks. It implements an efficient cache system and allows the display of several, very large-scale genomic datasets.'),
(74585, 2009, 'bio', 'KEA: kinase enrichment analysis', 'Lachmann, Alexander|Maayan, Avi', 'Department of Pharmacology and Systems Therapeutics, Systems Biology Center in New York, Icahn Medical Institute, Mount Sinai School of Medicine, 1425 Madison Avenue, New York, NY 10029, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center in New York, Icahn Medical Institute, Mount Sinai School of Medicine, 1425 Madison Avenue, New York, NY 10029, USA.', 'United States|United States', 103, 'Computational Biology|Databases, Protein|Internet|Phosphorylation|Phosphotransferases|Software', 'Journal Article', '10.1093/bioinformatics/btp026', '19176546', 'Multivariate experiments applied to mammalian cells often produce lists of proteins/genes altered under treatment versus control conditions. Such lists can be projected onto prior knowledge of kinase-substrate interactions to infer the list of kinases associated with a specific protein list. By computing how the proportion of kinases, associated with a specific list of proteins/genes, deviates from an expected distribution, we can rank kinases and kinase families based on the likelihood that these kinases are functionally associated with regulating the cell under specific experimental conditions. Such analysis can assist in producing hypotheses that can explain how the kinome is involved in the maintenance of different cellular states and can be manipulated to modulate cells towards a desired phenotype.'),
(74586, 2009, 'bio', 'A novel meta-analysis method exploiting consistency of high-throughput experiments', 'Rajaram, Satwik', 'Department of Physics,1110 W. Green Street, University of Illinois at Urbana-Champaign, Urbana, IL 61801-3080, USA. srajaram@uiuc.edu', 'United States', 2, 'Computational Biology|Gene Expression Profiling|Genes, cdc|Meta-Analysis as Topic|Oligonucleotide Array Sequence Analysis|Schizosaccharomyces', 'Journal Article', '10.1093/bioinformatics/btp007', '19176547', 'Large-scale biological experiments provide snapshots into the huge number of processes running in parallel within the organism. These processes depend on a large number of (hidden) (epi)genetic, social, environmental and other factors that are out of experimentalists control. This makes it extremely difficult to identify the dominant processes and the elements involved in them based on a single experiment. It is therefore desirable to use multiple sets of experiments targeting the same phenomena while differing in some experimental parameters (hidden or controllable). Although such datasets are becoming increasingly common, their analysis is complicated by the fact that the various biological elements could be influenced by different sets of factors.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(74587, 2009, 'bio', 'Benchmarks for identification of ordinary differential equations from time series data', 'Gennemark, Peter|Wedelin, Dag', 'Department of Mathematical Sciences, University of Göteborg, SE-412 96 Göteborg, Sweden. peterg@chalmers.se|Department of Mathematical Sciences, University of Göteborg, SE-412 96 Göteborg, Sweden. peterg@chalmers.se', 'Sweden|Sweden', 30, 'Algorithms|Benchmarking|Computational Biology|Kinetics|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btp050', '19176548', 'In recent years, the biological literature has seen a significant increase of reported methods for identifying both structure and parameters of ordinary differential equations (ODEs) from time series data. A natural way to evaluate the performance of such methods is to try them on a sufficient number of realistic test cases. However, weak practices in specifying identification problems and lack of commonly accepted benchmark problems makes it difficult to evaluate and compare different methods.'),
(74588, 2009, 'bio', 'Genome-wide association analysis by lasso penalized logistic regression', 'Wu, Tong Tong|Chen, Yi Fang|Hastie, Trevor|Sobel, Eric|Lange, Kenneth', 'Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD 20742, USA.|Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD 20742, USA.|Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD 20742, USA.|Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD 20742, USA.|Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD 20742, USA.', 'United States|United States|United States|United States|United States', 428, 'Computational Biology|Genome-Wide Association Study|Internet|Logistic Models|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btp041', '19176549', 'In ordinary regression, imposition of a lasso penalty makes continuous model selection straightforward. Lasso penalized regression is particularly advantageous when the number of predictors far exceeds the number of observations.'),
(74589, 2009, 'bio', 'Automated procedure for candidate compound selection in GC-MS metabolomics based on prediction of Kovats retention index', 'Mihaleva, V V|Verhoeven, H A|de Vos, R C H|Hall, R D|van Ham, R C H J', 'Applied Bioinformatics, Plant Research International, Droevendaalsesteeg 1, Wageningen, The Netherlands.|Applied Bioinformatics, Plant Research International, Droevendaalsesteeg 1, Wageningen, The Netherlands.|Applied Bioinformatics, Plant Research International, Droevendaalsesteeg 1, Wageningen, The Netherlands.|Applied Bioinformatics, Plant Research International, Droevendaalsesteeg 1, Wageningen, The Netherlands.|Applied Bioinformatics, Plant Research International, Droevendaalsesteeg 1, Wageningen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 29, 'Algorithms|Computational Biology|Gas Chromatography-Mass Spectrometry|Linear Models|Metabolomics', 'Journal Article', '10.1093/bioinformatics/btp056', '19176550', 'Matching both the retention index (RI) and the mass spectrum of an unknown compound against a mass spectral reference library provides strong evidence for a correct identification of that compound. Data on retention indices are, however, available for only a small fraction of the compounds in such libraries. We propose a quantitative structure-RI model that enables the ranking and filtering of putative identifications of compounds for which the predicted RI falls outside a predefined window.'),
(74590, 2009, 'bio', 'QMSim: a large-scale genome simulator for livestock', 'Sargolzaei, Mehdi|Schenkel, Flavio S', 'Department of Animal and Poultry Science, University of Guelph, Guelph, Ontario, Canada. msargol@uoguelph.ca|Department of Animal and Poultry Science, University of Guelph, Guelph, Ontario, Canada. msargol@uoguelph.ca', 'Canada|Canada', 171, 'Animals|Animals, Domestic|Computational Biology|Genome|Genotype|Pedigree|Software', 'Journal Article', '10.1093/bioinformatics/btp045', '19176551', 'QMSim was designed to simulate large-scale genotyping data in multiple and complex livestock pedigrees. The simulation is basically carried out in two steps. In the first step, a historical population is simulated to establish mutation-drift equilibrium, and in the second step, recent population structures are generated, which can be very complex. A wide variety of genome architectures, ranging from infinitesimal model to single-locus model, can be simulated. The program is efficient in terms of computing time and memory requirements.'),
(74591, 2009, 'bio', 'Serial dilution curve: a new method for analysis of reverse phase protein array data', 'Zhang, Li|Wei, Qingyi|Mao, Li|Liu, Wenbin|Mills, Gordon B|Coombes, Kevin', 'Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler street, Unit 1410, Houston, TX 77030, USA. lzhangli@mdanderson.org|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler street, Unit 1410, Houston, TX 77030, USA. lzhangli@mdanderson.org|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler street, Unit 1410, Houston, TX 77030, USA. lzhangli@mdanderson.org|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler street, Unit 1410, Houston, TX 77030, USA. lzhangli@mdanderson.org|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler street, Unit 1410, Houston, TX 77030, USA. lzhangli@mdanderson.org|Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler street, Unit 1410, Houston, TX 77030, USA. lzhangli@mdanderson.org', 'United States|United States|United States|United States|United States|United States', 0, 'Indicator Dilution Techniques|Protein Array Analysis|Proteins|Research Design|Software', 'Comparative Study', '10.1093/bioinformatics/btn663', '19176552', 'Reverse phase protein arrays (RPPAs) are a powerful high-throughput tool for measuring protein concentrations in a large number of samples. In RPPA technology, the original samples are often diluted successively multiple times, forming dilution series to extend the dynamic range of the measurements and to increase confidence in quantitation. An RPPA experiment is equivalent to running multiple ELISA assays concurrently except that there is usually no known protein concentration from which one can construct a standard response curve. Here, we describe a new method called serial dilution curve for RPPA data analysis. Compared with the existing methods, the new method has the advantage of using fewer parameters and offering a simple way of visualizing the raw data. We showed how the method can be used to examine data quality and to obtain robust quantification of protein concentrations.'),
(74592, 2009, 'bio', 'Testing significance relative to a fold-change threshold is a TREAT', 'McCarthy, Davis J|Smyth, Gordon K', 'The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3050, Australia.|The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3050, Australia.', 'Australia|Australia', 269, 'Algorithms|Gene Expression Profiling|Internet|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btp053', '19176553', 'Statistical methods are used to test for the differential expression of genes in microarray experiments. The most widely used methods successfully test whether the true differential expression is different from zero, but give no assurance that the differences found are large enough to be biologically meaningful.'),
(74593, 2009, 'bio', 'Fragment-based identification of druggable hot spots of proteins using Fourier domain correlation techniques', 'Brenke, Ryan|Kozakov, Dima|Chuang, Gwo-Yu|Beglov, Dmitri|Hall, David|Landon, Melissa R|Mattos, Carla|Vajda, Sandor', 'Program in Bioinformatics, Boston University, Boston, MA, USA.|Program in Bioinformatics, Boston University, Boston, MA, USA.|Program in Bioinformatics, Boston University, Boston, MA, USA.|Program in Bioinformatics, Boston University, Boston, MA, USA.|Program in Bioinformatics, Boston University, Boston, MA, USA.|Program in Bioinformatics, Boston University, Boston, MA, USA.|Program in Bioinformatics, Boston University, Boston, MA, USA.|Program in Bioinformatics, Boston University, Boston, MA, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 281, 'Algorithms|Binding Sites|Crystallography, X-Ray|Internet|Models, Molecular|Protein Conformation|Protein Interaction Mapping|Proteins', 'Journal Article', '10.1093/bioinformatics/btp036', '19176554', 'The binding sites of proteins generally contain smaller regions that provide major contributions to the binding free energy and hence are the prime targets in drug design. Screening libraries of fragment-sized compounds by NMR or X-ray crystallography demonstrates that such hot spot regions bind a large variety of small organic molecules, and that a relatively high hit rate is predictive of target sites that are likely to bind drug-like ligands with high affinity. Our goal is to determine the hot spots computationally rather than experimentally.'),
(74594, 2009, 'bio', 'A flexible rank-based framework for detecting copy number aberrations from array data', 'LaFramboise, Thomas|Winckler, Wendy|Thomas, Roman K', 'Department of Genetics, Case Western Reserve University, Cleveland, OH 44106, USA. Thomas.LaFramboise@case.edu|Department of Genetics, Case Western Reserve University, Cleveland, OH 44106, USA. Thomas.LaFramboise@case.edu|Department of Genetics, Case Western Reserve University, Cleveland, OH 44106, USA. Thomas.LaFramboise@case.edu', 'United States|United States|United States', 0, 'Autistic Disorder|Computational Biology|DNA|Gene Dosage|Genetic Variation|Genome|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btp063', '19176555', 'DNA copy number aberration--both inherited and sporadic--is a significant contributor to a variety of human diseases. Copy number characterization is therefore an area of intense research. Probe hybridization-based arrays are important tools used to measure copy number in a high-throughput manner.'),
(74595, 2009, 'bio', 'Parallelized prediction error estimation for evaluation of high-dimensional models', 'Porzelius, Christine|Binder, Harald|Schumacher, Martin', 'Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, 79104 Freiburg, Germany. cp@fdm.uni-freiburg.de|Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, 79104 Freiburg, Germany. cp@fdm.uni-freiburg.de|Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, 79104 Freiburg, Germany. cp@fdm.uni-freiburg.de', 'Germany|Germany|Germany', 10, 'Bias|Computational Biology|Internet|Models, Statistical|Software', 'Journal Article', '10.1093/bioinformatics/btp062', '19176556', 'There is a multitude of new techniques that promise to extract predictive information in bioinformatics applications. It has been recognized that a first step for validation of the resulting model fits should rely on proper use of resampling techniques. However, this advice is frequently not followed, potential reasons being difficulty of correct implementation and computational demand. This is addressed by the R package peperr, which is designed for reliable prediction error estimation through resampling, potentially accelerated by parallel execution on a compute cluster. Its interface allows easy connection to newly developed model fitting routines. Performance evaluation of the latter is furthermore guided by diagnostic plots, which helps to detect specific problems due to high-dimensional data structures.'),
(74596, 2009, 'bio', 'The DICS repository: module-assisted analysis of disease-related gene lists', 'Dietmann, Sabine|Georgii, Elisabeth|Antonov, Alexey|Tsuda, Koji|Mewes, Hans-Werner', 'Institute for Bioinformatics and Systems Biology, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. sabine.dietmann@googlemail.com|Institute for Bioinformatics and Systems Biology, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. sabine.dietmann@googlemail.com|Institute for Bioinformatics and Systems Biology, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. sabine.dietmann@googlemail.com|Institute for Bioinformatics and Systems Biology, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. sabine.dietmann@googlemail.com|Institute for Bioinformatics and Systems Biology, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. sabine.dietmann@googlemail.com', 'Germany|Germany|Germany|Germany|Germany', 8, 'Computational Biology|Databases, Protein|Disease|Genes|Humans|Internet|Protein Interaction Mapping|Proteins', 'Journal Article', '10.1093/bioinformatics/btp055', '19176557', 'The DICS database is a dynamic web repository of computationally predicted functional modules from the human protein-protein interaction network. It provides references to the CORUM, DrugBank, KEGG and Reactome pathway databases. DICS can be accessed for retrieving sets of overlapping modules and protein complexes that are significantly enriched in a gene list, thereby providing valuable information about the functional context.'),
(74597, 2009, 'bio', 'Retention time alignment algorithms for LC/MS data must consider non-linear shifts', 'Podwojski, Katharina|Fritsch, Arno|Chamrad, Daniel C|Paul, Wolfgang|Sitek, Barbara|Stühler, Kai|Mutzel, Petra|Stephan, Christian|Meyer, Helmut E|Urfer, Wolfgang|Ickstadt, Katja|Rahnenführer, Jörg', 'Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de|Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de|Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de|Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de|Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de|Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de|Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de|Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de|Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de|Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de|Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de|Fakultät Statistik, Technische Universität Dortmund, 44221 Dortmund, Germany. katharina.podwojski@tu-dortmund.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 60, 'Algorithms|Chromatography, Liquid|Computer Simulation|Mass Spectrometry|Proteins|Proteome|Proteomics', 'Comparative Study', '10.1093/bioinformatics/btp052', '19176558', 'Proteomics has particularly evolved to become of high interest for the field of biomarker discovery and drug development. Especially the combination of liquid chromatography and mass spectrometry (LC/MS) has proven to be a powerful technique for analyzing protein mixtures. Clinically orientated proteomic studies will have to compare hundreds of LC/MS runs at a time. In order to compare different runs, sophisticated preprocessing steps have to be performed. An important step is the retention time (rt) alignment of LC/MS runs. Especially non-linear shifts in the rt between pairs of LC/MS runs make this a crucial and non-trivial problem.'),
(74598, 2009, 'bio', 'A novel comprehensive wave-form MS data processing method', 'Chen, Shuo|Li, Ming|Hong, Don|Billheimer, Dean|Li, Huiming|Xu, Baogang J|Shyr, Yu', 'Division of Cancer Biostatistics, Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA.|Division of Cancer Biostatistics, Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA.|Division of Cancer Biostatistics, Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA.|Division of Cancer Biostatistics, Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA.|Division of Cancer Biostatistics, Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA.|Division of Cancer Biostatistics, Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA.|Division of Cancer Biostatistics, Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA.', 'United States|United States|United States|United States|United States|United States|United States', 14, 'Algorithms|Computational Biology|Mass Spectrometry|Proteins', 'Journal Article', '10.1093/bioinformatics/btp060', '19176559', 'Mass spectrometry (MS) can generate high-throughput protein profiles for biomedical research to discover biologically related protein patterns/biomarkers. The noisy functional MS data collected by current technologies, however, require consistent, sensitive and robust data-processing techniques for successful biomedical application. Therefore, it is important to detect features precisely for each spectrum, quantify them well and assign a unique label to features from the same protein/peptide across spectra.'),
(74599, 2009, 'bio', 'Fast computation of neighbor seeds', 'Ilie, Lucian|Ilie, Silvana', 'Department of Computer Science, University of Western Ontario, London N6A 5B7, Ontario, Canada. ilie@csd.uwo.ca|Department of Computer Science, University of Western Ontario, London N6A 5B7, Ontario, Canada. ilie@csd.uwo.ca', 'Canada|Canada', 3, 'Algorithms|Computational Biology|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btp054', '19176560', 'Alignment of biological sequences is one of the most frequently performed computer tasks. The current state of the art involves the use of (multiple) spaced seeds for producing high quality alignments. A particular important class is that of neighbor seeds which combine high sensitivity with reduced space requirements. Current algorithms for computing good neighbor seeds are very slow (exponential).'),
(74600, 2009, 'bio', 'Double water exclusion: a hypothesis refining the O-ring theory for the hot spots at protein interfaces', 'Li, Jinyan|Liu, Qian', 'Bioinformatics Research Center, School of Computer Engineering, Nanyang Technological University, Singapore 639798. jyli@ntu.edu.sg|Bioinformatics Research Center, School of Computer Engineering, Nanyang Technological University, Singapore 639798. jyli@ntu.edu.sg', 'Singapore|Singapore', 54, 'Algorithms|Computational Biology|Databases, Protein|Models, Molecular|Protein Conformation|Proteins|Thermodynamics|Water', 'Journal Article', '10.1093/bioinformatics/btp058', '19179356', 'The O-ring theory reveals that the binding hot spot at a protein interface is surrounded by a ring of residues that are energetically less important than the residues in the hot spot. As this ring of residues is served to occlude water molecules from the hot spot, the O-ring theory is also called water exclusion hypothesis. We propose a double water exclusion hypothesis to refine the O-ring theory by assuming the hot spot itself is water-free. To computationally model a water-free hot spot, we use a biclique pattern that is defined as two maximal groups of residues from two chains in a protein complex holding the property that every residue contacts with all residues in the other group.'),
(74601, 2009, 'bio', 'SECISaln, a web-based tool for the creation of structure-based alignments of eukaryotic SECIS elements', 'Chapple, Charles E|Guigó, Roderic|Krol, Alain', 'Institut Municipal dInvestigació Mèdica, Universitat Pompeu Fabra and Parc de Recerca Biomedica de Barcelona, Carrer del Doctor Aiguader 88, 08003, Barcelona, Catalonia, Spain. charles.chapple@crg.es|Institut Municipal dInvestigació Mèdica, Universitat Pompeu Fabra and Parc de Recerca Biomedica de Barcelona, Carrer del Doctor Aiguader 88, 08003, Barcelona, Catalonia, Spain. charles.chapple@crg.es|Institut Municipal dInvestigació Mèdica, Universitat Pompeu Fabra and Parc de Recerca Biomedica de Barcelona, Carrer del Doctor Aiguader 88, 08003, Barcelona, Catalonia, Spain. charles.chapple@crg.es', 'Spain|Spain|Spain', 32, '3 Untranslated Regions|Base Sequence|Codon, Terminator|Computational Biology|Eukaryotic Cells|Internet|Molecular Sequence Data|Nucleic Acid Conformation|Protein Structure, Secondary|RNA|Selenoproteins|Software', 'Journal Article', '10.1093/bioinformatics/btp020', '19179357', 'Selenoproteins contain the 21st amino acid selenocysteine which is encoded by an inframe UGA codon, usually read as a stop. In eukaryotes, its co-translational recoding requires the presence of an RNA stem-loop structure, the SECIS element in the 3 untranslated region of (UTR) selenoprotein mRNAs. Despite little sequence conservation, SECIS elements share the same overall secondary structure. Until recently, the lack of a significantly high number of selenoprotein mRNA sequences hampered the identification of other potential sequence conservation. In this work, the web-based tool SECISaln provides for the first time an extensive structure-based sequence alignment of SECIS elements resulting from the well-defined secondary structure of the SECIS RNA and the increased size of the eukaryotic selenoproteome. We have used SECISaln to improve our knowledge of SECIS secondary structure and to discover novel, conserved nucleotide positions and we believe it will be a useful tool for the selenoprotein and RNA scientific communities.'),
(74602, 2009, 'bio', 'CORNA: testing gene lists for regulation by microRNAs', 'Wu, X|Watson, M', 'Bioinformatics Group, Institute for Animal Health, Compton, RG20 7NN, UK. xikun.wu@bbsrc.ac.uk|Bioinformatics Group, Institute for Animal Health, Compton, RG20 7NN, UK. xikun.wu@bbsrc.ac.uk', 'United Kingdom|United Kingdom', 48, 'Computational Biology|Databases, Genetic|Gene Expression Regulation|Genomics|MicroRNAs|Software', 'Journal Article', '10.1093/bioinformatics/btp059', '19181683', 'With the increasing use of post-genomics techniques to examine a wide variety of biological systems in laboratories throughout the world, scientists are often presented with lists of genes that they must make sense of. A consistently challenging problem is that of defining co-regulated genes within those gene lists. In recent years, microRNAs have emerged as a mechanism for regulating several cellular processes. In this article, we report on how gene lists and microRNA targets data may be integrated to test for significant associations between gene lists and microRNAs.'),
(74603, 2009, 'bio', 'Exploring phenotype-associated modules in an oral cavity tumor using an integrated framework', 'Sun, Zhirong|Luo, Jie|Zhou, Yun|Luo, Junjie|Liu, Ke|Li, Wenting', 'Institute of Bioinformatics and Systems Biology, State Key Laboratory of Biomembrane and Membrane Biotechnology and Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, 100084, China. sunzhr@mail.tsinghua.edu.cn|Institute of Bioinformatics and Systems Biology, State Key Laboratory of Biomembrane and Membrane Biotechnology and Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, 100084, China. sunzhr@mail.tsinghua.edu.cn|Institute of Bioinformatics and Systems Biology, State Key Laboratory of Biomembrane and Membrane Biotechnology and Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, 100084, China. sunzhr@mail.tsinghua.edu.cn|Institute of Bioinformatics and Systems Biology, State Key Laboratory of Biomembrane and Membrane Biotechnology and Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, 100084, China. sunzhr@mail.tsinghua.edu.cn|Institute of Bioinformatics and Systems Biology, State Key Laboratory of Biomembrane and Membrane Biotechnology and Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, 100084, China. sunzhr@mail.tsinghua.edu.cn|Institute of Bioinformatics and Systems Biology, State Key Laboratory of Biomembrane and Membrane Biotechnology and Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, 100084, China. sunzhr@mail.tsinghua.edu.cn', 'China|China|China|China|China|China', 4, 'Algorithms|Computational Biology|Humans|Mouth Neoplasms|Phenotype|Prognosis', 'Journal Article', '10.1093/bioinformatics/btp057', '19181684', 'Like most human diseases, tumors are complex traits, the genesis and development of which recruit a number of genes and several important biological processes. As proteins involved in common processes tend to be centralized in the same local area of protein-protein interaction networks, here a novel framework has been developed to identify which areas of the networks are most relevant to a phenotype.'),
(74604, 2009, 'bio', 'NOBLAST and JAMBLAST: New Options for BLAST and a Java Application Manager for BLAST results', 'Lagnel, Jacques|Tsigenopoulos, Costas S|Iliopoulos, Ioannis', 'Institute of Marine Biology and Genetics, Hellenic Centre for Marine Research, Heraklion 71003, Crete, Greece. lagnel@her.hcmr.gr|Institute of Marine Biology and Genetics, Hellenic Centre for Marine Research, Heraklion 71003, Crete, Greece. lagnel@her.hcmr.gr|Institute of Marine Biology and Genetics, Hellenic Centre for Marine Research, Heraklion 71003, Crete, Greece. lagnel@her.hcmr.gr', 'Greece|Greece|Greece', 19, 'Computational Biology|Internet|Programming Languages|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btp067', '19181685', 'NOBLAST (New Options for BLAST) is an open source program that provides a new user-friendly tabular output format for various NCBI BLAST programs (Blastn, Blastp, Blastx, Tblastn, Tblastx, Mega BLAST and Psi BLAST) without any use of a parser and provides E-value correction in case of use of segmented BLAST database. JAMBLAST using the NOBLAST output allows the user to manage, view and filter the BLAST hits using a number of selection criteria.'),
(74605, 2009, 'bio', 'Benchmarking regulatory network reconstruction with GRENDEL', 'Haynes, Brian C|Brent, Michael R', 'Center for Genome Sciences and Department of Computer Science, Washington University, St Louis, MO, USA.|Center for Genome Sciences and Department of Computer Science, Washington University, St Louis, MO, USA.', 'United States|United States', 22, 'Algorithms|Benchmarking|Computational Biology|Gene Regulatory Networks', 'Journal Article', '10.1093/bioinformatics/btp068', '19188190', 'Over the past decade, the prospect of inferring networks of gene regulation from high-throughput experimental data has received a great deal of attention. In contrast to the massive effort that has gone into automated deconvolution of biological networks, relatively little effort has been invested in benchmarking the proposed algorithms. The rate at which new network inference methods are being proposed far outpaces our ability to objectively evaluate and compare them. This is largely due to a lack of fully understood biological networks to use as gold standards.'),
(74606, 2009, 'bio', 'SciMiner: web-based literature mining tool for target identification and functional enrichment analysis', 'Hur, Junguk|Schuyler, Adam D|States, David J|Feldman, Eva L', 'Bioinformatics Program, University of Michigan, Ann Arbor, MI 48109, USA. juhur@umich.edu|Bioinformatics Program, University of Michigan, Ann Arbor, MI 48109, USA. juhur@umich.edu|Bioinformatics Program, University of Michigan, Ann Arbor, MI 48109, USA. juhur@umich.edu|Bioinformatics Program, University of Michigan, Ann Arbor, MI 48109, USA. juhur@umich.edu', 'United States|United States|United States|United States', 62, 'Computational Biology|Genes|Information Storage and Retrieval|Internet|MEDLINE|Proteins|PubMed|Publications|Software|United States', 'Journal Article', '10.1093/bioinformatics/btp049', '19188191', 'SciMiner is a web-based literature mining and functional analysis tool that identifies genes and proteins using a context specific analysis of MEDLINE abstracts and full texts. SciMiner accepts a free text query (PubMed Entrez search) or a list of PubMed identifiers as input. SciMiner uses both regular expression patterns and dictionaries of gene symbols and names compiled from multiple sources. Ambiguous acronyms are resolved by a scoring scheme based on the co-occurrence of acronyms and corresponding description terms, which incorporates optional user-defined filters. Functional enrichment analyses are used to identify highly relevant targets (genes and proteins), GO (Gene Ontology) terms, MeSH (Medical Subject Headings) terms, pathways and protein-protein interaction networks by comparing identified targets from one search result with those from other searches or to the full HGNC [HUGO (Human Genome Organization) Gene Nomenclature Committee] gene set. The performance of gene/protein name identification was evaluated using the BioCreAtIvE (Critical Assessment of Information Extraction systems in Biology) version 2 (Year 2006) Gene Normalization Task as a gold standard. SciMiner achieved 87.1% recall, 71.3% precision and 75.8% F-measure. SciMiners literature mining performance coupled with functional enrichment analyses provides an efficient platform for retrieval and summary of rich biological information from corpora of users interests.'),
(74607, 2009, 'bio', 'Accurate identification of orthologous segments among multiple genomes', 'Hachiya, Tsuyoshi|Osana, Yasunori|Popendorf, Kris|Sakakibara, Yasubumi', 'Department of Biosciences and Informatics, Keio University, Seikei University, Japan. hacchy@dna.bio.keio.ac.jp|Department of Biosciences and Informatics, Keio University, Seikei University, Japan. hacchy@dna.bio.keio.ac.jp|Department of Biosciences and Informatics, Keio University, Seikei University, Japan. hacchy@dna.bio.keio.ac.jp|Department of Biosciences and Informatics, Keio University, Seikei University, Japan. hacchy@dna.bio.keio.ac.jp', 'Japan|Japan|Japan|Japan', 24, 'Algorithms|Computational Biology|Genome|Genomics|Sequence Alignment|Software|Synteny', 'Journal Article', '10.1093/bioinformatics/btp070', '19188192', 'The accurate detection of orthologous segments (also referred to as syntenic segments) plays a key role in comparative genomics, as it is useful for inferring genome rearrangement scenarios and computing whole-genome alignments. Although a number of algorithms for detecting orthologous segments have been proposed, none of them contain a framework for optimizing their parameter values.'),
(74608, 2009, 'bio', 'High-performance gene name normalization with GeNo', 'Wermter, Joachim|Tomanek, Katrin|Hahn, Udo', 'Jena University Language and Information Engineering Lab, Friedrich-Schiller-Universität Jena, Fürstengraben 30, 07743 Jena, Germany. joachim.wermter@uni-jena.de|Jena University Language and Information Engineering Lab, Friedrich-Schiller-Universität Jena, Fürstengraben 30, 07743 Jena, Germany. joachim.wermter@uni-jena.de|Jena University Language and Information Engineering Lab, Friedrich-Schiller-Universität Jena, Fürstengraben 30, 07743 Jena, Germany. joachim.wermter@uni-jena.de', 'Germany|Germany|Germany', 76, 'Algorithms|Genes|Proteins|Software|Terminology as Topic', 'Journal Article', '10.1093/bioinformatics/btp071', '19188193', 'The recognition and normalization of textual mentions of gene and protein names is both particularly important and challenging. Its importance lies in the fact that they constitute the crucial conceptual entities in biomedicine. Their recognition and normalization remains a challenging task because of widespread gene name ambiguities within species, across species, with common English words and with medical sublanguage terms.'),
(74609, 2009, 'bio', 'Meta-analysis of age-related gene expression profiles identifies common signatures of aging', 'de Magalhães, João Pedro|Curado, João|Church, George M', 'Department of Genetics, Harvard Medical School, Boston, MA 02115, USA. jp@senescence.info|Department of Genetics, Harvard Medical School, Boston, MA 02115, USA. jp@senescence.info|Department of Genetics, Harvard Medical School, Boston, MA 02115, USA. jp@senescence.info', 'United States|United States|United States', 407, 'Aging|Animals|Gene Expression Profiling|Humans|Mice|Rats|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btp073', '19189975', 'Numerous microarray studies of aging have been conducted, yet given the noisy nature of gene expression changes with age, elucidating the transcriptional features of aging and how these relate to physiological, biochemical and pathological changes remains a critical problem.'),
(74610, 2009, 'bio', 'Genetic network inference as a series of discrimination tasks', 'Kimura, Shuhei|Nakayama, Satoshi|Hatakeyama, Mariko', 'Graduate School of Engineering, Tottori University, Koyama-minami, Tottori, Japan. kimura@ike.tottori-u.ac.jp|Graduate School of Engineering, Tottori University, Koyama-minami, Tottori, Japan. kimura@ike.tottori-u.ac.jp|Graduate School of Engineering, Tottori University, Koyama-minami, Tottori, Japan. kimura@ike.tottori-u.ac.jp', 'Japan|Japan|Japan', 35, 'Algorithms|Computational Biology|Gene Expression Profiling|Gene Regulatory Networks', 'Journal Article', '10.1093/bioinformatics/btp072', '19189976', 'Genetic network inference methods based on sets of differential equations generally require a great deal of time, as the equations must be solved many times. To reduce the computational cost, researchers have proposed other methods for inferring genetic networks by solving sets of differential equations only a few times, or even without solving them at all. When we try to obtain reasonable network models using these methods, however, we must estimate the time derivatives of the gene expression levels with great precision. In this study, we propose a new method to overcome the drawbacks of inference methods based on sets of differential equations.'),
(74611, 2009, 'bio', 'Systems biology metabolic modeling assistant: an ontology-based tool for the integration of metabolic data in kinetic modeling', 'Reyes-Palomares, Armando|Montañez, Raul|Real-Chicharro, Alejando|Chniber, Othmane|Kerzazi, Amine|Navas-Delgado, Ismael|Medina, Miguel Angel|Aldana-Montes, José F|Sánchez-Jiménez, Francisca', 'Department of Molecular Biology and Biochemistry and unit 741 of CIBER de Enfermedades Raras, Campus de Teatinos, University of Malaga, 29071, Spain.|Department of Molecular Biology and Biochemistry and unit 741 of CIBER de Enfermedades Raras, Campus de Teatinos, University of Malaga, 29071, Spain.|Department of Molecular Biology and Biochemistry and unit 741 of CIBER de Enfermedades Raras, Campus de Teatinos, University of Malaga, 29071, Spain.|Department of Molecular Biology and Biochemistry and unit 741 of CIBER de Enfermedades Raras, Campus de Teatinos, University of Malaga, 29071, Spain.|Department of Molecular Biology and Biochemistry and unit 741 of CIBER de Enfermedades Raras, Campus de Teatinos, University of Malaga, 29071, Spain.|Department of Molecular Biology and Biochemistry and unit 741 of CIBER de Enfermedades Raras, Campus de Teatinos, University of Malaga, 29071, Spain.|Department of Molecular Biology and Biochemistry and unit 741 of CIBER de Enfermedades Raras, Campus de Teatinos, University of Malaga, 29071, Spain.|Department of Molecular Biology and Biochemistry and unit 741 of CIBER de Enfermedades Raras, Campus de Teatinos, University of Malaga, 29071, Spain.|Department of Molecular Biology and Biochemistry and unit 741 of CIBER de Enfermedades Raras, Campus de Teatinos, University of Malaga, 29071, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 14, 'Computational Biology|Kinetics|Metabolic Networks and Pathways|Models, Biological|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btp061', '19189977', 'We present Systems Biology Metabolic Modeling Assistant (SBMM Assistant), a tool built using an ontology-based mediator, and designed to facilitate metabolic modeling through the integration of data from repositories that contain valuable metabolic information. This software can be used for the visualization, design and management of metabolic networks, selection, integration and storage of metabolic information, and as an assistant for kinetic modeling.'),
(74612, 2009, 'bio', 'VANO: a volume-object image annotation system', 'Peng, Hanchuan|Long, Fuhui|Myers, Eugene W', 'Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, VA, USA. pengh@janelia.hhmi.org|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, VA, USA. pengh@janelia.hhmi.org|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, VA, USA. pengh@janelia.hhmi.org', 'United States|United States|United States', 25, 'Animals|Caenorhabditis elegans|Databases, Factual|Drosophila|Image Processing, Computer-Assisted|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp046', '19189978', 'Volume-object annotation system (VANO) is a cross-platform image annotation system that enables one to conveniently visualize and annotate 3D volume objects including nuclei and cells. An application of VANO typically starts with an initial collection of objects produced by a segmentation computation. The objects can then be labeled, categorized, deleted, added, split, merged and redefined. VANO has been used to build high-resolution digital atlases of the nuclei of Caenorhabditis elegans at the L1 stage and the nuclei of Drosophila melanogasters ventral nerve cord at the late embryonic stage.'),
(74613, 2009, 'bio', 'Lightweight comparison of RNAs based on exact sequence-structure matches', 'Heyne, Steffen|Will, Sebastian|Beckstette, Michael|Backofen, Rolf', 'Bioinformatics Group, Albert-Ludwigs-University Freiburg, Georges-Koehler-Allee 106, Freiburg, D-79110, Germany.|Bioinformatics Group, Albert-Ludwigs-University Freiburg, Georges-Koehler-Allee 106, Freiburg, D-79110, Germany.|Bioinformatics Group, Albert-Ludwigs-University Freiburg, Georges-Koehler-Allee 106, Freiburg, D-79110, Germany.|Bioinformatics Group, Albert-Ludwigs-University Freiburg, Georges-Koehler-Allee 106, Freiburg, D-79110, Germany.', 'Germany|Germany|Germany|Germany', 24, 'Base Sequence|Computational Biology|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA', 'Comparative Study', '10.1093/bioinformatics/btp065', '19189979', 'Specific functions of ribonucleic acid (RNA) molecules are often associated with different motifs in the RNA structure. The key feature that forms such an RNA motif is the combination of sequence and structure properties. In this article, we introduce a new RNA sequence-structure comparison method which maintains exact matching substructures. Existing common substructures are treated as whole unit while variability is allowed between such structural motifs. Based on a fast detectable set of overlapping and crossing substructure matches for two nested RNA secondary structures, our method ExpaRNA (exact pattern of alignment of RNA) computes the longest collinear sequence of substructures common to two RNAs in O(H.nm) time and O(nm) space, where H < n.m for real RNA structures. Applied to different RNAs, our method correctly identifies sequence-structure similarities between two RNAs.'),
(74614, 2009, 'bio', 'QVALITY: non-parametric estimation of q-values and posterior error probabilities', 'Käll, Lukas|Storey, John D|Noble, William Stafford', 'Department of Biochemistry and Biophysics, Center for Biomembrane Research, Stockholm University, Sweden, USA. lukas.kall@cbr.su.se|Department of Biochemistry and Biophysics, Center for Biomembrane Research, Stockholm University, Sweden, USA. lukas.kall@cbr.su.se|Department of Biochemistry and Biophysics, Center for Biomembrane Research, Stockholm University, Sweden, USA. lukas.kall@cbr.su.se', 'Sweden|Sweden|Sweden', 72, 'Algorithms|Computational Biology|DNA|Oligonucleotide Array Sequence Analysis|Probability|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btp021', '19193729', 'Qvality is a C++ program for estimating two types of standard statistical confidence measures: the q-value, which is an analog of the p-value that incorporates multiple testing correction, and the posterior error probability (PEP, also known as the local false discovery rate), which corresponds to the probability that a given observation is drawn from the null distribution. In computing q-values, qvality employs a standard bootstrap procedure to estimate the prior probability of a score being from the null distribution, for PEP estimation, qvality relies upon non-parametric logistic regression. Relative to other tools for estimating statistical confidence measures, qvality is unique in its ability to estimate both types of scores directly from a null distribution, without requiring the user to calculate p-values.'),
(74615, 2009, 'bio', 'A single-sample method for normalizing and combining full-resolution copy numbers from multiple platforms, labs and analysis methods', 'Bengtsson, Henrik|Ray, Amrita|Spellman, Paul|Speed, Terence P', 'Department of Statistics, Life Sciences Division, University of California, Lawrence Berkeley National Laboratory, Berkeley, USA. hb@stat.berkeley.edu|Department of Statistics, Life Sciences Division, University of California, Lawrence Berkeley National Laboratory, Berkeley, USA. hb@stat.berkeley.edu|Department of Statistics, Life Sciences Division, University of California, Lawrence Berkeley National Laboratory, Berkeley, USA. hb@stat.berkeley.edu|Department of Statistics, Life Sciences Division, University of California, Lawrence Berkeley National Laboratory, Berkeley, USA. hb@stat.berkeley.edu', 'United States|United States|United States|United States', 30, 'Algorithms|Gene Dosage|Genetic Variation|Genome, Human|Genomics|Humans|Neoplasms', 'Journal Article', '10.1093/bioinformatics/btp074', '19193730', 'The rapid expansion of whole-genome copy number (CN) studies brings a demand for increased precision and resolution of CN estimates. Recent studies have obtained CN estimates from more than one platform for the same set of samples, and it is natural to want to combine the different estimates in order to meet this demand. Estimates from different platforms show different degrees of attenuation of the true CN changes. Similar differences can be observed in CNs from the same platform run in different labs, or in the same lab, with different analytical methods. This is the reason why it is not straightforward to combine CN estimates from different sources (platforms, labs and analysis methods).'),
(74616, 2009, 'bio', 'CoCAS: a ChIP-on-chip analysis suite', 'Benoukraf, Touati|Cauchy, Pierre|Fenouil, Romain|Jeanniard, Adrien|Koch, Frederic|Jaeger, Sébastien|Thieffry, Denis|Imbert, Jean|Andrau, Jean-Christophe|Spicuglia, Salvatore|Ferrier, Pierre', 'Centre dImmunologie de Marseille-Luminy, CNRS, UMR6102, Inserm, U631, Université de la Méditerranée and Inserm, U928, TAGC, Marseille, France.|Centre dImmunologie de Marseille-Luminy, CNRS, UMR6102, Inserm, U631, Université de la Méditerranée and Inserm, U928, TAGC, Marseille, France.|Centre dImmunologie de Marseille-Luminy, CNRS, UMR6102, Inserm, U631, Université de la Méditerranée and Inserm, U928, TAGC, Marseille, France.|Centre dImmunologie de Marseille-Luminy, CNRS, UMR6102, Inserm, U631, Université de la Méditerranée and Inserm, U928, TAGC, Marseille, France.|Centre dImmunologie de Marseille-Luminy, CNRS, UMR6102, Inserm, U631, Université de la Méditerranée and Inserm, U928, TAGC, Marseille, France.|Centre dImmunologie de Marseille-Luminy, CNRS, UMR6102, Inserm, U631, Université de la Méditerranée and Inserm, U928, TAGC, Marseille, France.|Centre dImmunologie de Marseille-Luminy, CNRS, UMR6102, Inserm, U631, Université de la Méditerranée and Inserm, U928, TAGC, Marseille, France.|Centre dImmunologie de Marseille-Luminy, CNRS, UMR6102, Inserm, U631, Université de la Méditerranée and Inserm, U928, TAGC, Marseille, France.|Centre dImmunologie de Marseille-Luminy, CNRS, UMR6102, Inserm, U631, Université de la Méditerranée and Inserm, U928, TAGC, Marseille, France.|Centre dImmunologie de Marseille-Luminy, CNRS, UMR6102, Inserm, U631, Université de la Méditerranée and Inserm, U928, TAGC, Marseille, France.|Centre dImmunologie de Marseille-Luminy, CNRS, UMR6102, Inserm, U631, Université de la Méditerranée and Inserm, U928, TAGC, Marseille, France.', 'France|France|France|France|France|France|France|France|France|France|France', 18, 'Chromatin Immunoprecipitation|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btp075', '19193731', 'High-density tiling microarrays are increasingly used in combination with ChIP assays to study transcriptional regulation. To ease the analysis of the large amounts of data generated by this approach, we have developed ChIP-on-chip Analysis Suite (CoCAS), a standalone software suite which implements optimized ChIP-on-chip data normalization, improved peak detection, as well as quality control reports. Our software allows dye swap, replicate correlation and connects easily with genome browsers and other peak detection algorithms. CoCAS can readily be used on the latest generation of Agilent high-density arrays. Also, the implemented peak detection methods are suitable for other datasets, including ChIP-Seq output.'),
(74617, 2009, 'bio', 'Statistical methods of background correction for Illumina BeadArray data', 'Xie, Yang|Wang, Xinlei|Story, Michael', 'Division of Biostatistics, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, USA. yang.xie@utsouthwestern.edu|Division of Biostatistics, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, USA. yang.xie@utsouthwestern.edu|Division of Biostatistics, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, USA. yang.xie@utsouthwestern.edu', 'United States|United States|United States', 49, 'Computational Biology|Gene Expression Profiling|Models, Statistical|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btp040', '19193732', 'Advances in technology have made different microarray platforms available. Among the many, Illumina BeadArrays are relatively new and have captured significant market share. With BeadArray technology, high data quality is generated from low sample input at reduced cost. However, the analysis methods for Illumina BeadArrays are far behind those for Affymetrix oligonucleotide arrays, and so need to be improved.'),
(74618, 2009, 'bio', 'Radié: visualizing taxon properties and parsimonious mappings using a radial phylogenetic tree', 'Whalley, Jacqueline|Brooks, Stephen|Beiko, Robert G', 'School of Computing and Mathematical Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand.|School of Computing and Mathematical Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand.|School of Computing and Mathematical Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand.', 'New Zealand|New Zealand|New Zealand', 0, 'Algorithms|Computational Biology|Evolution, Molecular|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btp044', '19193733', 'A phenotypic character has a convex mapping to a given phylogenetic tree if each character state can be assigned a single point of origin in the tree. However, phenomena such as convergent evolution and lateral genetic transfer can lead to intermingling of character states and a consequent non-convex mapping. The phylogenetic heterogeneity of different characters can identify subsets of states that are non-randomly associated or which may have been transferred from one lineage to another. We have developed Radié, an interactive 3D Java application for mapping character states to the leaves and internal edges of a radial phylogenetic tree. In Radié each state of a given character is associated with a unique color, and internal edges with many descendant character states can be represented in a number of different ways to illustrate the diversity within each group.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(74619, 2009, 'bio', 'Bioinformatics for next generation sequencing', 'Bateman, Alex|Quackenbush, John', 'School of Computing and Mathematical Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand.|School of Computing and Mathematical Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand.', 'New Zealand|New Zealand', 21, 'Genome|Genomics|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA', 'Editorial', '10.1093/bioinformatics/btp037', '19202193', '-'),
(74620, 2009, 'bio', 'FRANz: reconstruction of wild multi-generation pedigrees', 'Riester, Markus|Stadler, Peter F|Klemm, Konstantin', 'Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstrasse 16-18, D-04107 Leipzig, Germany. markus@bioinf.uni-leipzig.de|Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstrasse 16-18, D-04107 Leipzig, Germany. markus@bioinf.uni-leipzig.de|Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstrasse 16-18, D-04107 Leipzig, Germany. markus@bioinf.uni-leipzig.de', 'Germany|Germany|Germany', 56, 'Algorithms|Computational Biology|Markov Chains|Monte Carlo Method|Pedigree|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btp064', '19202194', 'We present a software package for pedigree reconstruction in natural populations using co-dominant genomic markers such as microsatellites and single nucleotide polymorphisms (SNPs). If available, the algorithm makes use of prior information such as known relationships (sub-pedigrees) or the age and sex of individuals. Statistical confidence is estimated by Markov Chain Monte Carlo (MCMC) sampling. The accuracy of the algorithm is demonstrated for simulated data as well as an empirical dataset with known pedigree. The parentage inference is robust even in the presence of genotyping errors.'),
(74621, 2009, 'bio', 'A web-based software system for dynamic gene cluster comparison across multiple genomes', 'Revanna, Kashi Vishwanath|Krishnakumar, Vivek|Dong, Qunfeng', 'Center for Genomics and Bioinformatics, Indiana University, Bloomington, IN 47405, USA.|Center for Genomics and Bioinformatics, Indiana University, Bloomington, IN 47405, USA.|Center for Genomics and Bioinformatics, Indiana University, Bloomington, IN 47405, USA.', 'India|India|India', 0, 'Genome|Internet|Multigene Family|Software', 'Comparative Study', '10.1093/bioinformatics/btp078', '19208612', 'Investigating the conservation of gene clusters across multiple genomes has become a standard practice in the era of comparative genomics. However, all existing software and databases rely heavily on pre-computation to identify homologous genes by genome-wide comparisons. Such pre-computing strategies lack accuracy and updating the data is computationally intensive. Since most molecular biologists are often interested only in a small cluster of genes, catering to this need, we have developed a web-based software system that allows users to upload a list of genes, perform dynamic search against the genomes of their choices and interactively visualize the gene cluster conservation using a novel multi-genome browser. Our approach avoids expensive genome-wide pre-computing and allows users to dynamically change the search criteria to fit their genes of interest. Our system can be customized for any genome sequences. We have applied it to both prokaryotic and eukaryotic genomes to illustrate its usability.'),
(74622, 2009, 'bio', 'STEM: species tree estimation using maximum likelihood for gene trees under coalescence', 'Kubatko, Laura S|Carstens, Bryan C|Knowles, L Lacey', 'Departments of Statistics and Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43210, USA. lkubatko@stat.osu.edu|Departments of Statistics and Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43210, USA. lkubatko@stat.osu.edu|Departments of Statistics and Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43210, USA. lkubatko@stat.osu.edu', 'United States|United States|United States', 318, 'Algorithms|Computer Simulation|Genes|Likelihood Functions|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btp079', '19211573', 'STEM is a software package written in the C language to obtain maximum likelihood (ML) estimates for phylogenetic species trees given a sample of gene trees under the coalescent model. It includes options to compute the ML species tree, search the space of all species trees for the k trees of highest likelihood and compute ML branch lengths for a user-input species tree.'),
(74623, 2009, 'bio', 'A flexible two-stage procedure for identifying gene sets that are differentially expressed', 'Heller, Ruth|Manduchi, Elisabetta|Grant, Gregory R|Ewens, Warren J', 'Department of Statistics, Wharton School, University of Pennsylvania, Philadelphia, PA 19104-6340, USA. ruheller@whatron.upenn.edu|Department of Statistics, Wharton School, University of Pennsylvania, Philadelphia, PA 19104-6340, USA. ruheller@whatron.upenn.edu|Department of Statistics, Wharton School, University of Pennsylvania, Philadelphia, PA 19104-6340, USA. ruheller@whatron.upenn.edu|Department of Statistics, Wharton School, University of Pennsylvania, Philadelphia, PA 19104-6340, USA. ruheller@whatron.upenn.edu', 'United States|United States|United States|United States', 0, 'Computer Simulation|Gene Expression|Gene Expression Profiling|Models, Statistical|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btp076', '19213738', 'Microarray data analysis has expanded from testing individual genes for differential expression to testing gene sets for differential expression. The tests at the gene set level may focus on multivariate expression changes or on the differential expression of at least one gene in the gene set. These tests may be powerful at detecting subtle changes in expression, but findings at the gene set level need to be examined further to understand whether they are informative and if so how.'),
(74624, 2009, 'bio', 'Enumeration of condition-dependent dense modules in protein interaction networks', 'Georgii, Elisabeth|Dietmann, Sabine|Uno, Takeaki|Pagel, Philipp|Tsuda, Koji', 'Max Planck Institute for Biological Cybernetics, Tübingen, Germany.|Max Planck Institute for Biological Cybernetics, Tübingen, Germany.|Max Planck Institute for Biological Cybernetics, Tübingen, Germany.|Max Planck Institute for Biological Cybernetics, Tübingen, Germany.|Max Planck Institute for Biological Cybernetics, Tübingen, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Computational Biology|Humans|Multiprotein Complexes|Phenotype|Protein Interaction Mapping|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btp080', '19213739', 'Modern systems biology aims at understanding how the different molecular components of a biological cell interact. Often, cellular functions are performed by complexes consisting of many different proteins. The composition of these complexes may change according to the cellular environment, and one protein may be involved in several different processes. The automatic discovery of functional complexes from protein interaction data is challenging. While previous approaches use approximations to extract dense modules, our approach exactly solves the problem of dense module enumeration. Furthermore, constraints from additional information sources such as gene expression and phenotype data can be integrated, so we can systematically mine for dense modules with interesting profiles.'),
(74625, 2009, 'bio', 'Simulation of large-scale rule-based models', 'Colvin, Joshua|Monine, Michael I|Faeder, James R|Hlavacek, William S|Von Hoff, Daniel D|Posner, Richard G', 'Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA. dynstoc@tgen.org|Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA. dynstoc@tgen.org|Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA. dynstoc@tgen.org|Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA. dynstoc@tgen.org|Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA. dynstoc@tgen.org|Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA. dynstoc@tgen.org', 'United States|United States|United States|United States|United States|United States', 45, 'Algorithms|Binding Sites|Computer Simulation|Internet|Models, Biological|Protein Interaction Mapping|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btp066', '19213740', 'Interactions of molecules, such as signaling proteins, with multiple binding sites and/or multiple sites of post-translational covalent modification can be modeled using reaction rules. Rules comprehensively, but implicitly, define the individual chemical species and reactions that molecular interactions can potentially generate. Although rules can be automatically processed to define a biochemical reaction network, the network implied by a set of rules is often too large to generate completely or to simulate using conventional procedures. To address this problem, we present DYNSTOC, a general-purpose tool for simulating rule-based models.'),
(74626, 2009, 'bio', 'Allergen Atlas: a comprehensive knowledge center and analysis resource for allergen information', 'Tong, Joo Chuan|Lim, Shen Jean|Muh, Hon Cheng|Chew, Fook Tim|Tammi, Martti T', 'Data Mining Department, Institute for Infocomm Research, South Tower, Singapore.|Data Mining Department, Institute for Infocomm Research, South Tower, Singapore.|Data Mining Department, Institute for Infocomm Research, South Tower, Singapore.|Data Mining Department, Institute for Infocomm Research, South Tower, Singapore.|Data Mining Department, Institute for Infocomm Research, South Tower, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore', 0, 'Allergens|Computational Biology|Databases, Protein|Information Storage and Retrieval|Internet|Proteins', 'Journal Article', '10.1093/bioinformatics/btp077', '19213741', 'A variety of specialist databases have been developed to facilitate the study of allergens. However, these databases either contain different subsets of allergen data or are deficient in tools for assessing potential allergenicity of proteins. Here, we describe Allergen Atlas, a comprehensive repository of experimentally validated allergen sequences collected from in-house laboratory, online data submission, literature reports and all existing general-purpose and specialist databases. Each entry was manually verified, classified and hyperlinked to major databases including Swiss-Prot, Protein Data Bank (PDB), Gene Ontology (GO), Pfam and PubMed. The database is integrated with analysis tools that include: (i) keyword search, (ii) BLAST, (iii) position-specific iterative BLAST (PSI-BLAST), (iv) FAO/WHO criteria search, (v) graphical representation of allergen information network and (vi) online data submission. The latest version contains information of 1593 allergen sequences (496 IUIS allergens, 978 experimentally verified allergens and 119 new sequences), 56 IgE epitope sequences, 679 links to PDB structures and 155 links to Pfam domains.'),
(74627, 2009, 'bio', 'PASS: a program to align short sequences', 'Campagna, Davide|Albiero, Alessandro|Bilardi, Alessandra|Caniato, Elisa|Forcato, Claudio|Manavski, Svetlin|Vitulo, Nicola|Valle, Giorgio', 'CRIBI Biotechnology Centre, University of Padua, Padova, Italy.|CRIBI Biotechnology Centre, University of Padua, Padova, Italy.|CRIBI Biotechnology Centre, University of Padua, Padova, Italy.|CRIBI Biotechnology Centre, University of Padua, Padova, Italy.|CRIBI Biotechnology Centre, University of Padua, Padova, Italy.|CRIBI Biotechnology Centre, University of Padua, Padova, Italy.|CRIBI Biotechnology Centre, University of Padua, Padova, Italy.|CRIBI Biotechnology Centre, University of Padua, Padova, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Internet|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btp087', '19218350', 'Standard DNA alignment programs are inadequate to manage the data produced by new generation DNA sequencers. To answer this problem, we developed PASS with the objective of improving execution time and sensitivity when compared with other available programs. PASS performs fast gapped and ungapped alignments of short DNA sequences onto a reference DNA, typically a genomic sequence. It is designed to handle a huge amount of reads such as those generated by Solexa, SOLiD or 454 technologies. The algorithm is based on a data structure that holds in RAM the index of the genomic positions of seed words (typically 11 and 12 bases) as well as an index of the precomputed scores of short words (typically seven and eight bases) aligned against each other. After building the genomic index, the program scans every query sequence performing three steps: (1) it finds matching seed words in the genome, (2) for every match checks the precomputed alignment of the short flanking regions, (3) if passes step 2, then it performs an exact dynamic alignment of a narrow region around the match. The performance of the program is very striking both for sensitivity and speed. For instance, gap alignment is achieved hundreds of times faster than BLAST and several times faster than SOAP, especially when gaps are allowed. Furthermore, PASS has a higher sensitivity when compared with the other available programs.'),
(74628, 2009, 'bio', 'Gene network reconstruction from transcriptional dynamics under kinetic model uncertainty: a case for the second derivative', 'Bickel, David R|Montazeri, Zahra|Hsieh, Pei-Chun|Beatty, Mary|Lawit, Shai J|Bate, Nicholas J', 'Ottawa Institute of Systems Biology, Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, 451 Smyth Road, Ottawa, Ontario, ON K1H 8M5, Canada. dbickel@uottawa.ca|Ottawa Institute of Systems Biology, Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, 451 Smyth Road, Ottawa, Ontario, ON K1H 8M5, Canada. dbickel@uottawa.ca|Ottawa Institute of Systems Biology, Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, 451 Smyth Road, Ottawa, Ontario, ON K1H 8M5, Canada. dbickel@uottawa.ca|Ottawa Institute of Systems Biology, Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, 451 Smyth Road, Ottawa, Ontario, ON K1H 8M5, Canada. dbickel@uottawa.ca|Ottawa Institute of Systems Biology, Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, 451 Smyth Road, Ottawa, Ontario, ON K1H 8M5, Canada. dbickel@uottawa.ca|Ottawa Institute of Systems Biology, Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, 451 Smyth Road, Ottawa, Ontario, ON K1H 8M5, Canada. dbickel@uottawa.ca', 'Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Bayes Theorem|Gene Regulatory Networks|Kinetics|Models, Genetic|Oligonucleotide Array Sequence Analysis|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btp028', '19218351', 'Measurements of gene expression over time enable the reconstruction of transcriptional networks. However, Bayesian networks and many other current reconstruction methods rely on assumptions that conflict with the differential equations that describe transcriptional kinetics. Practical approximations of kinetic models would enable inferring causal relationships between genes from expression data of microarray, tag-based and conventional platforms, but conclusions are sensitive to the assumptions made.'),
(74629, 2009, 'bio', 'CGAS: comparative genomic analysis server', 'Itoh, Masumi|Watanabe, Hidemi', 'Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Hokkaido, Japan.|Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Hokkaido, Japan.', 'Japan|Japan', 0, 'Comparative Genomic Hybridization|Genome|Genomics|Internet|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btp086', '19218352', 'Comparative approach is one of the most essential methods for extracting functional and evolutionary information from genomic sequences. So far, a number of sequence comparison tools have been developed, and most are either for on-site use, requiring program installation but providing a wide variety of analyses, or for the online search of users sequences against given databases on a server. We newly devised an Asynchronous JavaScript and XML (Ajax)-based system for comparative genomic analyses, CGAS, with highly interactive interface within a browser, requiring no software installation. The current version, CGAS version 1, provides functionality for viewing similarity relationships between users sequences, including a multiple dot plot between sequences with their annotation information. The scrollbar-less draggable interface of CGAS is implemented with Google Maps API version 2. The annotation information associated with the genomic sequences compared is synchronously displayed with the comparison view. The multiple-comparison viewer is one of the unique functionalities of this system to allow the users to compare the differences between different pairs of sequences. In this viewer, the system tells orthologous correspondences between the sequences compared interactively. This web-based tool is platform-independent and will provide biologists having no computational skills with opportunities to analyze their own data without software installation and customization of the computer system.'),
(74630, 2009, 'bio', 'Determination of sample size in genome-scale RNAi screens', 'Zhang, Xiaohua Douglas|Heyse, Joseph F', 'Biometrics Research and BARDS, Merck Research Laboratories, West Point, PA 19486, USA. Xiaohua_zhang@merck.com|Biometrics Research and BARDS, Merck Research Laboratories, West Point, PA 19486, USA. Xiaohua_zhang@merck.com', 'United States|United States', 0, 'Animals|Computational Biology|Gene Expression Profiling|Genome|Humans|RNA Interference|RNA, Small Interfering|Sample Size', 'Journal Article', '10.1093/bioinformatics/btp082', '19223447', 'For genome-scale RNAi research, it is critical to investigate sample size required for the achievement of reasonably low false negative rate (FNR) and false positive rate.'),
(74631, 2009, 'bio', 'M are better than one: an ensemble-based motif finder and its application to regulatory element prediction', 'Yanover, Chen|Singh, Mona|Zaslavsky, Elena', 'Fred Hutchinson Cancer Research Center, Seattle, WA, USA. cyanover@fhcrc.org|Fred Hutchinson Cancer Research Center, Seattle, WA, USA. cyanover@fhcrc.org|Fred Hutchinson Cancer Research Center, Seattle, WA, USA. cyanover@fhcrc.org', 'United States|United States|United States', 16, 'Algorithms|Binding Sites|Genomics|Regulatory Elements, Transcriptional|Regulatory Sequences, Nucleic Acid|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btp090', '19223448', 'Identifying regulatory elements in genomic sequences is a key component in understanding the control of gene expression. Computationally, this problem is often addressed by motif discovery, where the goal is to find a set of mutually similar subsequences within a collection of input sequences. Though motif discovery is widely studied and many approaches to it have been suggested, it remains a challenging and as yet unresolved problem.'),
(74632, 2009, 'bio', 'OnTheFly: a tool for automated document-based text annotation, data linking and network generation', 'Pavlopoulos, Georgios A|Pafilis, Evangelos|Kuhn, M|Hooper, Sean D|Schneider, Reinhard', 'Structural and Computational Biology Unit, EMBL Meyerhofstrasse 1, Heidelberg, . pavlopou@embl.de|Structural and Computational Biology Unit, EMBL Meyerhofstrasse 1, Heidelberg, . pavlopou@embl.de|Structural and Computational Biology Unit, EMBL Meyerhofstrasse 1, Heidelberg, . pavlopou@embl.de|Structural and Computational Biology Unit, EMBL Meyerhofstrasse 1, Heidelberg, . pavlopou@embl.de|Structural and Computational Biology Unit, EMBL Meyerhofstrasse 1, Heidelberg, . pavlopou@embl.de', '-|-|-|-|-', 0, 'Database Management Systems|Databases, Factual|Information Storage and Retrieval|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp081', '19223449', 'OnTheFly is a web-based application that applies biological named entity recognition to enrich Microsoft Office, PDF and plain text documents. The input files are converted into the HTML format and then sent to the Reflect tagging server, which highlights biological entity names like genes, proteins and chemicals, and attaches to them JavaScript code to invoke a summary pop-up window. The window provides an overview of relevant information about the entity, such as a protein description, the domain composition, a link to the 3D structure and links to other relevant online resources. OnTheFly is also able to extract the bioentities mentioned in a set of files and to produce a graphical representation of the networks of the known and predicted associations of these entities by retrieving the information from the STITCH database.'),
(74633, 2009, 'bio', 'RAMI: a tool for identification and characterization of phylogenetic clusters in microbial communities', 'Pommier, Thomas|Canbäck, Björn|Lundberg, Per|Hagström, Ake|Tunlid, Anders', 'Department of Natural Science, Kalmar University, Kalmar, Sweden. tpommier@univ-montp2.fr|Department of Natural Science, Kalmar University, Kalmar, Sweden. tpommier@univ-montp2.fr|Department of Natural Science, Kalmar University, Kalmar, Sweden. tpommier@univ-montp2.fr|Department of Natural Science, Kalmar University, Kalmar, Sweden. tpommier@univ-montp2.fr|Department of Natural Science, Kalmar University, Kalmar, Sweden. tpommier@univ-montp2.fr', 'Sweden|Sweden|Sweden|Sweden|Sweden', 35, 'Bacteria|DNA, Bacterial|DNA, Ribosomal|Internet|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btp051', '19223450', 'The most common approach to estimate microbial diversity is based on the analysis of DNA sequences of specific target genes including ribosomal genes. Commonly, the sequences are grouped into operational taxonomic units based on genetic distance (sequence similarity) instead of genetic change (patristic distance). This method may fail to adequately identify clusters of evolutionary related sequences and it provides no information on the phylogenetic structure of the community. An ease-of-use web application for this purpose has been missing.'),
(74634, 2009, 'bio', 'Homogeneous decomposition of protein interaction networks: refining the description of intra-modular interactions', 'Del Mondo, Géraldine|Eveillard, Damien|Rusu, Irena', 'Computational Biology Group- LINA, Université de Nantes, CNRS UMR 6241, Nantes, France.|Computational Biology Group- LINA, Université de Nantes, CNRS UMR 6241, Nantes, France.|Computational Biology Group- LINA, Université de Nantes, CNRS UMR 6241, Nantes, France.', 'France|France|France', 0, 'Algorithms|Computational Biology|Databases, Protein|Multiprotein Complexes|Protein Interaction Mapping|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1093/bioinformatics/btp083', '19223451', 'Modules in biology appeared quickly as an accurate way for summarizing complex living systems by simple ones. Therefore, finding an appropriate relationship between modules extracted from a biological graph and protein complexes remains a crucial task. Recent studies successfully proposed various descriptions of protein interaction networks. These approaches succeed in showing modules within the network and how the modules interact. However, describing the interactions within the modules, i.e. intra-modular interactions, remains little analyzed despite its interest for understanding module functions.'),
(74635, 2009, 'bio', 'Identification of differential gene pathways with principal component analysis', 'Ma, Shuangge|Kosorok, Michael R', 'Department of Epidemiology and Public Health, Yale University, New Haven, CT 06510, USA. shuangge.ma@yale.edu|Department of Epidemiology and Public Health, Yale University, New Haven, CT 06510, USA. shuangge.ma@yale.edu', 'United States|United States', 51, 'Computational Biology|Databases, Genetic|Gene Expression Profiling|Phenotype|Principal Component Analysis', 'Journal Article', '10.1093/bioinformatics/btp085', '19223452', 'Development of high-throughput technology makes it possible to measure expressions of thousands of genes simultaneously. Genes have the inherent pathway structure, where pathways are composed of multiple genes with coordinated biological functions. It is of great interest to identify differential gene pathways that are associated with the variations of phenotypes.'),
(74636, 2009, 'bio', 'A new ensemble-based algorithm for identifying breath gas marker candidates in liver disease using ion molecule reaction mass spectrometry', 'Netzer, M|Millonig, G|Osl, M|Pfeifer, B|Praun, S|Villinger, J|Vogel, W|Baumgartner, C', 'Research Group for Clinical Bioinformatics, Institute of Biomedical Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Innsbruck Medical University, Innsbruck, Austria. michalel.netzer@umit.at|Research Group for Clinical Bioinformatics, Institute of Biomedical Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Innsbruck Medical University, Innsbruck, Austria. michalel.netzer@umit.at|Research Group for Clinical Bioinformatics, Institute of Biomedical Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Innsbruck Medical University, Innsbruck, Austria. michalel.netzer@umit.at|Research Group for Clinical Bioinformatics, Institute of Biomedical Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Innsbruck Medical University, Innsbruck, Austria. michalel.netzer@umit.at|Research Group for Clinical Bioinformatics, Institute of Biomedical Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Innsbruck Medical University, Innsbruck, Austria. michalel.netzer@umit.at|Research Group for Clinical Bioinformatics, Institute of Biomedical Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Innsbruck Medical University, Innsbruck, Austria. michalel.netzer@umit.at|Research Group for Clinical Bioinformatics, Institute of Biomedical Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Innsbruck Medical University, Innsbruck, Austria. michalel.netzer@umit.at|Research Group for Clinical Bioinformatics, Institute of Biomedical Engineering, University for Health Sciences, Medical Informatics and Technology (UMIT), Innsbruck Medical University, Innsbruck, Austria. michalel.netzer@umit.at', 'Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria', 64, 'Algorithms|Biomarkers|Breath Tests|Cohort Studies|Humans|Liver Diseases|Mass Spectrometry|Middle Aged', 'Journal Article', '10.1093/bioinformatics/btp093', '19223453', 'Alcoholic fatty liver disease (AFLD) and non-AFLD (NAFLD) can progress to severe liver diseases such as steatohepatitis, cirrhosis and cancer. Thus, the detection of early liver disease is essential, however, minimal invasive diagnostic methods in clinical hepatology still lack specificity.'),
(74637, 2009, 'bio', 'gcExplorer: interactive exploration of gene clusters', 'Scharl, Theresa|Leisch, Friedrich', 'Department of Biotechnology, Universität für Bodenkultur, Vienna, Austria. theresa.scharl@ci.tuwien.ac.at|Department of Biotechnology, Universität für Bodenkultur, Vienna, Austria. theresa.scharl@ci.tuwien.ac.at', 'Austria|Austria', 0, 'Algorithms|Computational Biology|Gene Expression Profiling|Multigene Family|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp099', '19225024', 'Cluster analysis plays an important role in the analysis of gene expression data since the early beginning of microarray studies and is routinely used to find groups of genes with common expression pattern. In order to make cluster analysis helpful for users, visualization of cluster solutions is of utmost importance. Here, we present the new R package gcExplorer for the interactive exploration of gene clusters. gcExplorer facilitates the interpretation of cluster results and allows to investigate extensive information about clusters.'),
(74638, 2009, 'bio', 'Ultrasome: efficient aberration caller for copy number studies of ultra-high resolution', 'Nilsson, Björn|Johansson, Mikael|Al-Shahrour, Fatima|Carpenter, Anne E|Ebert, Benjamin L', 'Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. bnilsson@broad.mit.edu|Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. bnilsson@broad.mit.edu|Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. bnilsson@broad.mit.edu|Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. bnilsson@broad.mit.edu|Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. bnilsson@broad.mit.edu', 'United States|United States|United States|United States|United States', 13, 'Algorithms|Chromosome Aberrations|Computational Biology|Gene Dosage|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btp091', '19228802', 'Multimillion-probe microarrays allow detection of gains and losses of chromosomal material at unprecedented resolution. However, the data generated by these arrays are several-fold larger than data from earlier platforms, creating a need for efficient analysis tools that scale robustly with data size.'),
(74639, 2009, 'bio', 'An integrative scoring system for ranking SNPs by their potential deleterious effects', 'Lee, Phil Hyoun|Shatkay, Hagit', 'Computational Biology and Machine Learning Lab, School of Computing, Queens University, Kingston, ON, Canada. lee@cs.queensu.ca|Computational Biology and Machine Learning Lab, School of Computing, Queens University, Kingston, ON, Canada. lee@cs.queensu.ca', 'Canada|Canada', 77, 'Computational Biology|Genome, Human|Humans|Polymorphism, Single Nucleotide', 'Comparative Study', '10.1093/bioinformatics/btp103', '19228803', 'Identifying single nucleotide polymorphisms (SNPs) that underlie common and complex human diseases, such as cancer, is of major interest in current molecular epidemiology. Nevertheless, the tremendous number of SNPs on the human genome requires computational methods for prioritizing SNPs according to their potentially deleterious effects to human health, and as such, for expediting genotyping and analysis. As of yet, little has been done to quantitatively assess the possible deleterious effects of SNPs for effective association studies.'),
(74640, 2009, 'bio', 'MOM: maximum oligonucleotide mapping', 'Eaves, Hugh L|Gao, Yuan', 'Department of Computer Science, Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, USA. hleaves@vcu.edu|Department of Computer Science, Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, USA. hleaves@vcu.edu', 'United States|United States', 29, 'Algorithms|Base Sequence|Molecular Sequence Data|Oligonucleotides|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btp092', '19228804', 'Current short read mapping programs are based on the reasonable premise that most sequencing errors occur near the 3() end of the read. These programs map reads with either a small number of mismatches in the entire read, or a small number of mismatches in the segment remaining after trimming bases from the 3() end or a single base from the 5() end. Though multiple sequencing errors most likely occur near the 3() end of the reads, they can still occur at the 5() end of the reads. Trimming from the 3() end will not be able to map these reads. We have developed a program, Maximum Oligonucleotide Mapping (MOM), based on the concept of query matching that is designed to capture a maximal length match within the short read satisfying the user defined error parameters. This query matching approach thus accommodates multiple sequencing errors at both ends. We demonstrate that this technique achieves greater sensitivity and a higher percentage of uniquely mapped reads when compared to existing programs such as SOAP, MAQ and SHRiMP. Software and Test Data'),
(74641, 2009, 'bio', 'INTEGRALL: a database and search engine for integrons, integrases and gene cassettes', 'Moura, Alexandra|Soares, Mário|Pereira, Carolina|Leitão, Nuno|Henriques, Isabel|Correia, António', 'CESAM & Department of Biology, University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal. amoura@ua.pt|CESAM & Department of Biology, University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal. amoura@ua.pt|CESAM & Department of Biology, University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal. amoura@ua.pt|CESAM & Department of Biology, University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal. amoura@ua.pt|CESAM & Department of Biology, University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal. amoura@ua.pt|CESAM & Department of Biology, University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal. amoura@ua.pt', 'Portugal|Portugal|Portugal|Portugal|Portugal|Portugal', 225, 'Base Sequence|Computational Biology|DNA Transposable Elements|Databases, Genetic|Integrases|Integrons|Internet', 'Journal Article', '10.1093/bioinformatics/btp105', '19228805', 'INTEGRALL is a freely available, text-based search system developed with the aim of collecting and organizing information on integrons in a single database. The current release (1.2) contains more than 4800 integron sequences and provides a public genetic repository for sequence data and nomenclature, offering scientists an easy and interactive access to integrons DNA sequences, their molecular arrangements as well as their genetic contexts.'),
(74642, 2009, 'bio', 'microPred: effective classification of pre-miRNAs for human miRNA gene prediction', 'Batuwita, Rukshan|Palade, Vasile', 'Oxford University Computing Laboratory, University of Oxford, Wolfson Building, Oxford, UK. manb@comlab.ox.ac.uk|Oxford University Computing Laboratory, University of Oxford, Wolfson Building, Oxford, UK. manb@comlab.ox.ac.uk', 'United Kingdom|United Kingdom', 187, 'Animals|Base Sequence|Computational Biology|Databases, Genetic|Humans|MicroRNAs|Molecular Sequence Data|Nucleic Acid Conformation|RNA Precursors|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btp107', '19233894', 'In this article, we show that the classification of human precursor microRNA (pre-miRNAs) hairpins from both genome pseudo hairpins and other non-coding RNAs (ncRNAs) is a common and essential requirement for both comparative and non-comparative computational recognition of human miRNA genes. However, the existing computational methods do not address this issue completely or successfully. Here we present the development of an effective classifier system (named as microPred) for this classification problem by using appropriate machine learning techniques. Our approach includes the introduction of more representative datasets, extraction of new biologically relevant features, feature selection, handling of class imbalance problem in the datasets and extensive classifier performance evaluation via systematic cross-validation methods.'),
(74643, 2009, 'bio', 'Supervised feature selection in mass spectrometry-based proteomic profiling by blockwise boosting', 'Gertheiss, Jan|Tutz, Gerhard', 'Department of Statistics, Ludwig-Maximilians-Universität, Munich, Germany. jan.gertheiss@stat.uni-muenchen.de|Department of Statistics, Ludwig-Maximilians-Universität, Munich, Germany. jan.gertheiss@stat.uni-muenchen.de', 'Germany|Germany', 9, 'Algorithms|Computational Biology|Databases, Genetic|Mass Spectrometry|Proteome|Proteomics', 'Journal Article', '10.1093/bioinformatics/btp094', '19233895', 'When feature selection in mass spectrometry is based on single m/z values, problems arise from the fact that variability is not only in vertical but also in horizontal direction, i.e. also slightly differing m/z values may correspond to the same feature. Hence, we propose to use the full spectra as input to a classifier, but to select small groups -- or blocks -- of adjacent m/z values, instead of single m/z values only. For that purpose we modify the LogitBoost to obtain a version of the so-called blockwise boosting procedure for classification. It is shown that blockwise boosting has high potential in predictive proteomics.'),
(74644, 2009, 'bio', 'Seevolution: visualizing chromosome evolution', 'Esteban-Marcos, Andrés|Darling, Aaron E|Ragan, Mark A', 'Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia.|Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia.|Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia.', 'Australia|Australia|Australia', 5, 'Chromosomes|Computational Biology|Computer Graphics|Evolution, Molecular|Genome|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp096', '19233896', 'Genome evolution underpins all of biology, yet its principles can be difficult to communicate to the non-specialist. To facilitate broader understanding of genome evolution, we have designed an interactive 3D environment that enables visualization of diverse genome evolution processes. The system can intuitively and interactively animate mutation histories involving genome rearrangement, point mutation, recombination, insertion and deletion. Multiple organisms related by a phylogeny can be visualized simultaneously. As methods to infer evolutionary histories of genomes become increasingly complex, visualization of the evolutionary process will not only be useful for communication, but will also serve as an exploratory tool for discovering new patterns of genome evolution.'),
(74645, 2009, 'bio', 'Array-based genotyping in Scerevisiae using semi-supervised clustering', 'Bourgon, Richard|Mancera, Eugenio|Brozzi, Alessandro|Steinmetz, Lars M|Huber, Wolfgang', 'EMBL, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. bourgon@ebi.ac.uk|EMBL, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. bourgon@ebi.ac.uk|EMBL, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. bourgon@ebi.ac.uk|EMBL, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. bourgon@ebi.ac.uk|EMBL, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. bourgon@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 5, 'Algorithms|Cluster Analysis|Computational Biology|Genome, Fungal|Genotype|Models, Genetic|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btp104', '19237444', 'Microarrays provide an accurate and cost-effective method for genotyping large numbers of individuals at high resolution. The resulting data permit the identification of loci at which genetic variation is associated with quantitative traits, or fine mapping of meiotic recombination, which is a key determinant of genetic diversity among individuals. Several issues inherent to short oligonucleotide arrays -- cross-hybridization, or variability in probe response to target -- have the potential to produce genotyping errors. There is a need for improved statistical methods for array-based genotyping.'),
(74646, 2009, 'bio', 'The ruggedness of protein-protein energy landscape and the cutoff for 1/r(n) potentials', 'Ruvinsky, Anatoly M|Vakser, Ilya A', 'Center for Bioinformatics, The University of Kansas, Lawrence, KS 66047, USA.|Center for Bioinformatics, The University of Kansas, Lawrence, KS 66047, USA.', 'United States|United States', 2, 'Algorithms|Binding Sites|Computational Biology|Kinetics|Multiprotein Complexes|Protein Conformation|Protein Folding|Protein Interaction Mapping|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btp108', '19237445', 'Computational studies of the energetics of protein association are important for revealing the underlying fundamental principles and for designing better tools to model protein complexes. The interaction cutoff contribution to the ruggedness of protein-protein energy landscape is studied in terms of relative energy fluctuations for 1/r(n) potentials based on a simplistic model of a protein complex. This artificial ruggedness exists for short cutoffs and gradually disappears with the cutoff increase.'),
(74647, 2009, 'bio', 'A neural network model for constructing endophenotypes of common complex diseases: an application to male young-onset hypertension microarray data', 'Lynn, Ke-Shiuan|Li, Li-Lan|Lin, Yen-Ju|Wang, Chiuen-Huei|Sheng, Shu-Hui|Lin, Ju-Hwa|Liao, Wayne|Hsu, Wen-Lian|Pan, Wen-Harn', 'Institute of Information Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Information Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Information Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Information Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Information Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Information Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Information Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Information Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Information Sciences, Academia Sinica, Taipei, Taiwan.', '-|-|-|-|-|-|-|-|-', 19, 'Age of Onset|Computer Simulation|Humans|Hypertension|Male|Neural Networks (Computer)|Oligonucleotide Array Sequence Analysis|Phenotype', 'Journal Article', '10.1093/bioinformatics/btp106', '19237446', 'Identification of disease-related genes using high-throughput microarray data is more difficult for complex diseases as compared with monogenic ones. We hypothesized that an endophenotype derived from transcriptional data is associated with a set of genes corresponding to a pathway cluster. We assumed that a complex disease is associated with multiple endophenotypes and can be induced by their up/downregulated gene expression patterns. Thus, a neural network model was adopted to simulate the gene-endophenotype-disease relationship in which endophenotypes were represented by hidden nodes.'),
(74648, 2009, 'bio', 'ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks', 'Bindea, Gabriela|Mlecnik, Bernhard|Hackl, Hubert|Charoentong, Pornpimol|Tosolini, Marie|Kirilovsky, Amos|Fridman, Wolf-Herman|Pagès, Franck|Trajanoski, Zlatko|Galon, Jérôme', 'INSERM, AVENIR Team, Integrative Cancer Immunology, U872, Paris, France.|INSERM, AVENIR Team, Integrative Cancer Immunology, U872, Paris, France.|INSERM, AVENIR Team, Integrative Cancer Immunology, U872, Paris, France.|INSERM, AVENIR Team, Integrative Cancer Immunology, U872, Paris, France.|INSERM, AVENIR Team, Integrative Cancer Immunology, U872, Paris, France.|INSERM, AVENIR Team, Integrative Cancer Immunology, U872, Paris, France.|INSERM, AVENIR Team, Integrative Cancer Immunology, U872, Paris, France.|INSERM, AVENIR Team, Integrative Cancer Immunology, U872, Paris, France.|INSERM, AVENIR Team, Integrative Cancer Immunology, U872, Paris, France.|INSERM, AVENIR Team, Integrative Cancer Immunology, U872, Paris, France.', 'France|France|France|France|France|France|France|France|France|France', 2173, 'Computational Biology|Databases, Genetic|Gene Regulatory Networks|Models, Biological|Multigene Family|Software', 'Journal Article', '10.1093/bioinformatics/btp101', '19237447', 'We have developed ClueGO, an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes. ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta pathways and creates a functionally organized GO/pathway term network. It can analyze one or compare two lists of genes and comprehensively visualizes functionally grouped terms. A one-click update option allows ClueGO to automatically download the most recent GO/KEGG release at any time. ClueGO provides an intuitive representation of the analysis results and can be optionally used in conjunction with the GOlorize plug-in.'),
(74649, 2009, 'bio', 'PAnnBuilder: an R package for assembling proteomic annotation data', 'Li, Hong|Ding, Guohui|Xie, Lu|Li, Yixue', 'Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, PR China.|Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, PR China.|Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, PR China.|Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, PR China.', 'China|China|China|China', 4, 'Animals|Computational Biology|Databases, Protein|Humans|Mice|Programming Languages|Proteome|Proteomics|Rats|Software', 'Journal Article', '10.1093/bioinformatics/btp100', '19237448', 'PAnnBuilder is an R package to automatically assemble protein annotation information from public resources to provide uniform annotation data for large-scale proteomic studies. Sixteen public databases have been parsed and 54 annotation packages have been constructed based on R environment or SQLite database. These ready-to-use packages cover most frequently needed protein annotation for three model species including human, mouse and rat. Several extended applications such as annotation based on protein sequence similarity are also provided. Sophisticated users can develop their own packages using PAnnBuilder. PAnnBuilder may become an important tool for proteomic research.'),
(74650, 2009, 'bio', 'iMembrane: homology-based membrane-insertion of proteins', 'Kelm, Sebastian|Shi, Jiye|Deane, Charlotte M', 'Department of Statistics, University of Oxford, Oxford, UK. kelm@stats.ox.ac.uk|Department of Statistics, University of Oxford, Oxford, UK. kelm@stats.ox.ac.uk|Department of Statistics, University of Oxford, Oxford, UK. kelm@stats.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 23, 'Algorithms|Computational Biology|Databases, Protein|Lipid Bilayers|Membrane Proteins|Models, Molecular|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1093/bioinformatics/btp102', '19237449', 'iMembrane is a homology-based method, which predicts a membrane proteins position within a lipid bilayer. It projects the results of coarse-grained molecular dynamics simulations onto any membrane protein structure or sequence provided by the user. iMembrane is simple to use and is currently the only computational method allowing the rapid prediction of a membrane proteins lipid bilayer insertion. Bilayer insertion data are essential in the accurate structural modelling of membrane proteins or the design of drugs that target them.'),
(74651, 2009, 'bio', 'PLATINUM: a web tool for analysis of hydrophobic/hydrophilic organization of biomolecular complexes', 'Pyrkov, Timothy V|Chugunov, Anton O|Krylov, Nikolay A|Nolde, Dmitry E|Efremov, Roman G', 'M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Ul. Miklukho-Maklaya, 16/10, 117997 GSP, Moscow V-437, Russia. pyrkov@nmr.ru|M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Ul. Miklukho-Maklaya, 16/10, 117997 GSP, Moscow V-437, Russia. pyrkov@nmr.ru|M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Ul. Miklukho-Maklaya, 16/10, 117997 GSP, Moscow V-437, Russia. pyrkov@nmr.ru|M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Ul. Miklukho-Maklaya, 16/10, 117997 GSP, Moscow V-437, Russia. pyrkov@nmr.ru|M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Ul. Miklukho-Maklaya, 16/10, 117997 GSP, Moscow V-437, Russia. pyrkov@nmr.ru', '-|-|-|-|-', 115, 'Binding Sites|Databases, Protein|Hydrophobic and Hydrophilic Interactions|Internet|Ligands|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btp111', '19244385', 'The PLATINUM (Protein-Ligand ATtractions Investigation NUMerically) web service is designed for analysis and visualization of hydrophobic/hydrophilic properties of biomolecules supplied as 3D-structures. Furthermore, PLATINUM provides a number of tools for quantitative characterization of the hydrophobic/hydrophilic match in biomolecular complexes e.g. in docking poses. These complement standard scoring functions. The calculations are based on the concept of empirical Molecular Hydrophobicity Potential (MHP).');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(74652, 2009, 'bio', 'BISEN: Biochemical Simulation Environment', 'Vanlier, J|Wu, F|Qi, F|Vinnakota, K C|Han, Y|Dash, R K|Yang, F|Beard, D A', 'BioModeling and Bioinformatics, BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.|BioModeling and Bioinformatics, BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.|BioModeling and Bioinformatics, BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.|BioModeling and Bioinformatics, BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.|BioModeling and Bioinformatics, BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.|BioModeling and Bioinformatics, BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.|BioModeling and Bioinformatics, BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.|BioModeling and Bioinformatics, BioMedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 12, 'Algorithms|Biochemical Phenomena|Computational Biology|Software', 'Journal Article', '10.1093/bioinformatics/btp069', '19244386', 'The Biochemical Simulation Environment (BISEN) is a suite of tools for generating equations and associated computer programs for simulating biochemical systems in the MATLAB computing environment. This is the first package that can generate appropriate systems of differential equations for user-specified multi-compartment systems of enzymes and transporters accounting for detailed biochemical thermodynamics, rapid equilibria of multiple biochemical species and dynamic proton and metal ion buffering.'),
(74653, 2009, 'bio', 'Statistical inferences for isoform expression in RNA-Seq', 'Jiang, Hui|Wong, Wing Hung', 'Institute for Computational and Mathematical Engineering and Department of Statistics, Stanford University, Stanford, CA 94305, USA.|Institute for Computational and Mathematical Engineering and Department of Statistics, Stanford University, Stanford, CA 94305, USA.', 'United States|United States', 323, 'Bayes Theorem|Computational Biology|Gene Expression Profiling|Protein Isoforms|RNA|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btp113', '19244387', 'The development of RNA sequencing (RNA-Seq) makes it possible for us to measure transcription at an unprecedented precision and throughput. However, challenges remain in understanding the source and distribution of the reads, modeling the transcript abundance and developing efficient computational methods. In this article, we develop a method to deal with the isoform expression estimation problem. The count of reads falling into a locus on the genome annotated with multiple isoforms is modeled as a Poisson variable. The expression of each individual isoform is estimated by solving a convex optimization problem and statistical inferences about the parameters are obtained from the posterior distribution by importance sampling. Our results show that isoform expression inference in RNA-Seq is possible by employing appropriate statistical methods.'),
(74654, 2009, 'bio', 'Predicting helix-helix interactions from residue contacts in membrane proteins', 'Lo, Allan|Chiu, Yi-Yuan|Rødland, Einar Andreas|Lyu, Ping-Chiang|Sung, Ting-Yi|Hsu, Wen-Lian', 'Bioinformatics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan.|Bioinformatics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan.|Bioinformatics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan.|Bioinformatics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan.|Bioinformatics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan.|Bioinformatics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan.', '-|-|-|-|-|-', 44, 'Computational Biology|Databases, Protein|Membrane Proteins|Models, Biological|Protein Structure, Secondary|Reproducibility of Results', 'Journal Article', '10.1093/bioinformatics/btp114', '19244388', 'Helix-helix interactions play a critical role in the structure assembly, stability and function of membrane proteins. On the molecular level, the interactions are mediated by one or more residue contacts. Although previous studies focused on helix-packing patterns and sequence motifs, few of them developed methods specifically for contact prediction.'),
(74655, 2009, 'bio', 'Boosting for high-dimensional time-to-event data with competing risks', 'Binder, Harald|Allignol, Arthur|Schumacher, Martin|Beyersmann, Jan', 'Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstr 1 and Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Freiburg, Germany. binderh@fdm.uni-freiburg.de|Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstr 1 and Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Freiburg, Germany. binderh@fdm.uni-freiburg.de|Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstr 1 and Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Freiburg, Germany. binderh@fdm.uni-freiburg.de|Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstr 1 and Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Freiburg, Germany. binderh@fdm.uni-freiburg.de', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Gene Expression Profiling|Humans|Models, Statistical|Neoplasms|Oligonucleotide Array Sequence Analysis|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/btp088', '19244389', 'For analyzing high-dimensional time-to-event data with competing risks, tailored modeling techniques are required that consider the event of interest and the competing events at the same time, while also dealing with censoring. For low-dimensional settings, proportional hazards models for the subdistribution hazard have been proposed, but an adaptation for high-dimensional settings is missing. In addition, tools for judging the prediction performance of fitted models have to be provided.'),
(74656, 2009, 'bio', 'Biomarker discovery in MALDI-TOF serum protein profiles using discrete wavelet transformation', 'Alexandrov, Theodore|Decker, Jens|Mertens, Bart|Deelder, Andre M|Tollenaar, Rob A E M|Maass, Peter|Thiele, Herbert', 'Center for Industrial Mathematics, University of Bremen, D-28334 Bremen, Germany. theodore@math.uni-bremen.de|Center for Industrial Mathematics, University of Bremen, D-28334 Bremen, Germany. theodore@math.uni-bremen.de|Center for Industrial Mathematics, University of Bremen, D-28334 Bremen, Germany. theodore@math.uni-bremen.de|Center for Industrial Mathematics, University of Bremen, D-28334 Bremen, Germany. theodore@math.uni-bremen.de|Center for Industrial Mathematics, University of Bremen, D-28334 Bremen, Germany. theodore@math.uni-bremen.de|Center for Industrial Mathematics, University of Bremen, D-28334 Bremen, Germany. theodore@math.uni-bremen.de|Center for Industrial Mathematics, University of Bremen, D-28334 Bremen, Germany. theodore@math.uni-bremen.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 61, 'Biomarkers|Blood Proteins|Gene Expression Profiling|Proteomics|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Journal Article', '10.1093/bioinformatics/btn662', '19244390', 'Automatic classification of high-resolution mass spectrometry proteomic data has increasing potential in the early diagnosis of cancer. We propose a new procedure of biomarker discovery in serum protein profiles based on: (i) discrete wavelet transformation of the spectra, (ii) selection of discriminative wavelet coefficients by a statistical test and (iii) building and evaluating a support vector machine classifier by double cross-validation with attention to the generalizability of the results. In addition to the evaluation results (total recognition rate, sensitivity and specificity), the procedure provides the biomarker patterns, i.e. the parts of spectra which discriminate cancer and control individuals. The evaluation was performed on matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) serum protein profiles of 66 colorectal cancer patients and 50 controls.'),
(74657, 2009, 'bio', 'mkESA: enhanced suffix array construction tool', 'Homann, Robert|Fleer, David|Giegerich, Robert|Rehmsmeier, Marc', 'International NRW Graduate School in Bioinformatics and Genome Research, Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany. rhomann@techfak.uni-bielefeld.de|International NRW Graduate School in Bioinformatics and Genome Research, Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany. rhomann@techfak.uni-bielefeld.de|International NRW Graduate School in Bioinformatics and Genome Research, Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany. rhomann@techfak.uni-bielefeld.de|International NRW Graduate School in Bioinformatics and Genome Research, Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany. rhomann@techfak.uni-bielefeld.de', 'Germany|Germany|Germany|Germany', 18, 'Algorithms|Computational Biology|Sequence Analysis|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btp112', '19246510', 'We introduce the tool mkESA, an open source program for constructing enhanced suffix arrays (ESAs), striving for low memory consumption, yet high practical speed. mkESA is a user-friendly program written in portable C99, based on a parallelized version of the Deep-Shallow suffix array construction algorithm, which is known for its high speed and small memory usage. The tool handles large FASTA files with multiple sequences, and computes suffix arrays and various additional tables, such as the LCP table (longest common prefix) or the inverse suffix array, from given sequence data.'),
(74658, 2009, 'bio', 'A robust peak detection method for RNA structure inference by high-throughput contact mapping', 'Kim, Jinkyu|Yu, Seunghak|Shim, Byonghyo|Kim, Hanjoo|Min, Hyeyoung|Chung, Eui-Young|Das, Rhiju|Yoon, Sungroh', 'School of Electrical Engineering, Korea University, Seoul 136-713, Korea.|School of Electrical Engineering, Korea University, Seoul 136-713, Korea.|School of Electrical Engineering, Korea University, Seoul 136-713, Korea.|School of Electrical Engineering, Korea University, Seoul 136-713, Korea.|School of Electrical Engineering, Korea University, Seoul 136-713, Korea.|School of Electrical Engineering, Korea University, Seoul 136-713, Korea.|School of Electrical Engineering, Korea University, Seoul 136-713, Korea.|School of Electrical Engineering, Korea University, Seoul 136-713, Korea.', '-|-|-|-|-|-|-|-', 0, 'Base Sequence|Computational Biology|Models, Molecular|Molecular Sequence Data|Nucleic Acid Conformation|Pattern Recognition, Automated|RNA', 'Journal Article', '10.1093/bioinformatics/btp110', '19246511', 'For high-throughput prediction of the helical arrangements of large RNA molecules, an innovative method termed multiplexed hydroxyl radical (*OH) cleavage analysis (MOHCA) has been proposed. A key step in this promising technique is to detect peaks accurately from noisy radioactivity profiles. Since manual peak finding is laborious and prone to error, an automated peak detection method to improve the accuracy and throughput of MOHCA is required. Existing methods were not applicable to MOHCA due to their high false positive rates.'),
(74659, 2009, 'bio', 'PSIBLAST_PairwiseStatSig: reordering PSI-BLAST hits using pairwise statistical significance', 'Agrawal, Ankit|Huang, Xiaoqiu', 'Department of Computer Science, Iowa State University, Ames, IA 50011-1041, USA. ankitag@cs.iastate.edu|Department of Computer Science, Iowa State University, Ames, IA 50011-1041, USA. ankitag@cs.iastate.edu', 'United States|United States', 14, 'Algorithms|Computational Biology|Databases, Protein|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btp089', '19251771', 'We present an add-on to BLAST and PSI-BLAST programs to reorder their hits using pairwise statistical significance. Using position-specific substitution matrices to estimate pairwise statistical significance has been recently shown to give promising results in terms of retrieval accuracy, which motivates its use to refine PSI-BLAST results, since PSI-BLAST also constructs a position-specific substitution matrix for the query sequence during the search. The obvious advantage of the approach is more accurate estimates of statistical significance because of pairwise statistical significance, along with the advantage of BLAST/PSI-BLAST in terms of speed.'),
(74660, 2009, 'bio', 'Textual data compression in computational biology: a synopsis', 'Giancarlo, Raffaele|Scaturro, Davide|Utro, Filippo', 'Dipartimento di Matematica ed Applicazioni, Università di Palermo, Palermo, Italy. raffaele@math.unipa.it|Dipartimento di Matematica ed Applicazioni, Università di Palermo, Palermo, Italy. raffaele@math.unipa.it|Dipartimento di Matematica ed Applicazioni, Università di Palermo, Palermo, Italy. raffaele@math.unipa.it', 'Italy|Italy|Italy', 68, 'Computational Biology|Databases, Factual|Information Storage and Retrieval|Software', 'Journal Article', '10.1093/bioinformatics/btp117', '19251772', 'Textual data compression, and the associated techniques coming from information theory, are often perceived as being of interest for data communication and storage. However, they are also deeply related to classification and data mining and analysis. In recent years, a substantial effort has been made for the application of textual data compression techniques to various computational biology tasks, ranging from storage and indexing of large datasets to comparison and reverse engineering of biological networks.'),
(74661, 2009, 'bio', 'GeNGe: systematic generation of gene regulatory networks', 'Hache, Hendrik|Wierling, Christoph|Lehrach, Hans|Herwig, Ralf', 'Vertebrate Genomics-Bioinformatics Group, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany. hache@molgen.mpg.de|Vertebrate Genomics-Bioinformatics Group, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany. hache@molgen.mpg.de|Vertebrate Genomics-Bioinformatics Group, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany. hache@molgen.mpg.de|Vertebrate Genomics-Bioinformatics Group, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany. hache@molgen.mpg.de', 'Germany|Germany|Germany|Germany', 0, 'Computational Biology|Gene Expression Profiling|Gene Regulatory Networks|Internet|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp115', '19251773', 'The analysis of gene regulatory networks (GRNs) is a central goal of bioinformatics highly accelerated by the advent of new experimental techniques, such as RNA interference. A battery of reverse engineering methods has been developed in recent years to reconstruct the underlying GRNs from these and other experimental data. However, the performance of the individual methods is poorly understood and validation of algorithmic performances is still missing to a large extent. To enable such systematic validation, we have developed the web application GeNGe (GEne Network GEnerator), a controlled framework for the automatic generation of GRNs. The theoretical model for a GRN is a non-linear differential equation system. Networks can be user-defined or constructed in a modular way with the option to introduce global and local network perturbations. Resulting data can be used, e.g. as benchmark data for evaluating GRN reconstruction methods or for predicting effects of perturbations as theoretical counterparts of biological experiments.'),
(74662, 2009, 'bio', 'WSsas: a web service for the annotation of functional residues through structural homologues', 'Talavera, David|Laskowski, Roman A|Thornton, Janet M', 'EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. talavera@ebi.ac.uk|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. talavera@ebi.ac.uk|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. talavera@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 15, 'Computational Biology|Databases, Protein|Internet|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btp116', '19251774', 'Annotation tools help scientists to traverse the gap between characterized and uncharacterized proteins. Tools for the prediction of protein function include those which predict the function of entire proteins or complexes, those annotating functional domains and those which predict specific residues within the domain. We have developed WSsas, a web service focused on the annotation of essential functional residues. WSsas uses similarity searches and pairwise alignments to transfer functional information about binding, catalytic and protein-protein interaction residues from solved structures to query sequences. In addition, WSsas can supply information about the relevant functional atoms. The web service definition (WSDL) file and a Perl client are freely available at http://www.ebi.ac.uk/thornton-srv/databases/WSsas/.'),
(74663, 2009, 'bio', 'DIYA: a bacterial annotation pipeline for any genomics lab', 'Stewart, Andrew C|Osborne, Brian|Read, Timothy D', 'Genomics Department, Biological Defense Research Directorate, Naval Medical Research Center, Rockville, MD, USA.|Genomics Department, Biological Defense Research Directorate, Naval Medical Research Center, Rockville, MD, USA.|Genomics Department, Biological Defense Research Directorate, Naval Medical Research Center, Rockville, MD, USA.', 'United States|United States|United States', 0, 'Databases, Genetic|Genome, Bacterial|Genomics|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btp097', '19254921', 'DIYA (Do-It-Yourself Annotator) is a modular and configurable open source pipeline software, written in Perl, used for the rapid annotation of bacterial genome sequences. The software is currently used to take DNA contigs as input, either in the form of complete genomes or the result of shotgun sequencing, and produce an annotated sequence in Genbank file format as output.'),
(74664, 2009, 'bio', 'The use of gene ontology evidence codes in preventing classifier assessment bias', 'Rogers, Mark F|Ben-Hur, Asa', 'Computer Science Department, Colorado State University, Ft. Collins, CO, USA. rogersma@cs.colostate.edu|Computer Science Department, Colorado State University, Ft. Collins, CO, USA. rogersma@cs.colostate.edu', 'United States|United States', 0, 'Computational Biology|Databases, Protein|Genes|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btp122', '19254922', 'The biological communitys reliance on computational annotations of protein function makes correct assessment of function prediction methods an issue of great importance. The fact that a large fraction of the annotations in current biological databases are based on computational methods can lead to bias in estimating the accuracy of function prediction methods. This can happen since predicting an annotation that was derived computationally in the first place is likely easier than predicting annotations that were derived experimentally, leading to over-optimistic classifier performance estimates.'),
(74665, 2009, 'bio', 'Multivariate analysis of variance test for gene set analysis', 'Tsai, Chen-An|Chen, James J', 'Graduate Institute of Biostatistics and Biostatistics Center, China Medical University, Taichung, Taiwan. catsai@mail.cmu.edu.tw|Graduate Institute of Biostatistics and Biostatistics Center, China Medical University, Taichung, Taiwan. catsai@mail.cmu.edu.tw', 'China|China', 70, 'Analysis of Variance|Computer Simulation|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btp098', '19254923', 'Gene class testing (GCT) or gene set analysis (GSA) is a statistical approach to determine whether some functionally predefined sets of genes express differently under different experimental conditions. Shortcomings of the Fishers exact test for the overrepresentation analysis are illustrated by an example. Most alternative GSA methods are developed for data collected from two experimental conditions, and most is based on a univariate gene-by-gene test statistic or assume independence among genes in the gene set. A multivariate analysis of variance (MANOVA) approach is proposed for studies with two or more experimental conditions.'),
(74666, 2009, 'bio', 'Erratum: sample size determination for the false discovery rate', 'Pounds, Stan|Cheng, Cheng', 'Graduate Institute of Biostatistics and Biostatistics Center, China Medical University, Taichung, Taiwan. catsai@mail.cmu.edu.tw|Graduate Institute of Biostatistics and Biostatistics Center, China Medical University, Taichung, Taiwan. catsai@mail.cmu.edu.tw', 'China|China', 0, 'Computational Biology|False Positive Reactions|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Sample Size', 'Letter', '10.1093/bioinformatics/btn661', '19255981', '-'),
(74667, 2009, 'bio', 'Illoura: a software tool for analysis, visualization and semantic querying of cellular and other spatial biological data', 'McComb, Tim|Cairncross, Oliver|Noske, Andrew B|Wood, David L A|Marsh, Brad J|Ragan, Mark A', 'Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4072, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Cells|Computational Biology|Computer Graphics|Databases, Factual|Information Storage and Retrieval|Software', 'Journal Article', '10.1093/bioinformatics/btp125', '19258351', 'New high-resolution approaches for mapping ultrastructure of cells in 3D are leading to unprecedented quantities of spatial data. Here we present Illoura, a software tool for the integrated management, analysis and visualization of these data within a semantic context, and illustrate its capability by analysis of spatial relationships in mammalian beta cells.'),
(74668, 2009, 'bio', 'SpliceAid: a database of experimental RNA target motifs bound by splicing proteins in humans', 'Piva, Francesco|Giulietti, Matteo|Nocchi, Linda|Principato, Giovanni', 'Institute of Biology and Genetics, Polytechnic University of Marche, 60131, Ancona, Italy. f.piva@univpm.it|Institute of Biology and Genetics, Polytechnic University of Marche, 60131, Ancona, Italy. f.piva@univpm.it|Institute of Biology and Genetics, Polytechnic University of Marche, 60131, Ancona, Italy. f.piva@univpm.it|Institute of Biology and Genetics, Polytechnic University of Marche, 60131, Ancona, Italy. f.piva@univpm.it', 'Italy|Italy|Italy|Italy', 0, 'Binding Sites|Databases, Nucleic Acid|Humans|Internet|RNA|RNA Splicing|RNA-Binding Proteins', 'Journal Article', '10.1093/bioinformatics/btp124', '19261717', 'The correct post-transcriptional RNA processing is finely regulated by RNA-binding proteins. Unfortunately, there is little experimental information on target RNA sequences of RNA-binding proteins and moreover such experimentally derived target sequences are annotated in a compact form by the score matrices that overestimate the number of possible recognized sequences. We carried out an exhaustive hand curated literature search to create a database, SpliceAid, collecting all the experimentally assessed target RNA sequences that are bound by splicing proteins in humans. We built a web resource, database driven, to easy query SpliceAid and give back the results by an accurate and dynamic graphic representation.'),
(74669, 2009, 'bio', 'MIST: Maximum Information Spanning Trees for dimension reduction of biological data sets', 'King, Bracken M|Tidor, Bruce', 'Computer Science and Artificial Intelligence Laboratory, Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.|Computer Science and Artificial Intelligence Laboratory, Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.', 'United States|United States', 50, 'Computational Biology|Databases, Genetic|Entropy|Gene Expression Profiling|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btp109', '19261718', 'The study of complex biological relationships is aided by large and high-dimensional data sets whose analysis often involves dimension reduction to highlight representative or informative directions of variation. In principle, information theory provides a general framework for quantifying complex statistical relationships for dimension reduction. Unfortunately, direct estimation of high-dimensional information theoretic quantities, such as entropy and mutual information (MI), is often unreliable given the relatively small sample sizes available for biological problems. Here, we develop and evaluate a hierarchy of approximations for high-dimensional information theoretic statistics from associated low-order terms, which can be more reliably estimated from limited samples. Due to a relationship between this metric and the minimum spanning tree over a graph representation of the system, we refer to these approximations as MIST (Maximum Information Spanning Trees).'),
(74670, 2009, 'bio', 'A web server for inferring the human N-acetyltransferase-2 (NAT2) enzymatic phenotype from NAT2 genotype', 'Kuznetsov, Igor B|McDuffie, Michael|Moslehi, Roxana', 'Gen*NY*Sis Center for Excellence in Cancer Genomics, Department of Epidemiology and Biostatistics, University at Albany, One Discovery Drive, Rensselaer, NY 12144, USA. ikuznetsov@albany.edu|Gen*NY*Sis Center for Excellence in Cancer Genomics, Department of Epidemiology and Biostatistics, University at Albany, One Discovery Drive, Rensselaer, NY 12144, USA. ikuznetsov@albany.edu|Gen*NY*Sis Center for Excellence in Cancer Genomics, Department of Epidemiology and Biostatistics, University at Albany, One Discovery Drive, Rensselaer, NY 12144, USA. ikuznetsov@albany.edu', 'United States|United States|United States', 30, 'Arylamine N-Acetyltransferase|Genotype|Humans|Internet|Phenotype|Polymorphism, Single Nucleotide|Software|Substrate Specificity', 'Journal Article', '10.1093/bioinformatics/btp121', '19261719', 'N-acetyltransferase-2 (NAT2) is an important enzyme that catalyzes the acetylation of aromatic and heterocyclic amine carcinogens. Individuals in human populations are divided into three NAT2 acetylator phenotypes: slow, rapid and intermediate. NAT2PRED is a web server that implements a supervised pattern recognition method to infer NAT2 phenotype from SNPs found in NAT2 gene positions 282, 341, 481, 590, 803 and 857. The web server can be used for a fast determination of NAT2 phenotypes in genetic screens.'),
(74671, 2009, 'bio', 'A modified hyperplane clustering algorithm allows for efficient and accurate clustering of extremely large datasets', 'Sharma, Ashok|Podolsky, Robert|Zhao, Jieping|McIndoe, Richard A', 'Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta, GA, USA.|Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta, GA, USA.|Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta, GA, USA.|Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta, GA, USA.', 'Georgia|Georgia|Georgia|Georgia', 0, 'Algorithms|Cluster Analysis|Computational Biology|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Software', 'Journal Article', '10.1093/bioinformatics/btp123', '19261720', 'As the number of publically available microarray experiments increases, the ability to analyze extremely large datasets across multiple experiments becomes critical. There is a requirement to develop algorithms which are fast and can cluster extremely large datasets without affecting the cluster quality. Clustering is an unsupervised exploratory technique applied to microarray data to find similar data structures or expression patterns. Because of the high input/output costs involved and large distance matrices calculated, most of the algomerative clustering algorithms fail on large datasets (30,000 + genes/200 + arrays). In this article, we propose a new two-stage algorithm which partitions the high-dimensional space associated with microarray data using hyperplanes. The first stage is based on the Balanced Iterative Reducing and Clustering using Hierarchies algorithm with the second stage being a conventional k-means clustering technique. This algorithm has been implemented in a software tool (HPCluster) designed to cluster gene expression data. We compared the clustering results using the two-stage hyperplane algorithm with the conventional k-means algorithm from other available programs. Because, the first stage traverses the data in a single scan, the performance and speed increases substantially. The data reduction accomplished in the first stage of the algorithm reduces the memory requirements allowing us to cluster 44,460 genes without failure and significantly decreases the time to complete when compared with popular k-means programs. The software was written in C# (.NET 1.1).'),
(74672, 2009, 'bio', 'LOCP--locating pilus operons in gram-positive bacteria', 'Plyusnin, Ilya|Holm, Liisa|Kankainen, Matti', 'Institute of Biotechnology, University of Helsinki, P.O.Box 56 (Viikinkaari 5), FIN-00014 University of Helsinki, Finland.|Institute of Biotechnology, University of Helsinki, P.O.Box 56 (Viikinkaari 5), FIN-00014 University of Helsinki, Finland.|Institute of Biotechnology, University of Helsinki, P.O.Box 56 (Viikinkaari 5), FIN-00014 University of Helsinki, Finland.', 'Finland|Finland|Finland', 8, 'Algorithms|Fimbriae, Bacterial|Genome, Bacterial|Gram-Positive Bacteria|Operon|Software', 'Journal Article', '10.1093/bioinformatics/btp127', '19261721', 'Pilus operons encode a pivotal host-microbe interaction structure that is vital for pathogenicity, colonization and adhesion. LOCP is a computational tool to quickly test whether or not the genome of a gram-positive bacterium of interest or some DNA-contig in a metagenomic sample hold pilus operons. Predictions are made based on distinctive motifs of pilus-related protein sequences and on the tendency of these protein sequences to occur in dense clusters. The tool showed a phenomenal accuracy and revealed that various novel, and even unexpected, gram-positive bacteria do possess pilus operons. Thus, the tool helps us to focus the laboratory research on genes behind this important and indicative feature, and to screen for strains containing them.'),
(74673, 2009, 'bio', 'RNATOPS-W: a web server for RNA structure searches of genomes', 'Wang, Yingfeng|Huang, Zhibin|Wu, Yong|Malmberg, Russell L|Cai, Liming', 'Department of Computer Science, Department of Plant Biology and Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA.|Department of Computer Science, Department of Plant Biology and Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA.|Department of Computer Science, Department of Plant Biology and Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA.|Department of Computer Science, Department of Plant Biology and Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA.|Department of Computer Science, Department of Plant Biology and Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA.', 'Georgia|Georgia|Georgia|Georgia|Georgia', 1, 'Genome|Genomics|Internet|Markov Chains|RNA|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btp095', '19269988', 'RNATOPS-W is a web server to search sequences for RNA secondary structures including pseudoknots. The server accepts an annotated RNA multiple structural alignment as a structural profile and genomic or other sequences to search. It is built upon RNATOPS, a command line C++ software package for the same purpose, in which filters to speed up search are manually selected. RNATOPS-W improves upon RNATOPS by adding the function of automatic selection of a hidden Markov model (HMM) filter and also a friendly user interface for selection of a substructure filter by the user. In addition, RNATOPS-W complements existing RNA secondary structure search web servers that either use built-in structure profiles or are not able to detect pseudoknots. RNATOPS-W inherits the efficiency of RNATOPS in detecting large, complex RNA structures.'),
(74674, 2009, 'bio', 'PADRE: a package for analyzing and displaying reticulate evolution', 'Lott, Martin|Spillner, Andreas|Huber, Katharina T|Moulton, Vincent', 'School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK. martin.lott@uea.ac.uk|School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK. martin.lott@uea.ac.uk|School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK. martin.lott@uea.ac.uk|School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK. martin.lott@uea.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Evolution, Molecular|Gene Regulatory Networks|Phylogeny|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp133', '19269989', 'Recent advances in gene sequencing for polyploid species, coupled with standard phylogenetic tree reconstruction, leads to gene trees in which the same species can label several leaves. Such multi-labeled trees are then used to reconstruct the evolutionary history of the polyploid species in question. However, this reconstruction process requires new techniques that are not available in current phylogenetic software packages. Here, we describe the software package PADRE (Package for Analyzing and Displaying Reticulate Evolution) that implements such techniques, allowing the reconstruction of complex evolutionary histories for polyploids in the form of phylogenetic networks.'),
(74675, 2009, 'bio', 'A consistency-based consensus algorithm for de novo and reference-guided sequence assembly of short reads', 'Rausch, Tobias|Koren, Sergey|Denisov, Gennady|Weese, David|Emde, Anne-Katrin|Döring, Andreas|Reinert, Knut', 'International Max Planck Research School for Computational Biology and Scientific Computing, Ihnestr. 63-73, Algorithmische Bioinformatik, Institut für Informatik, Takustr. 9, 14195 Berlin, Germany. rausch@inf.fu-berlin.de|International Max Planck Research School for Computational Biology and Scientific Computing, Ihnestr. 63-73, Algorithmische Bioinformatik, Institut für Informatik, Takustr. 9, 14195 Berlin, Germany. rausch@inf.fu-berlin.de|International Max Planck Research School for Computational Biology and Scientific Computing, Ihnestr. 63-73, Algorithmische Bioinformatik, Institut für Informatik, Takustr. 9, 14195 Berlin, Germany. rausch@inf.fu-berlin.de|International Max Planck Research School for Computational Biology and Scientific Computing, Ihnestr. 63-73, Algorithmische Bioinformatik, Institut für Informatik, Takustr. 9, 14195 Berlin, Germany. rausch@inf.fu-berlin.de|International Max Planck Research School for Computational Biology and Scientific Computing, Ihnestr. 63-73, Algorithmische Bioinformatik, Institut für Informatik, Takustr. 9, 14195 Berlin, Germany. rausch@inf.fu-berlin.de|International Max Planck Research School for Computational Biology and Scientific Computing, Ihnestr. 63-73, Algorithmische Bioinformatik, Institut für Informatik, Takustr. 9, 14195 Berlin, Germany. rausch@inf.fu-berlin.de|International Max Planck Research School for Computational Biology and Scientific Computing, Ihnestr. 63-73, Algorithmische Bioinformatik, Institut für Informatik, Takustr. 9, 14195 Berlin, Germany. rausch@inf.fu-berlin.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Base Sequence|Computational Biology|Internet|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btp131', '19269990', 'Novel high-throughput sequencing technologies pose new algorithmic challenges in handling massive amounts of short-read, high-coverage data. A robust and versatile consensus tool is of particular interest for such data since a sound multi-read alignment is a prerequisite for variation analyses, accurate genome assemblies and insert sequencing.'),
(74676, 2009, 'bio', 'Smoothing waves in array CGH tumor profiles', 'van de Wiel, Mark A|Brosens, Rebecca|Eilers, Paul H C|Kumps, Candy|Meijer, Gerrit A|Menten, Björn|Sistermans, Erik|Speleman, Frank|Timmerman, Marieke E|Ylstra, Bauke', 'Department of Epidemiology & Biostatistics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Epidemiology & Biostatistics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Epidemiology & Biostatistics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Epidemiology & Biostatistics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Epidemiology & Biostatistics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Epidemiology & Biostatistics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Epidemiology & Biostatistics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Epidemiology & Biostatistics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Epidemiology & Biostatistics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Epidemiology & Biostatistics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Neth', 59, 'Comparative Genomic Hybridization|Computational Biology|Databases, Genetic|Gene Dosage|Gene Expression Profiling|Neoplasms|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btp132', '19276148', 'Many high-resolution array comparative genomic hybridization tumor profiles contain a wave bias, which makes accurate detection of breakpoints in such profiles more difficult.'),
(74677, 2009, 'bio', 'DV-Curve: a novel intuitive tool for visualizing and analyzing DNA sequences', 'Zhang, Zhu-Jin', 'Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China. zhangzhujin@gmail.com', 'China', 0, 'Base Sequence|Computational Biology|Computer Graphics|DNA|Databases, Genetic|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btp130', '19276149', 'The rapid growth of DNA sequence data creates a need to find graphic tools to study DNA sequence in a perceivable form. A large number of scholars work hard in this field. However, it is difficult to handle the following problems in one graph: (i) degeneracy, (ii) loss of information, (iii) difficulty of observing in multi-dimensional graph, (iv) difficulty of visualization when representing long DNA sequences and (v) need to reflect useful information.'),
(74678, 2009, 'bio', 'Correction for phylogeny, small number of observations and data redundancy improves the identification of coevolving amino acid pairs using mutual information', 'Buslje, Cristina Marino|Santos, Javier|Delfino, Jose Maria|Nielsen, Morten', 'Department of Biological Chemistry and Institute of Biochemistry and Biophysics (IQUIFIB), School of Pharmacy and Biochemistry, University of Buenos Aires, Junín 956, 1113 Buenos Aires, Argentina. cmb@qb.ffyb.uba.ar|Department of Biological Chemistry and Institute of Biochemistry and Biophysics (IQUIFIB), School of Pharmacy and Biochemistry, University of Buenos Aires, Junín 956, 1113 Buenos Aires, Argentina. cmb@qb.ffyb.uba.ar|Department of Biological Chemistry and Institute of Biochemistry and Biophysics (IQUIFIB), School of Pharmacy and Biochemistry, University of Buenos Aires, Junín 956, 1113 Buenos Aires, Argentina. cmb@qb.ffyb.uba.ar|Department of Biological Chemistry and Institute of Biochemistry and Biophysics (IQUIFIB), School of Pharmacy and Biochemistry, University of Buenos Aires, Junín 956, 1113 Buenos Aires, Argentina. cmb@qb.ffyb.uba.ar', 'Argentina|Argentina|Argentina|Argentina', 0, 'Algorithms|Amino Acid Sequence|Amino Acids|Computational Biology|Databases, Protein|Phylogeny|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btp135', '19276150', 'Mutual information (MI) theory is often applied to predict positional correlations in a multiple sequence alignment (MSA) to make possible the analysis of those positions structurally or functionally important in a given fold or protein family. Accurate identification of coevolving positions in protein sequences is difficult due to the high background signal imposed by phylogeny and noise. Several methods have been proposed using MI to identify coevolving amino acids in protein families.'),
(74679, 2009, 'bio', 'The tspair package for finding top scoring pair classifiers in R', 'Leek, Jeffrey T', 'Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD 21287, USA. jtleek@jhu.edu', 'United States', 0, 'Algorithms|Computational Biology|Gene Expression Profiling|Software', 'Journal Article', '10.1093/bioinformatics/btp126', '19276151', 'Top scoring pairs (TSPs) are pairs of genes whose relative rankings can be used to accurately classify individuals into one of two classes. TSPs have two main advantages over many standard classifiers used in gene expression studies: (i) a TSP is based on only two genes, which leads to easily interpretable and inexpensive diagnostic tests and (ii) TSP classifiers are based on gene rankings, so they are more robust to variation in technical factors or normalization than classifiers based on expression levels of individual genes. Here I describe the R package, tspair, which can be used to quickly identify and assess TSP classifiers for gene expression data.'),
(74680, 2009, 'bio', 'Joint estimation of copy number variation and reference intensities on multiple DNA arrays using GADA', 'Pique-Regi, Roger|Ortega, Antonio|Asgharzadeh, Shahab', 'Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, EEB 400, 3740 McClintock Ave, Los Angeles, CA 90089-2564, USA. rpique@ieee.org|Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, EEB 400, 3740 McClintock Ave, Los Angeles, CA 90089-2564, USA. rpique@ieee.org|Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, EEB 400, 3740 McClintock Ave, Los Angeles, CA 90089-2564, USA. rpique@ieee.org', 'United States|United States|United States', 34, 'Algorithms|Bayes Theorem|Databases, Genetic|Gene Dosage|Gene Expression Profiling|Genetic Variation|Genome|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btp119', '19276152', 'The complexity of a large number of recently discovered copy number polymorphisms is much higher than initially thought, thus making it more difficult to detect them in the presence of significant measurement noise. In this scenario, separate normalization and segmentation is prone to lead to many false detections of changes in copy number. New approaches capable of jointly modeling the copy number and the non-copy number (noise) hybridization effects across multiple samples will potentially lead to more accurate results.'),
(74681, 2009, 'bio', 'Switching regulatory models of cellular stress response', 'Sanguinetti, Guido|Ruttor, Andreas|Opper, Manfred|Archambeau, Cedric', 'Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Road, Sheffield, S1 4DP, UK. guido@dcs.shef.ac.uk|Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Road, Sheffield, S1 4DP, UK. guido@dcs.shef.ac.uk|Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Road, Sheffield, S1 4DP, UK. guido@dcs.shef.ac.uk|Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Road, Sheffield, S1 4DP, UK. guido@dcs.shef.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computational Biology|Escherichia coli|Gene Expression Profiling|Models, Statistical|Oxygen|RNA, Messenger|Stress, Physiological|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btp138', '19279066', 'Stress response in cells is often mediated by quick activation of transcription factors (TFs). Given the difficulty in experimentally assaying TF activities, several statistical approaches have been proposed to infer them from microarray time courses. However, these approaches often rely on prior assumptions which rule out the rapid responses observed during stress response.'),
(74682, 2009, 'bio', 'CodonExplorer: an online tool for analyzing codon usage and sequence composition, scaling from genes to genomes', 'Hamady, Micah|Wilson, Stephanie A|Zaneveld, Jesse|Sueoka, Noboru|Knight, Rob', 'Department of Computer Science, University of Colorado, Boulder, CO 80309, USA.|Department of Computer Science, University of Colorado, Boulder, CO 80309, USA.|Department of Computer Science, University of Colorado, Boulder, CO 80309, USA.|Department of Computer Science, University of Colorado, Boulder, CO 80309, USA.|Department of Computer Science, University of Colorado, Boulder, CO 80309, USA.', 'United States|United States|United States|United States|United States', 0, 'Base Composition|Base Sequence|Codon|Computational Biology|Genes|Genome|Online Systems|Software', 'Journal Article', '10.1093/bioinformatics/btp141', '19279067', 'DNA composition in general, and codon usage in particular, is crucial for understanding gene function and evolution. CodonExplorer, available online at http://bmf.colorado.edu/codonexplorer/, is an online tool and interactive database that contains millions of genes, allowing rapid exploration of the factors governing gene and genome compositional evolution and exploiting GC content and codon usage frequency to identify genes with composition suggesting high levels of expression or horizontal transfer.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(74683, 2009, 'bio', 'Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules', 'Fober, Thomas|Mernberger, Marco|Klebe, Gerhard|Hüllermeier, Eyke', 'Department of Mathematics and Computer Science, Philipps-Universität Marburg, Marburg, Germany.|Department of Mathematics and Computer Science, Philipps-Universität Marburg, Marburg, Germany.|Department of Mathematics and Computer Science, Philipps-Universität Marburg, Marburg, Germany.|Department of Mathematics and Computer Science, Philipps-Universität Marburg, Marburg, Germany.', 'Germany|Germany|Germany|Germany', 23, 'Algorithms|Binding Sites|Computational Biology|Computer Graphics|Databases, Protein|Protein Interaction Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btp144', '19286830', 'The concept of multiple graph alignment (MGA) has recently been introduced as a novel method for the structural analysis of biomolecules. Using approximate graph matching techniques, this method enables the robust identification of approximately conserved patterns in biologically related structures. In particular, MGA enables the characterization of functional protein families independent of sequence or fold homology. This article first recalls the concept of MGA and then addresses the problem of computing optimal alignments from an algorithmic point of view. In this regard, a method from the field of evolutionary algorithms is proposed and empirically compared with a hitherto existing heuristic approach. Empirically, it is shown that the former yields significantly better results than the latter, albeit at the cost of an increased runtime.'),
(74684, 2009, 'bio', 'Site of metabolism prediction for six biotransformations mediated by cytochromes P450', 'Zheng, Mingyue|Luo, Xiaomin|Shen, Qiancheng|Wang, Yong|Du, Yun|Zhu, Weiliang|Jiang, Hualiang', 'Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.', 'China|China|China|China|China|China|China', 54, 'Biotransformation|Computational Biology|Cytochrome P-450 Enzyme System|Drug Design|Metabolic Networks and Pathways|Metabolomics', 'Journal Article', '10.1093/bioinformatics/btp140', '19286831', 'One goal of metabolomics is to define and monitor the entire metabolite complement of a cell, while it is still far from reach since systematic and rapid approaches for determining the biotransformations of newly discovered metabolites are lacking. For drug development, such metabolic biotransformation of a new chemical entity (NCE) is of more interest because it may profoundly affect its bioavailability, activity and toxicity profile. The use of in silico methods to predict the site of metabolism (SOM) in phase I cytochromes P450-mediated reactions is usually a starting point of metabolic pathway studies, which may also assist in the process of drug/lead optimization.'),
(74685, 2009, 'bio', 'A novel parallel approach to the likelihood-based estimation of admixture in population genetics', 'Giovannini, Ambra|Zanghirati, Gaetano|Beaumont, Mark A|Chikhi, Lounès|Barbujani, Guido', 'Department of Mathematics and Math4Tech Center, University of Ferrara, Ferrara, Italy. ambra.giovannini@unife.it|Department of Mathematics and Math4Tech Center, University of Ferrara, Ferrara, Italy. ambra.giovannini@unife.it|Department of Mathematics and Math4Tech Center, University of Ferrara, Ferrara, Italy. ambra.giovannini@unife.it|Department of Mathematics and Math4Tech Center, University of Ferrara, Ferrara, Italy. ambra.giovannini@unife.it|Department of Mathematics and Math4Tech Center, University of Ferrara, Ferrara, Italy. ambra.giovannini@unife.it', 'Italy|Italy|Italy|Italy|Italy', 0, 'Computational Biology|Evolution, Molecular|Genetics, Population|Likelihood Functions|Monte Carlo Method', 'Journal Article', '10.1093/bioinformatics/btp136', '19286832', 'Inferring population admixture from genetic data and quantifying it is a difficult but crucial task in evolutionary and conservation biology. Unfortunately state-of-the-art probabilistic approaches are computationally demanding. Effectively exploiting the computational power of modern multiprocessor systems can thus have a positive impact to Monte Carlo-based simulation of admixture modeling. A novel parallel approach is briefly described and promising results on its message passing interface (MPI)-based C++ implementation are reported.'),
(74686, 2009, 'bio', 'Statistical detection of cooperative transcription factors with similarity adjustment', 'Pape, Utz J|Klein, Holger|Vingron, Martin', 'Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestr. 73 and Mathematics and Computer Science, Free University of Berlin, Takustr. 9, 14195 Berlin, Germany. utz.pape@molgen.mpg.de|Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestr. 73 and Mathematics and Computer Science, Free University of Berlin, Takustr. 9, 14195 Berlin, Germany. utz.pape@molgen.mpg.de|Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestr. 73 and Mathematics and Computer Science, Free University of Berlin, Takustr. 9, 14195 Berlin, Germany. utz.pape@molgen.mpg.de', 'Germany|Germany|Germany', 6, 'Algorithms|Computational Biology|DNA|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btp143', '19286833', 'Statistical assessment of cis-regulatory modules (CRMs) is a crucial task in computational biology. Usually, one concludes from exceptional co-occurrences of DNA motifs that the corresponding transcription factors (TFs) are cooperative. However, similar DNA motifs tend to co-occur in random sequences due to high probability of overlapping occurrences. Therefore, it is important to consider similarity of DNA motifs in the statistical assessment.'),
(74687, 2009, 'bio', 'SimMLST: simulation of multi-locus sequence typing data under a neutral model', 'Didelot, Xavier|Lawson, Daniel|Falush, Daniel', 'Department of Statistics, University of Warwick, Coventry, UK. X.Didelot@warwick.ac.uk|Department of Statistics, University of Warwick, Coventry, UK. X.Didelot@warwick.ac.uk|Department of Statistics, University of Warwick, Coventry, UK. X.Didelot@warwick.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 12, 'Algorithms|Bacterial Typing Techniques|Computer Simulation|Programming Languages|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btp145', '19286834', 'Multi-locus sequence typing (MLST) is a widely used method of characterization of bacterial isolates. It has been applied to over 50,000 isolates in over 50 different species. Here, we present a coalescent method to jointly simulate MLST data and the clonal genealogy that gave rise to the sample.'),
(74688, 2009, 'bio', 'A concanavalin A-like lectin domain in the CHS1/LYST protein, shared by members of the BEACH family', 'Burgess, Agathe|Mornon, Jean-Paul|de Saint-Basile, Geneviève|Callebaut, Isabelle', 'INSERM, U768, Paris, F-75015, France.|INSERM, U768, Paris, F-75015, France.|INSERM, U768, Paris, F-75015, France.|INSERM, U768, Paris, F-75015, France.', 'France|France|France|France', 28, 'Amino Acid Sequence|Binding Sites|Computational Biology|Concanavalin A|Databases, Protein|Molecular Sequence Data|Protein Folding|Protein Structure, Tertiary|Sequence Alignment|Vesicular Transport Proteins', 'Journal Article', '10.1093/bioinformatics/btp151', '19289442', 'CHS1/LYST, the causative protein of the Chediak-Higashi syndrome (CHS), belongs to the BEACH (named after BEige And Chediak-Higashi) family, which includes various large proteins sharing the same C-terminal domain architecture [a PH (Pleckstrin homology)-BEACH domain followed by WD repeats). Members of the BEACH family are generally defined as vesicle-trafficking regulatory proteins, but their functions remain to be determined at the molecular level. Here, using a panel of sensitive methods of sequence analysis, we show that the N-terminal regions of BEACH proteins contain an as yet not described domain, which shares striking similarities with clostridial neurotoxins and defines a novel family within the concanavalin A (ConA)-like lectin superfamily. These results suggest that the BEACH ConA-like lectin domain could be involved in oligosaccharide binding associated with protein traffic and sorting along the secretory pathway, especially in relation with components of the vesicle fusion machinery.'),
(74689, 2009, 'bio', 'A method and program for estimating graphical models for linkage disequilibrium that scale linearly with the number of loci, and their application to gene drop simulation', 'Thomas, Alun', 'Department of Biomedical Informatics, Division of Genetic Epidemiology, University of Utah, 391 Chipeta Way Suite D, Salt Lake City, UT 84108, USA. alun@genepi.med.utah.edu', 'United States', 9, 'Chromosome Mapping|Computational Biology|Internet|Linkage Disequilibrium|Models, Genetic|Polymorphism, Single Nucleotide|Programming Languages', 'Journal Article', '10.1093/bioinformatics/btp146', '19289443', 'Efficient models for genetic linkage disequilibrium (LD) are needed to enable appropriate statistical analysis of the dense, genome-wide single nucleotide polymorphism assays currently available.'),
(74690, 2009, 'bio', 'GS2: an efficiently computable measure of GO-based similarity of gene sets', 'Ruths, Troy|Ruths, Derek|Nakhleh, Luay', 'Department of Computer Science, Rice University, 6100 Main Street, MS 132, Houston, TX, USA. troy.ruths@rice.edu|Department of Computer Science, Rice University, 6100 Main Street, MS 132, Houston, TX, USA. troy.ruths@rice.edu|Department of Computer Science, Rice University, 6100 Main Street, MS 132, Houston, TX, USA. troy.ruths@rice.edu', 'United States|United States|United States', 31, 'Algorithms|Databases, Genetic|Gene Expression Profiling|Genes|Genomics|Internet|Software|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btp128', '19289444', 'The growing availability of genome-scale datasets has attracted increasing attention to the development of computational methods for automated inference of functional similarities among genes and their products. One class of such methods measures the functional similarity of genes based on their distance in the Gene Ontology (GO). To measure the functional relatedness of a gene set, these measures consider every pair of genes in the set, and the average of all pairwise distances is calculated. However, as more data becomes available and gene sets used for analysis become larger, such pair-based calculation becomes prohibitive.'),
(74691, 2009, 'bio', 'TopHat: discovering splice junctions with RNA-Seq', 'Trapnell, Cole|Pachter, Lior|Salzberg, Steven L', 'Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. cole@cs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. cole@cs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. cole@cs.umd.edu', 'United States|United States|United States', 7550, 'Algorithms|Gene Expression Profiling|Models, Genetic|RNA Splicing|RNA, Messenger|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btp120', '19289445', 'A new protocol for sequencing the messenger RNA in a cell, known as RNA-Seq, generates millions of short sequence fragments in a single run. These fragments, or reads, can be used to measure levels of gene expression and to identify novel splice variants of genes. However, current software for aligning RNA-Seq data to a genome relies on known splice junctions and cannot identify novel ones. TopHat is an efficient read-mapping algorithm designed to align reads from an RNA-Seq experiment to a reference genome without relying on known splice sites.'),
(74692, 2009, 'bio', 'Using multi-data hidden Markov models trained on local neighborhoods of protein structure to predict residue-residue contacts', 'Björkholm, Patrik|Daniluk, Pawel|Kryshtafovych, Andriy|Fidelis, Krzysztof|Andersson, Robin|Hvidsten, Torgeir R', 'The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 28, 'Computational Biology|Databases, Protein|Markov Chains|Models, Molecular|Protein Folding|Protein Structure, Secondary|Proteins', 'Journal Article', '10.1093/bioinformatics/btp149', '19289446', 'Correct prediction of residue-residue contacts in proteins that lack good templates with known structure would take ab initio protein structure prediction a large step forward. The lack of correct contacts, and in particular long-range contacts, is considered the main reason why these methods often fail.'),
(74693, 2009, 'bio', 'Transcriptionally active gene fragments derived from potentially fast-evolving donor genes in the rice genome', 'Wang, Xiangfeng|Yu, Zhihui|Yang, Xiaozeng|Deng, Xing-Wang|Li, Lei', 'Department of Molecular, Cell and Developmental Biology, Yale University, New Haven, CT 06520, USA.|Department of Molecular, Cell and Developmental Biology, Yale University, New Haven, CT 06520, USA.|Department of Molecular, Cell and Developmental Biology, Yale University, New Haven, CT 06520, USA.|Department of Molecular, Cell and Developmental Biology, Yale University, New Haven, CT 06520, USA.|Department of Molecular, Cell and Developmental Biology, Yale University, New Haven, CT 06520, USA.', 'United States|United States|United States|United States|United States', 3, 'DNA Transposable Elements|Evolution, Molecular|Gene Expression Profiling|Genome, Plant|Oryza|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btp147', '19289447', 'The unprecedented complexity of the transcriptomic data obtained in recent years creates opportunities for new genomic studies aimed at interpolating regulatory code of gene expression and tracing genome evolution. We report here the identification and characterization of a set of 851 intergenic loci that represent transcribed gene fragments (TGFs) ectopically duplicated from 1030 non-transposable element (non-TE) donor genes in the rice genome. We analyzed the genomic context of the TGFs and donor genes. We show that the TGFs have adopted transcriptional orientation and pattern independent of the donor genes. We further show that TGFs have undergone relaxed purifying selection, consistent with their being pseudogenized. We found that the donor genes, which are biased toward certain molecular functions, exhibit an accelerated evolution rate comparing to the genome average. Our results demonstrated a large number of actively TGFs in the rice genome and shed light on the origin, mode of action and function of the TGFs.'),
(74694, 2009, 'bio', 'Gaussian process regression bootstrapping: exploring the effects of uncertainty in time course data', 'Kirk, Paul D W|Stumpf, Michael P H', 'Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London SW7 2AZ, UK. paul.kirk@imperial.ac.uk|Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London SW7 2AZ, UK. paul.kirk@imperial.ac.uk', 'United Kingdom|United Kingdom', 47, 'Computational Biology|Gene Regulatory Networks|Kinetics|Models, Statistical|Regression Analysis|Signal Transduction|Uncertainty', 'Journal Article', '10.1093/bioinformatics/btp139', '19289448', 'Although widely accepted that high-throughput biological data are typically highly noisy, the effects that this uncertainty has upon the conclusions we draw from these data are often overlooked. However, in order to assign any degree of confidence to our conclusions, we must quantify these effects. Bootstrap resampling is one method by which this may be achieved. Here, we present a parametric bootstrapping approach for time-course data, in which Gaussian process regression (GPR) is used to fit a probabilistic model from which replicates may then be drawn. This approach implicitly allows the time dependence of the data to be taken into account, and is applicable to a wide range of problems.'),
(74695, 2009, 'bio', 'Synergy Disequilibrium Plots: graphical visualization of pairwise synergies and redundancies of SNPs with respect to a phenotype', 'Watkinson, John|Anastassiou, Dimitris', 'Center for Computational Biology and Bioinformatics, Department of Electrical Engineering, Columbia University, New York, NY 10027, USA.|Center for Computational Biology and Bioinformatics, Department of Electrical Engineering, Columbia University, New York, NY 10027, USA.', 'United States|United States', 3, 'Computational Biology|Computer Graphics|Genome-Wide Association Study|Haplotypes|Phenotype|Polymorphism, Single Nucleotide|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp159', '19297347', 'We present a visualization tool applied on genome-wide association data, revealing disease-associated haplotypes, epistatically interacting loci, as well as providing visual signatures of multivariate correlations of genetic markers with respect to a phenotype.'),
(74696, 2009, 'bio', 'Visualization of genomic data with the Hilbert curve', 'Anders, Simon', 'European Bioinformatics Institute (EMBL-EBI), Hinxton, CB10 1SD, UK. sanders@fs.tum.de', 'United Kingdom', 42, 'Computational Biology|Genome|Genomics|Information Storage and Retrieval|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btp152', '19297348', 'In many genomic studies, one works with genome-position-dependent data, e.g. ChIP-chip or ChIP-Seq scores. Using conventional tools, it can be difficult to get a good feel for the data, especially the distribution of features. This article argues that the so-called Hilbert curve visualization can complement genome browsers and help to get further insights into the structure of ones data. This is demonstrated with examples from different use cases. An open-source application, called HilbertVis, is presented that allows the user to produce and interactively explore such plots.'),
(74697, 2009, 'bio', 'DASher: a stand-alone protein sequence client for DAS, the Distributed Annotation System', 'Messina, David N|Sonnhammer, Erik L L', 'Stockholm Bioinformatics Centre, Stockholm University, 10691 Stockholm, Sweden.|Stockholm Bioinformatics Centre, Stockholm University, 10691 Stockholm, Sweden.', 'Sweden|Sweden', 6, 'Computational Biology|Databases, Protein|Programming Languages|Proteins|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp153', '19297349', 'The rise in biological sequence data has led to a proliferation of separate, specialized databases. While there is great value in having many independent annotations, it is critical that there be a way to integrate them in one combined view. The Distributed Annotation System (DAS) was developed for that very purpose. There are currently no DAS clients that are open source, specialized for aggregating and comparing protein sequence annotation, and that can run as a self-contained application outside of a web browser. The speed, flexibility and extensibility that come with a stand-alone application motivated us to create DASher, an open-source Java DAS client. Given a UniProt sequence identifier, DASher automatically queries DAS-supporting servers worldwide for any information on that sequence and then displays the annotations in an interactive viewer for easy comparison. DASher is a fast, Java-based DAS client optimized for viewing protein sequence annotation and compliant with the latest DAS protocol specification 1.53E.'),
(74698, 2009, 'bio', 'Artefacts and biases affecting the evaluation of scoring functions on decoy sets for protein structure prediction', 'Handl, Julia|Knowles, Joshua|Lovell, Simon C', 'Faculty of Life Sciences, University of Manchester, Manchester, UK.|Faculty of Life Sciences, University of Manchester, Manchester, UK.|Faculty of Life Sciences, University of Manchester, Manchester, UK.', 'United Kingdom|United Kingdom|United Kingdom', 19, 'Artifacts|Computational Biology|Databases, Protein|Protein Conformation|Protein Folding|Proteins', 'Journal Article', '10.1093/bioinformatics/btp150', '19297350', 'Decoy datasets, consisting of a solved protein structure and numerous alternative native-like structures, are in common use for the evaluation of scoring functions in protein structure prediction. Several pitfalls with the use of these datasets have been identified in the literature, as well as useful guidelines for generating more effective decoy datasets. We contribute to this ongoing discussion an empirical assessment of several decoy datasets commonly used in experimental studies.'),
(74699, 2009, 'bio', 'The PickPocket method for predicting binding specificities for receptors based on receptor pocket similarities: application to MHC-peptide binding', 'Zhang, Hao|Lund, Ole|Nielsen, Morten', 'Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby 2800, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby 2800, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby 2800, Denmark.', 'Denmark|Denmark|Denmark', 82, 'Amino Acid Sequence|Binding Sites|Computational Biology|Databases, Protein|Histocompatibility Antigens|Major Histocompatibility Complex|Molecular Sequence Data|Peptides|Protein Binding|Protein Interaction Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btp137', '19297351', 'Receptor-ligand interactions play an important role in controlling many biological systems. One prominent example is the binding of peptides to the major histocompatibility complex (MHC) molecules controlling the onset of cellular immune responses. Thousands of MHC allelic versions exist, making determination of the binding specificity for each variant experimentally infeasible. Here, we present a method that can extrapolate from variants with known binding specificity to those where no experimental data are available.'),
(74700, 2009, 'bio', 'Identifying functional modules using expression profiles and confidence-scored protein interactions', 'Ulitsky, Igor|Shamir, Ron', 'Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.|Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.', 'Israel|Israel', 87, 'DNA Damage|Databases, Protein|Gene Expression|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Proteins|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1093/bioinformatics/btp118', '19297352', 'Microarray-based gene expression studies have great potential but are frequently difficult to interpret due to their overwhelming dimensions. Recent studies have shown that the analysis of expression data can be improved by its integration with protein interaction networks, but the performance of these analyses has been hampered by the uneven quality of the interaction data.'),
(74701, 2009, 'bio', 'Automated diagnosis of LC-MS/MS performance', 'Xu, Hua|Freitas, Michael A', 'Proteomics and Informatics Services Facility, Research Resources Center, University of Illinois at Chicago, Chicago, IL 60612, USA. huaxu@uic.edu|Proteomics and Informatics Services Facility, Research Resources Center, University of Illinois at Chicago, Chicago, IL 60612, USA. huaxu@uic.edu', 'United States|United States', 15, 'Chromatography, Liquid|Databases, Protein|Electronic Data Processing|Proteome|Software|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btp155', '19304874', 'We report a software scheme for automated diagnosis of liquid chromatography tandem mass spectrometry (LC-MS/MS) system performance. The proposed software scheme provides a robust framework for establishing automated diagnosis of LC-MS/MS system performance for a variety of instruments and experiments. This schematic consists of four main software components: (i) data conversion, (ii) peptide identification, (iii) LC retention time analysis and (iv) system performance evaluation. The implementation of a standard approach for assessing LC-MS/MS system performance enables researchers to apply reliable metrics to assess their workflows performance over different batch experiments. Furthermore, the results from system diagnosis can provide feedback to the workflow to stop batch analysis if system performance falls below prescribed thresholds. A basic implementation of the approach based on the MassMatrix database search and LC retention time analysis programs is presented.'),
(74702, 2009, 'bio', 'Local RNA structure alignment with incomplete sequence', 'Kolbe, Diana L|Eddy, Sean R', 'HHMI Janelia Farm Research Campus, Ashburn, VA 20147, USA. kolbed@janelia.hhmi.org|HHMI Janelia Farm Research Campus, Ashburn, VA 20147, USA. kolbed@janelia.hhmi.org', 'United States|United States', 12, 'Algorithms|Databases, Genetic|Models, Molecular|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btp154', '19304875', 'Accuracy of automated structural RNA alignment is improved by using models that consider not only primary sequence but also secondary structure information. However, current RNA structural alignment approaches tend to perform poorly on incomplete sequence fragments, such as single reads from metagenomic environmental surveys, because nucleotides that are expected to be base paired are missing.'),
(74703, 2009, 'bio', 'The calibrated population resistance tool: standardized genotypic estimation of transmitted HIV-1 drug resistance', 'Gifford, Robert J|Liu, Tommy F|Rhee, Soo-Yon|Kiuchi, Mark|Hue, Stephane|Pillay, Deenan|Shafer, Robert W', 'Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, CA, USA. robjgiff@gmail.com|Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, CA, USA. robjgiff@gmail.com|Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, CA, USA. robjgiff@gmail.com|Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, CA, USA. robjgiff@gmail.com|Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, CA, USA. robjgiff@gmail.com|Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, CA, USA. robjgiff@gmail.com|Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, CA, USA. robjgiff@gmail.com', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Databases, Genetic|Drug Resistance, Viral|Genotype|HIV-1|Online Systems', 'Journal Article', '10.1093/bioinformatics/btp134', '19304876', 'The calibrated population resistance (CPR) tool is a web-accessible program for performing standardized genotypic estimation of transmitted HIV-1 drug resistance. The program is linked to the Stanford HIV drug resistance database and can additionally perform viral genotyping and algorithmic estimation of resistance to specific antiretroviral drugs.'),
(74704, 2009, 'bio', 'GNU MCSim: Bayesian statistical inference for SBML-coded systems biology models', 'Bois, Frédéric Y', 'Direction des Risques Chroniques, INERIS, Parc ALATA, BP2, F-60550, Verneuil en Halatte, France. frederic.bois@ineris.fr', 'France', 66, 'Bayes Theorem|Computational Biology|Monte Carlo Method|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btp162', '19304877', 'Statistical inference about the parameter values of complex models, such as the ones routinely developed in systems biology, is efficiently performed through Bayesian numerical techniques. In that framework, prior information and multiple levels of uncertainty can be seamlessly integrated. GNU MCSim was precisely developed to achieve those aims, in a general non-linear differential context. Starting with version 5.3.0, GNU MCSim reads in and simulates Systems Biology Markup Language models. Markov chain Monte Carlo simulations can be used to generate samples from the joint posterior distribution of the model parameters, given a dataset and prior distributions. Hierarchical statistical models can be used. Optimal design of experiments can also be investigated.'),
(74705, 2009, 'bio', 'Biopython: freely available Python tools for computational molecular biology and bioinformatics', 'Cock, Peter J A|Antao, Tiago|Chang, Jeffrey T|Chapman, Brad A|Cox, Cymon J|Dalke, Andrew|Friedberg, Iddo|Hamelryck, Thomas|Kauff, Frank|Wilczynski, Bartek|de Hoon, Michiel J L', 'Plant Pathology, SCRI, Invergowrie, Dundee, UK. peter.cock@scri.ac.uk|Plant Pathology, SCRI, Invergowrie, Dundee, UK. peter.cock@scri.ac.uk|Plant Pathology, SCRI, Invergowrie, Dundee, UK. peter.cock@scri.ac.uk|Plant Pathology, SCRI, Invergowrie, Dundee, UK. peter.cock@scri.ac.uk|Plant Pathology, SCRI, Invergowrie, Dundee, UK. peter.cock@scri.ac.uk|Plant Pathology, SCRI, Invergowrie, Dundee, UK. peter.cock@scri.ac.uk|Plant Pathology, SCRI, Invergowrie, Dundee, UK. peter.cock@scri.ac.uk|Plant Pathology, SCRI, Invergowrie, Dundee, UK. peter.cock@scri.ac.uk|Plant Pathology, SCRI, Invergowrie, Dundee, UK. peter.cock@scri.ac.uk|Plant Pathology, SCRI, Invergowrie, Dundee, UK. peter.cock@scri.ac.uk|Plant Pathology, SCRI, Invergowrie, Dundee, UK. peter.cock@scri.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 1425, 'Computational Biology|Databases, Factual|Internet|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btp163', '19304878', 'The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning.'),
(74706, 2009, 'bio', 'Evolutionary Trace Annotation Server: automated enzyme function prediction in protein structures using 3D templates', 'Ward, R Matthew|Venner, Eric|Daines, Bryce|Murray, Stephen|Erdin, Serkan|Kristensen, David M|Lichtarge, Olivier', 'Department of Molecular and Human Genetics, Program in Structural and Computational Biology and Molecular, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.|Department of Molecular and Human Genetics, Program in Structural and Computational Biology and Molecular, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.|Department of Molecular and Human Genetics, Program in Structural and Computational Biology and Molecular, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.|Department of Molecular and Human Genetics, Program in Structural and Computational Biology and Molecular, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.|Department of Molecular and Human Genetics, Program in Structural and Computational Biology and Molecular, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.|Department of Molecular and Human Genetics, Program in Structural and Computational Biology and Molecular, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.|Department of Molecular and Human Genetics, Program in Structural and Computational Biology and Molecular, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.', 'United States|United States|United States|United States|United States|United States|United States', 21, 'Computational Biology|Databases, Protein|Enzymes|Evolution, Molecular|Internet|Phylogeny|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btp160', '19307237', 'The Evolutionary Trace Annotation (ETA) Server predicts enzymatic activity. ETA starts with a structure of unknown function, such as those from structural genomics, and with no prior knowledge of its mechanism uses the phylogenetic Evolutionary Trace (ET) method to extract key functional residues and propose a function-associated 3D motif, called a 3D template. ETA then searches previously annotated structures for geometric template matches that suggest molecular and thus functional mimicry. In order to maximize the predictive value of these matches, ETA next applies distinctive specificity filters -- evolutionary similarity, function plurality and match reciprocity. In large scale controls on enzymes, prediction coverage is 43% but the positive predictive value rises to 92%, thus minimizing false annotations. Users may modify any search parameter, including the template. ETA thus expands the ET suite for protein structure annotation, and can contribute to the annotation efforts of metaservers.'),
(74707, 2009, 'bio', 'Statistical model for whole genome sequencing and its application to minimally invasive diagnosis of fetal genetic disease', 'Chu, Tianjiao|Bunce, Kimberly|Hogge, W Allen|Peters, David G', 'Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA 15213, USA.|Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA 15213, USA.|Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA 15213, USA.|Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA 15213, USA.', 'United States|United States|United States|United States', 30, 'Adult|Child, Preschool|DNA|Down Syndrome|Female|Fetal Diseases|Fetus|Genome, Human|Humans|Male|Models, Statistical|Pregnancy|Pregnancy Trimester, First|Prenatal Diagnosis|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btp156', '19307238', 'There is currently great interest in the development of methods for the minimally invasive diagnosis of fetal genetic disease using cell-free DNA from maternal plasma samples obtained in the first trimester of pregnancy. With the rapid development of high-throughput sequencing technology, the possibility of detecting the presence of trisomy fetal genomes in the maternal plasma DNA sample has recently been explored. The major concern of this whole genome sequencing approach is that, while detecting the karyotype of the fetal genome from the maternal plasma requires extremely high accuracy of copy number estimation, the majority of the available high-throughput sequencing technologies require polymerase chain reaction (PCR) and are subject to the substantial bias that is inherent to the PCR process. We introduce a novel and sophisticated statistical model for the whole genome sequencing data, and based on this model, develop a highly sensitive method of Minimally Invasive Karyotyping (MINK) for the diagnosis of the fetal genetic disease. Specifically we demonstrate, by applying our statistical method to ultra high-throughput whole sequencing data, that trisomy 21 can be detected in a minor (fetal) genome when it is mixed into a major (maternal) background genome at frequencies as low as 5%. This observation provides additional proof of concept and justification for the further development of this method towards its eventual clinical application. Here, we describe the statistical and experimental methods that illustrate this approach and discuss future directions for technical development and potential clinical applications.'),
(74708, 2009, 'bio', 'KEGGgraph: a graph approach to KEGG PATHWAY in R and bioconductor', 'Zhang, Jitao David|Wiemann, Stefan', 'Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), INF 580, Heidelberg, Germany. j.zhang@dkfz-heidelberg.de|Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), INF 580, Heidelberg, Germany. j.zhang@dkfz-heidelberg.de', 'Germany|Germany', 194, 'Computational Biology|Computer Graphics|Databases, Genetic|Genome|Humans|Models, Biological|Pancreatic Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btp167', '19307239', 'KEGG PATHWAY is a service of Kyoto Encyclopedia of Genes and Genomes (KEGG), constructing manually curated pathway maps that represent current knowledge on biological networks in graph models. While valuable graph tools have been implemented in R/Bioconductor, to our knowledge there is currently no software package to parse and analyze KEGG pathways with graph theory.'),
(74709, 2009, 'bio', 'SBML2L(A)T(E)X: conversion of SBML files into human-readable reports', 'Dräger, Andreas|Planatscher, Hannes|Motsou Wouamba, Dieudonné|Schröder, Adrian|Hucka, Michael|Endler, Lukas|Golebiewski, Martin|Müller, Wolfgang|Zell, Andreas', 'Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany. andreas.draeger@uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany. andreas.draeger@uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany. andreas.draeger@uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany. andreas.draeger@uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany. andreas.draeger@uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany. andreas.draeger@uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany. andreas.draeger@uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany. andreas.draeger@uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany. andreas.draeger@uni-tuebingen.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Database Management Systems|Humans|Programming Languages|Software|Systems Biology|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp170', '19307240', 'The XML-based Systems Biology Markup Language (SBML) has emerged as a standard for storage, communication and interchange of models in systems biology. As a machine-readable format XML is difficult for humans to read and understand. Many tools are available that visualize the reaction pathways stored in SBML files, but many components, e.g. unit declarations, complex kinetic equations or links to MIRIAM resources, are often not made visible in these diagrams. For a broader understanding of the models, support in scientific writing and error detection, a human-readable report of the complete model is needed. We present SBML2L(A)T(E)X, a Java-based stand-alone program to fill this gap. A convenient web service allows users to directly convert SBML to various formats, including DVI, L(A)T(E)X and PDF, and provides many settings for customization.'),
(74710, 2009, 'bio', 'BioconductorBuntu: a Linux distribution that implements a web-based DNA microarray analysis server', 'Geeleher, Paul|Morris, Dermot|Hinde, John P|Golden, Aaron', 'School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland. paul.geeleher@nuigalway.ie|School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland. paul.geeleher@nuigalway.ie|School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland. paul.geeleher@nuigalway.ie|School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland. paul.geeleher@nuigalway.ie', 'Ireland|Ireland|Ireland|Ireland', 0, 'DNA|Databases, Genetic|Gene Expression Profiling|Internet|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp165', '19307241', 'BioconductorBuntu is a custom distribution of Ubuntu Linux that automatically installs a server-side microarray processing environment, providing a user-friendly web-based GUI to many of the tools developed by the Bioconductor Project, accessible locally or across a network. System installation is via booting off a CD image or by using a Debian package provided to upgrade an existing Ubuntu installation. In its current version, several microarray analysis pipelines are supported including oligonucleotide, dual-or single-dye experiments, including post-processing with Gene Set Enrichment Analysis. BioconductorBuntu is designed to be extensible, by server-side integration of further relevant Bioconductor modules as required, facilitated by its straightforward underlying Python-based infrastructure. BioconductorBuntu offers an ideal environment for the development of processing procedures to facilitate the analysis of next-generation sequencing datasets.'),
(74711, 2009, 'bio', 'Infernal 10: inference of RNA alignments', 'Nawrocki, Eric P|Kolbe, Diana L|Eddy, Sean R', 'HHMI Janelia Farm Research Campus, Ashburn, VA 20147, USA. nawrockie@janelia.hhmi.org|HHMI Janelia Farm Research Campus, Ashburn, VA 20147, USA. nawrockie@janelia.hhmi.org|HHMI Janelia Farm Research Campus, Ashburn, VA 20147, USA. nawrockie@janelia.hhmi.org', 'United States|United States|United States', 852, 'Databases, Nucleic Acid|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btp157', '19307242', 'INFERNAL builds consensus RNA secondary structure profiles called covariance models (CMs), and uses them to search nucleic acid sequence databases for homologous RNAs, or to create new sequence- and structure-based multiple sequence alignments.'),
(74712, 2009, 'bio', 'A web application to perform linkage disequilibrium and linkage analyses on a computational grid', 'Hernández-Sánchez, Jules|Grunchec, Jean-Alain|Knott, Sara', 'Institute of Evolutionary Biology, University of Edinburgh, Kings Buildings, Ashworth Laboratories, Edinburgh, UK. jules.hernandez@ed.ac.uk|Institute of Evolutionary Biology, University of Edinburgh, Kings Buildings, Ashworth Laboratories, Edinburgh, UK. jules.hernandez@ed.ac.uk|Institute of Evolutionary Biology, University of Edinburgh, Kings Buildings, Ashworth Laboratories, Edinburgh, UK. jules.hernandez@ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Databases, Genetic|Genetic Linkage|Internet|Linkage Disequilibrium|Quantitative Trait Loci|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp171', '19318423', 'Unravelling the genetic architecture of complex traits requires large amounts of data, sophisticated models and large computational resources. The lack of user-friendly software incorporating all these requisites is delaying progress in the analysis of complex traits.'),
(74713, 2009, 'bio', 'Integrating shotgun proteomics and mRNA expression data to improve protein identification', 'Ramakrishnan, Smriti R|Vogel, Christine|Prince, John T|Li, Zhihua|Penalva, Luiz O|Myers, Margaret|Marcotte, Edward M|Miranker, Daniel P|Wang, Rong', 'Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA.|Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA.|Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA.|Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA.|Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA.|Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA.|Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA.|Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA.|Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Bayes Theorem|Databases, Protein|Humans|Proteins|Proteome|Proteomics|RNA, Messenger|Software|Tandem Mass Spectrometry|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp168', '19318424', 'Tandem mass spectrometry (MS/MS) offers fast and reliable characterization of complex protein mixtures, but suffers from low sensitivity in protein identification. In a typical shotgun proteomics experiment, it is assumed that all proteins are equally likely to be present. However, there is often other information available, e.g. the probability of a proteins presence is likely to correlate with its mRNA concentration.'),
(74714, 2009, 'bio', 'dCAS: a desktop application for cDNA sequence annotation', 'Guo, Yongjian|Ribeiro, Jose M C|Anderson, Jennifer M|Bour, Stephan', 'Bioinformatics and Computational Biosciences Branch, Office of Cyber Infrastructure and Computational Biology and Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA. guoyo@mail.nih.gov|Bioinformatics and Computational Biosciences Branch, Office of Cyber Infrastructure and Computational Biology and Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA. guoyo@mail.nih.gov|Bioinformatics and Computational Biosciences Branch, Office of Cyber Infrastructure and Computational Biology and Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA. guoyo@mail.nih.gov|Bioinformatics and Computational Biosciences Branch, Office of Cyber Infrastructure and Computational Biology and Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA. guoyo@mail.nih.gov', 'United States|United States|United States|United States', 43, 'Base Sequence|Computational Biology|DNA, Complementary|Databases, Genetic|Expressed Sequence Tags|Information Storage and Retrieval|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btp129', '19318425', 'Understanding gene regulation and expression is the key to the advancement of biology. EST sequence assembly and analysis provide unique benefits in this regard. We have developed a standalone application, dCAS (Desktop cDNA Annotation System), which performs automated EST cleaning, clustering, assembly and annotation on a desktop computer. Compared with other available tools, dCAS provides a more convenient and user-friendly solution to biologists for extracting biological meaning from sequence data.');
