INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91743, 2007, 'bmc', 'Weighted analysis of general microarray experiments', 'Sjögren, Anders|Kristiansson, Erik|Rudemo, Mats|Nerman, Olle', 'Mathematical Statistics, Chalmers University of Technology, 412 96 Göteborg, Sweden. anders.sjogren@math.chalmers.se|Mathematical Statistics, Chalmers University of Technology, 412 96 Göteborg, Sweden. anders.sjogren@math.chalmers.se|Mathematical Statistics, Chalmers University of Technology, 412 96 Göteborg, Sweden. anders.sjogren@math.chalmers.se|Mathematical Statistics, Chalmers University of Technology, 412 96 Göteborg, Sweden. anders.sjogren@math.chalmers.se', 'Sweden|Sweden|Sweden|Sweden', 0, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-8-387', '17937807', 'In DNA microarray experiments, measurements from different biological samples are often assumed to be independent and to have identical variance. For many datasets these assumptions have been shown to be invalid and typically lead to too optimistic p-values. A method called WAME has been proposed where a variance is estimated for each sample and a covariance is estimated for each pair of samples. The current version of WAME is, however, limited to experiments with paired design, e.g. two-channel microarrays.'),
(91744, 2007, 'bmc', 'Topology independent protein structural alignment', 'Dundas, Joe|Binkowski, T A|DasGupta, Bhaskar|Liang, Jie', 'Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607-7053, USA. jdunda1@uic.edu|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607-7053, USA. jdunda1@uic.edu|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607-7053, USA. jdunda1@uic.edu|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607-7053, USA. jdunda1@uic.edu', 'United States|United States|United States|United States', 0, 'Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-8-388', '17937816', 'Identifying structurally similar proteins with different chain topologies can aid studies in homology modeling, protein folding, protein design, and protein evolution. These include circular permuted protein structures, and the more general cases of non-cyclic permutations between similar structures, which are related by non-topological rearrangement beyond circular permutation. We present a method based on an approximation algorithm that finds sequence-order independent structural alignments that are close to optimal. We formulate the structural alignment problem as a special case of the maximum-weight independent set problem, and solve this computationally intensive problem approximately by iteratively solving relaxations of a corresponding integer programming problem. The resulting structural alignment is sequence order independent. Our method is also insensitive to insertions, deletions, and gaps.'),
(91745, 2007, 'bmc', 'MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data', 'Moore, Eider B|Poliakov, Andrew V|Lincoln, Peter|Brinkley, James F', 'Structural Informatics Group, Department of Biological Structure, University of Washington, Seattle, USA. eider@u.washington.edu|Structural Informatics Group, Department of Biological Structure, University of Washington, Seattle, USA. eider@u.washington.edu|Structural Informatics Group, Department of Biological Structure, University of Washington, Seattle, USA. eider@u.washington.edu|Structural Informatics Group, Department of Biological Structure, University of Washington, Seattle, USA. eider@u.washington.edu', 'United States|United States|United States|United States', 12, 'Algorithms|Brain|Brain Mapping|Computer Graphics|Databases, Factual|Diagnostic Imaging|Humans|Image Interpretation, Computer-Assisted|Neurosciences|Software|Subtraction Technique|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-389', '17937818', 'Three-dimensional (3-D) visualization of multimodality neuroimaging data provides a powerful technique for viewing the relationship between structure and function. A number of applications are available that include some aspect of 3-D visualization, including both free and commercial products. These applications range from highly specific programs for a single modality, to general purpose toolkits that include many image processing functions in addition to visualization. However, few if any of these combine both stand-alone and remote multi-modality visualization in an open source, portable and extensible tool that is easy to install and use, yet can be included as a component of a larger information system.'),
(91746, 2007, 'bmc', 'On the detection of functionally coherent groups of protein domains with an extension to protein annotation', 'McLaughlin, William A|Chen, Ken|Hou, Tingjun|Wang, Wei', 'Department of Chemistry and Biochemistry, Center for Theoretical Biological Physics, University of California, San Diego, 9500 Gilman Drive La Jolla, CA 92093-0359, USA. wimclaug@ucsd.edu|Department of Chemistry and Biochemistry, Center for Theoretical Biological Physics, University of California, San Diego, 9500 Gilman Drive La Jolla, CA 92093-0359, USA. wimclaug@ucsd.edu|Department of Chemistry and Biochemistry, Center for Theoretical Biological Physics, University of California, San Diego, 9500 Gilman Drive La Jolla, CA 92093-0359, USA. wimclaug@ucsd.edu|Department of Chemistry and Biochemistry, Center for Theoretical Biological Physics, University of California, San Diego, 9500 Gilman Drive La Jolla, CA 92093-0359, USA. wimclaug@ucsd.edu', 'United States|United States|United States|United States', 3, 'Algorithms|Amino Acid Motifs|Databases, Genetic|Databases, Protein|Forecasting|Pattern Recognition, Automated|Protein Binding|Protein Conformation|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Proteomics|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Structural Homology, Protein|Structure-Activity Relationship|Terminology as Topic', 'Journal Article', '10.1186/1471-2105-8-390', '17937820', 'Protein domains coordinate to perform multifaceted cellular functions, and domain combinations serve as the functional building blocks of the cell. The available methods to identify functional domain combinations are limited in their scope, e.g. to the identification of combinations falling within individual proteins or within specific regions in a translated genome. Further effort is needed to identify groups of domains that span across two or more proteins and are linked by a cooperative function. Such functional domain combinations can be useful for protein annotation.'),
(91747, 2007, 'bmc', 'Analysis on multi-domain cooperation for predicting protein-protein interactions', 'Wang, Rui-Sheng|Wang, Yong|Wu, Ling-Yun|Zhang, Xiang-Sun|Chen, Luonan', 'School of Information, Renmin University of China, Beijing 100872, China. wangrsh@amss.ac.cn|School of Information, Renmin University of China, Beijing 100872, China. wangrsh@amss.ac.cn|School of Information, Renmin University of China, Beijing 100872, China. wangrsh@amss.ac.cn|School of Information, Renmin University of China, Beijing 100872, China. wangrsh@amss.ac.cn|School of Information, Renmin University of China, Beijing 100872, China. wangrsh@amss.ac.cn', 'China|China|China|China|China', 0, 'Animals|Binding Sites|Computational Biology|Databases, Protein|Fungal Proteins|Humans|Models, Molecular|Predictive Value of Tests|Programming, Linear|Protein Binding|Protein Interaction Domains and Motifs|Protein Interaction Mapping', 'Journal Article', '10.1186/1471-2105-8-391', '17937822', 'Domains are the basic functional units of proteins. It is believed that protein-protein interactions are realized through domain interactions. Revealing multi-domain cooperation can provide deep insights into the essential mechanism of protein-protein interactions at the domain level and be further exploited to improve the accuracy of protein interaction prediction.'),
(91748, 2007, 'bmc', 'Improved human disease candidate gene prioritization using mouse phenotype', 'Chen, Jing|Xu, Huan|Aronow, Bruce J|Jegga, Anil G', 'Division of Biomedical Informatics, Cincinnati Childrens Hospital Medical Center, Cincinnati, USA. Jing.Chen@cchmc.org|Division of Biomedical Informatics, Cincinnati Childrens Hospital Medical Center, Cincinnati, USA. Jing.Chen@cchmc.org|Division of Biomedical Informatics, Cincinnati Childrens Hospital Medical Center, Cincinnati, USA. Jing.Chen@cchmc.org|Division of Biomedical Informatics, Cincinnati Childrens Hospital Medical Center, Cincinnati, USA. Jing.Chen@cchmc.org', 'United States|United States|United States|United States', 157, 'Algorithms|Animals|Chromosome Mapping|Genetic Predisposition to Disease|Humans|Linkage Disequilibrium|Mice|Phenotype|Species Specificity', 'Journal Article', '10.1186/1471-2105-8-392', '17939863', 'The majority of common diseases are multi-factorial and modified by genetically and mechanistically complex polygenic interactions and environmental factors. High-throughput genome-wide studies like linkage analysis and gene expression profiling, tend to be most useful for classification and characterization but do not provide sufficient information to identify or prioritize specific disease causal genes.'),
(91749, 2007, 'bmc', 'Local Renyi entropic profiles of DNA sequences', 'Vinga, Susana|Almeida, Jonas S', 'Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento (INESC-ID), R, Alves Redol 9, 1000-029 Lisboa, Portugal. svinga@kdbio.inesc-id.pt|Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento (INESC-ID), R, Alves Redol 9, 1000-029 Lisboa, Portugal. svinga@kdbio.inesc-id.pt', 'Portugal|Portugal', 0, 'Base Sequence|Conserved Sequence|Data Interpretation, Statistical|Entropy|Escherichia coli|Game Theory|Genome, Bacterial|Haemophilus influenzae|Markov Chains|Pattern Recognition, Automated|Predictive Value of Tests|Sequence Analysis, DNA|Software|Uncertainty', 'Journal Article', '10.1186/1471-2105-8-393', '17939871', 'In a recent report the authors presented a new measure of continuous entropy for DNA sequences, which allows the estimation of their randomness level. The definition therein explored was based on the Rényi entropy of probability density estimation (pdf) using the Parzens window method and applied to Chaos Game Representation/Universal Sequence Maps (CGR/USM). Subsequent work proposed a fractal pdf kernel as a more exact solution for the iterated map representation. This report extends the concepts of continuous entropy by defining DNA sequence entropic profiles using the new pdf estimations to refine the density estimation of motifs.'),
(91750, 2007, 'bmc', 'A response to Yu et al A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array, BMC Bioinformatics 2007, 8: 145', 'Rueda, Oscar M|Diaz-Uriarte, Ramon', 'Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento (INESC-ID), R, Alves Redol 9, 1000-029 Lisboa, Portugal. svinga@kdbio.inesc-id.pt|Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento (INESC-ID), R, Alves Redol 9, 1000-029 Lisboa, Portugal. svinga@kdbio.inesc-id.pt', 'Portugal|Portugal', 0, 'Algorithms|Chromosome Breakage|Gene Amplification|Gene Deletion|Gene Expression Profiling|Genome, Human|Humans|Markov Chains|Monte Carlo Method|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Reference Standards|Research Design', 'Comment', '10.1186/1471-2105-8-394', '17939873', 'Yu et al. (BMC Bioinformatics 2007,8: 145+) have recently compared the performance of several methods for the detection of genomic amplification and deletion breakpoints using data from high-density single nucleotide polymorphism arrays. One of the methods compared is our non-homogenous Hidden Markov Model approach. Our approach uses Markov Chain Monte Carlo for inference, but Yu et al. ran the sampler for a severely insufficient number of iterations for a Markov Chain Monte Carlo-based method. Moreover, they did not use the appropriate reference level for the non-altered state.'),
(91751, 2007, 'bmc', 'Large scale clustering of protein sequences with FORCE -A layout based heuristic for weighted cluster editing', 'Wittkop, Tobias|Baumbach, Jan|Lobo, Francisco P|Rahmann, Sven', 'Computational Methods for Emerging Technologies, Bielefeld University, Bielefeld, Germany. tobias.wittkop@cebitec.uni-bielefeld.de|Computational Methods for Emerging Technologies, Bielefeld University, Bielefeld, Germany. tobias.wittkop@cebitec.uni-bielefeld.de|Computational Methods for Emerging Technologies, Bielefeld University, Bielefeld, Germany. tobias.wittkop@cebitec.uni-bielefeld.de|Computational Methods for Emerging Technologies, Bielefeld University, Bielefeld, Germany. tobias.wittkop@cebitec.uni-bielefeld.de', 'Germany|Germany|Germany|Germany', 56, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Cluster Analysis|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-8-396', '17941985', 'Detecting groups of functionally related proteins from their amino acid sequence alone has been a long-standing challenge in computational genome research. Several clustering approaches, following different strategies, have been published to attack this problem. Today, new sequencing technologies provide huge amounts of sequence data that has to be efficiently clustered with constant or increased accuracy, at increased speed.'),
(91752, 2007, 'bmc', 'Assessing the ability of sequence-based methods to provide functional insight within membrane integral proteins: a case study analyzing the neurotransmitter/Na+ symporter family', 'Livesay, Dennis R|Kidd, Patrick D|Eskandari, Sepehr|Roshan, Usman', 'Department of Computer Science and Bioinformatics Research Center, University of North Carolina at Charlotte, Charlotte, NC 28262, USA. drlivesa@uncc.edu|Department of Computer Science and Bioinformatics Research Center, University of North Carolina at Charlotte, Charlotte, NC 28262, USA. drlivesa@uncc.edu|Department of Computer Science and Bioinformatics Research Center, University of North Carolina at Charlotte, Charlotte, NC 28262, USA. drlivesa@uncc.edu|Department of Computer Science and Bioinformatics Research Center, University of North Carolina at Charlotte, Charlotte, NC 28262, USA. drlivesa@uncc.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|Models, Chemical|Models, Molecular|Plasma Membrane Neurotransmitter Transport Proteins|Protein Conformation|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-8-397', '17941992', 'Efforts to predict functional sites from globular proteins is increasingly common, however, the most successful of these methods generally require structural insight. Unfortunately, despite several recent technological advances, structural coverage of membrane integral proteins continues to be sparse. ConSequently, sequence-based methods represent an important alternative to illuminate functional roles. In this report, we critically examine the ability of several computational methods to provide functional insight within two specific areas. First, can phylogenomic methods accurately describe the functional diversity across a membrane integral protein family? And second, can sequence-based strategies accurately predict key functional sites? Due to the presence of a recently solved structure and a vast amount of experimental mutagenesis data, the neurotransmitter/Na+ symporter (NSS) family is an ideal model system to assess the quality of our predictions.'),
(91753, 2007, 'bmc', 'Strainer: software for analysis of population variation in community genomic datasets', 'Eppley, John M|Tyson, Gene W|Getz, Wayne M|Banfield, Jillian F', 'Department of Environmental Science, Policy and Management, University of California, Berkeley, CA 94720, USA. jmeppley@gmail.com|Department of Environmental Science, Policy and Management, University of California, Berkeley, CA 94720, USA. jmeppley@gmail.com|Department of Environmental Science, Policy and Management, University of California, Berkeley, CA 94720, USA. jmeppley@gmail.com|Department of Environmental Science, Policy and Management, University of California, Berkeley, CA 94720, USA. jmeppley@gmail.com', 'United States|United States|United States|United States', 29, 'Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Databases, Genetic|Genetic Variation|Genetics, Population|Genome, Bacterial|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-8-398', '17941997', 'Metagenomic analyses of microbial communities that are comprehensive enough to provide multiple samples of most loci in the genomes of the dominant organism types will also reveal patterns of genetic variation within natural populations. New bioinformatic tools will enable visualization and comprehensive analysis of this sequence variation and inference of recent evolutionary and ecological processes.'),
(91754, 2007, 'bmc', 'fREDUCE: detection of degenerate regulatory elements using correlation with expression', 'Wu, Randy Z|Chaivorapol, Christina|Zheng, Jiashun|Li, Hao|Liang, Shoudan', 'Department of Biochemistry and Biophysics, UCSF, 1700 4th Street, San Francisco, CA 94143-2542, USA. rwu@genome.ucsf.edu|Department of Biochemistry and Biophysics, UCSF, 1700 4th Street, San Francisco, CA 94143-2542, USA. rwu@genome.ucsf.edu|Department of Biochemistry and Biophysics, UCSF, 1700 4th Street, San Francisco, CA 94143-2542, USA. rwu@genome.ucsf.edu|Department of Biochemistry and Biophysics, UCSF, 1700 4th Street, San Francisco, CA 94143-2542, USA. rwu@genome.ucsf.edu|Department of Biochemistry and Biophysics, UCSF, 1700 4th Street, San Francisco, CA 94143-2542, USA. rwu@genome.ucsf.edu', 'United States|United States|United States|United States|United States', 13, 'Algorithms|Amino Acid Motifs|Base Sequence|Binding Sites|Computational Biology|Gene Expression Profiling|Genomics|Hepatocytes|Humans|Regulatory Sequences, Nucleic Acid|Saccharomyces cerevisiae|Substrate Specificity|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-8-399', '17941998', 'The precision of transcriptional regulation is made possible by the specificity of physical interactions between transcription factors and their cognate binding sites on DNA. A major challenge is to decipher transcription factor binding sites from sequence and functional genomic data using computational means. While current methods can detect strong binding sites, they are less sensitive to degenerate motifs.'),
(91755, 2007, 'bmc', 'CATMA, a comprehensive genome-scale resource for silencing and transcript profiling of Arabidopsis genes', 'Sclep, Gert|Allemeersch, Joke|Liechti, Robin|De Meyer, Björn|Beynon, Jim|Bhalerao, Rishikesh|Moreau, Yves|Nietfeld, Wilfried|Renou, Jean-Pierre|Reymond, Philippe|Kuiper, Martin Tr|Hilson, Pierre', 'Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Ghent, Belgium. gert.sclep@tecnoparco.org|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Ghent, Belgium. gert.sclep@tecnoparco.org|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Ghent, Belgium. gert.sclep@tecnoparco.org|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Ghent, Belgium. gert.sclep@tecnoparco.org|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Ghent, Belgium. gert.sclep@tecnoparco.org|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Ghent, Belgium. gert.sclep@tecnoparco.org|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Ghent, Belgium. gert.sclep@tecnoparco.org|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Ghent, Belgium. gert.sclep@tecnoparco.org|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Ghent, Belgium. gert.sclep@tecnoparco.org|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Ghent, Belgium. gert.sclep@tecnoparco.org|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Ghent, Belgium. gert.sclep@tecnoparco.org|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Ghent, Belgium. gert.sclep@tecnoparco.org', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Arabidopsis Proteins|Base Sequence|Chromosome Mapping|Database Management Systems|Databases, Genetic|Europe|Expressed Sequence Tags|Gene Silencing|Genome, Plant|Molecular Sequence Data|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-400', '17945016', 'The Complete Arabidopsis Transcript MicroArray (CATMA) initiative combines the efforts of laboratories in eight European countries 1 to deliver gene-specific sequence tags (GSTs) for the Arabidopsis research community. The CATMA initiative offers the power and flexibility to regularly update the GST collection according to evolving knowledge about the gene repertoire. These GST amplicons can easily be reamplified and shared, subsets can be picked at will to print dedicated arrays, and the GSTs can be cloned and used for other functional studies. This ongoing initiative has already produced approximately 24,000 GSTs that have been made publicly available for spotted microarray printing and RNA interference.'),
(91756, 2007, 'bmc', 'The Protein Identifier Cross-Referencing (PICR) service: reconciling protein identifiers across multiple source databases', 'Côté, Richard G|Jones, Philip|Martens, Lennart|Kerrien, Samuel|Reisinger, Florian|Lin, Quan|Leinonen, Rasko|Apweiler, Rolf|Hermjakob, Henning', 'European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1QY, UK. rcote@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1QY, UK. rcote@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1QY, UK. rcote@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1QY, UK. rcote@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1QY, UK. rcote@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1QY, UK. rcote@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1QY, UK. rcote@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1QY, UK. rcote@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1QY, UK. rcote@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 94, 'Algorithms|Amino Acid Sequence|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-401', '17945017', 'Each major protein database uses its own conventions when assigning protein identifiers. Resolving the various, potentially unstable, identifiers that refer to identical proteins is a major challenge. This is a common problem when attempting to unify datasets that have been annotated with proteins from multiple data sources or querying data providers with one flavour of protein identifiers when the source database uses another. Partial solutions for protein identifier mapping exist but they are limited to specific species or techniques and to a very small number of databases. As a result, we have not found a solution that is generic enough and broad enough in mapping scope to suit our needs.'),
(91757, 2007, 'bmc', 'Modeling SAGE tag formation and its effects on data interpretation within a Bayesian framework', 'Gilchrist, Michael A|Qin, Hong|Zaretzki, Russell', 'Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996, USA. mikeg@utk.edu|Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996, USA. mikeg@utk.edu|Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996, USA. mikeg@utk.edu', 'United States|United States|United States', 5, 'Bayes Theorem|Computer Simulation|Data Interpretation, Statistical|Databases, Genetic|Expressed Sequence Tags|Gene Expression Profiling|Models, Genetic|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-403', '17945026', 'Serial Analysis of Gene Expression (SAGE) is a high-throughput method for inferring mRNA expression levels from the experimentally generated sequence based tags. Standard analyses of SAGE data, however, ignore the fact that the probability of generating an observable tag varies across genes and between experiments. As a consequence, these analyses result in biased estimators and posterior probability intervals for gene expression levels in the transcriptome.'),
(91758, 2007, 'bmc', 'Automated group assignment in large phylogenetic trees using GRUNT: GRouping, Ungrouping, Naming Tool', 'Dalevi, Daniel|Desantis, Todd Z|Fredslund, Jakob|Andersen, Gary L|Markowitz, Victor M|Hugenholtz, Philip', 'Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720,USA. DDalevi@lbl.gov|Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720,USA. DDalevi@lbl.gov|Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720,USA. DDalevi@lbl.gov|Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720,USA. DDalevi@lbl.gov|Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720,USA. DDalevi@lbl.gov|Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720,USA. DDalevi@lbl.gov', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Classification|Database Management Systems|Databases, Nucleic Acid|Phylogeny|RNA, Ribosomal, 16S|Software', 'Journal Article', '10.1186/1471-2105-8-402', '17949484', 'Accurate taxonomy is best maintained if species are arranged as hierarchical groups in phylogenetic trees. This is especially important as trees grow larger as a consequence of a rapidly expanding sequence database. Hierarchical group names are typically manually assigned in trees, an approach that becomes unfeasible for very large topologies.'),
(91759, 2007, 'bmc', 'Application of amino acid occurrence for discriminating different folding types of globular proteins', 'Taguchi, Y-h|Gromiha, M Michael', 'Department of Physics, Faculty of Science and Technology, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan. tag@granular.com|Department of Physics, Faculty of Science and Technology, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan. tag@granular.com', 'Japan|Japan', 0, 'Algorithms|Amino Acids|Methods|Models, Molecular|Protein Conformation|Protein Folding|Proteins', 'Evaluation Studies', '10.1186/1471-2105-8-404', '17953741', 'Predicting the three-dimensional structure of a protein from its amino acid sequence is a long-standing goal in computational/molecular biology. The discrimination of different structural classes and folding types are intermediate steps in protein structure prediction.'),
(91760, 2007, 'bmc', 'AxPcoords & parallel AxParafit: statistical co-phylogenetic analyses on thousands of taxa', 'Stamatakis, Alexandros|Auch, Alexander F|Meier-Kolthoff, Jan|Göker, Markus', 'Ecole Polytechnique Fédérale de Lausanne, School of Computer & Communication Sciences, Laboratory for Computational Biology and Bioinformatics STATION 14, CH-1015 Lausanne, Switzerland. Alexandros.Stamatakis@epfl.ch|Ecole Polytechnique Fédérale de Lausanne, School of Computer & Communication Sciences, Laboratory for Computational Biology and Bioinformatics STATION 14, CH-1015 Lausanne, Switzerland. Alexandros.Stamatakis@epfl.ch|Ecole Polytechnique Fédérale de Lausanne, School of Computer & Communication Sciences, Laboratory for Computational Biology and Bioinformatics STATION 14, CH-1015 Lausanne, Switzerland. Alexandros.Stamatakis@epfl.ch|Ecole Polytechnique Fédérale de Lausanne, School of Computer & Communication Sciences, Laboratory for Computational Biology and Bioinformatics STATION 14, CH-1015 Lausanne, Switzerland. Alexandros.Stamatakis@epfl.ch', 'Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Computer Simulation|Data Interpretation, Statistical|Evolution, Molecular|Models, Genetic|Models, Statistical|Molecular Sequence Data|Phylogeny|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-8-405', '17953748', 'Current tools for Co-phylogenetic analyses are not able to cope with the continuous accumulation of phylogenetic data. The sophisticated statistical test for host-parasite co-phylogenetic analyses implemented in Parafit does not allow it to handle large datasets in reasonable times. The Parafit and DistPCoA programs are the by far most compute-intensive components of the Parafit analysis pipeline. We present AxParafit and AxPcoords (Ax stands for Accelerated) which are highly optimized versions of Parafit and DistPCoA respectively.'),
(91761, 2007, 'bmc', 'MetaLook: a 3D visualisation software for marine ecological genomics', 'Lombardot, Thierry|Kottmann, Renzo|Giuliani, Gregory|de Bono, Andrea|Addor, Nans|Glöckner, Frank Oliver', 'Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. tlombard@mpi-bremen.de|Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. tlombard@mpi-bremen.de|Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. tlombard@mpi-bremen.de|Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. tlombard@mpi-bremen.de|Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. tlombard@mpi-bremen.de|Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. tlombard@mpi-bremen.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 6, 'Animals|Chromosome Mapping|Computer Graphics|Ecology|Genomics|Imaging, Three-Dimensional|Marine Biology|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-406', '17953757', 'Marine ecological genomics can be defined as the application of genomic sciences to understand the structure and function of marine ecosystems. In this field of research, the analysis of genomes and metagenomes of environmental relevance must take into account the corresponding habitat (contextual) data, e.g. water depth, physical and chemical parameters. The creation of specialised software tools and databases is requisite to allow this new kind of integrated analysis.'),
(91762, 2007, 'bmc', 'Bioinformatic identification of novel putative photoreceptor specific cis-elements', 'Danko, Charles G|McIlvain, Vera A|Qin, Maochun|Knox, Barry E|Pertsov, Arkady M', 'Department of Pharmacology, SUNY Upstate Medical University, Syracuse, NY, USA. dankoc@gmail.com|Department of Pharmacology, SUNY Upstate Medical University, Syracuse, NY, USA. dankoc@gmail.com|Department of Pharmacology, SUNY Upstate Medical University, Syracuse, NY, USA. dankoc@gmail.com|Department of Pharmacology, SUNY Upstate Medical University, Syracuse, NY, USA. dankoc@gmail.com|Department of Pharmacology, SUNY Upstate Medical University, Syracuse, NY, USA. dankoc@gmail.com', 'United States|United States|United States|United States|United States', 3, 'Animals|Base Sequence|Computational Biology|Conserved Sequence|Mice|Molecular Sequence Data|Photoreceptor Cells|Promoter Regions, Genetic|Proteome|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-407', '17953763', 'Cell specific gene expression is largely regulated by different combinations of transcription factors that bind cis-elements in the upstream promoter sequence. However, experimental detection of cis-elements is difficult, expensive, and time-consuming. This provides a motivation for developing bioinformatic methods to identify cis-elements that could prioritize future experimental studies. Here, we use motif discovery algorithms to predict transcription factor binding sites involved in regulating the differences between murine rod and cone photoreceptor populations.'),
(91763, 2007, 'bmc', 'Growing functional modules from a seed protein via integration of protein interaction and gene expression data', 'Maraziotis, Ioannis A|Dimitrakopoulou, Konstantina|Bezerianos, Anastasios', 'Department of Medical Physics, School of Medicine, University of Patras, GR26500 Patras, Greece. imarazi@heart.med.upatras.gr|Department of Medical Physics, School of Medicine, University of Patras, GR26500 Patras, Greece. imarazi@heart.med.upatras.gr|Department of Medical Physics, School of Medicine, University of Patras, GR26500 Patras, Greece. imarazi@heart.med.upatras.gr', 'Greece|Greece|Greece', 69, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computer Graphics|Databases, Protein|Gene Expression|Gene Expression Profiling|Models, Biological|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Protein Interaction Mapping|Proteins|Proteomics|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Systems Biology', 'Journal Article', '10.1186/1471-2105-8-408', '17956603', 'Nowadays modern biology aims at unravelling the strands of complex biological structures such as the protein-protein interaction (PPI) networks. A key concept in the organization of PPI networks is the existence of dense subnetworks (functional modules) in them. In recent approaches clustering algorithms were applied at these networks and the resulting subnetworks were evaluated by estimating the coverage of well-established protein complexes they contained. However, most of these algorithms elaborate on an unweighted graph structure which in turn fails to elevate those interactions that would contribute to the construction of biologically more valid and coherent functional modules.'),
(91764, 2007, 'bmc', 'Absolute estimation of initial concentrations of amplicon in a real-time RT-PCR process', 'Smith, Marjo V|Miller, Chris R|Kohn, Michael|Walker, Nigel J|Portier, Chris J', 'Constella Group, Suite 200, 2605 Meridian Pky, Durham, NC, USA. msmith@constellagroup.com|Constella Group, Suite 200, 2605 Meridian Pky, Durham, NC, USA. msmith@constellagroup.com|Constella Group, Suite 200, 2605 Meridian Pky, Durham, NC, USA. msmith@constellagroup.com|Constella Group, Suite 200, 2605 Meridian Pky, Durham, NC, USA. msmith@constellagroup.com|Constella Group, Suite 200, 2605 Meridian Pky, Durham, NC, USA. msmith@constellagroup.com', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|Computer Systems|DNA|Models, Chemical|Models, Genetic|Polymerase Chain Reaction|Reverse Transcriptase Polymerase Chain Reaction', 'Journal Article', '10.1186/1471-2105-8-409', '17956631', 'Since real time PCR was first developed, several approaches to estimating the initial quantity of template in an RT-PCR reaction have been tried. While initially only the early thermal cycles corresponding to exponential duplication were used, lately there has been an effort to use all of the cycles in a PCR. The efforts have included both fitting empirical sigmoid curves and more elaborate mechanistic models that explore the chemical reactions taking place during each cycle. The more elaborate mechanistic models require many more parameters than can be fit from a single amplification, while the empirical models provide little insight and are difficult to tailor to specific reactants.'),
(91765, 2007, 'bmc', 'Features generated for computational splice-site prediction correspond to functional elements', 'Dogan, Rezarta Islamaj|Getoor, Lise|Wilbur, W John|Mount, Stephen M', 'Computer Science Department, University of Maryland, College Park, MD 20742, USA. rezarta@cs.umd.edu|Computer Science Department, University of Maryland, College Park, MD 20742, USA. rezarta@cs.umd.edu|Computer Science Department, University of Maryland, College Park, MD 20742, USA. rezarta@cs.umd.edu|Computer Science Department, University of Maryland, College Park, MD 20742, USA. rezarta@cs.umd.edu', 'United States|United States|United States|United States', 0, 'Computational Biology|Humans|Predictive Value of Tests|RNA Splice Sites|RNA, Messenger', 'Journal Article', '10.1186/1471-2105-8-410', '17958908', 'Accurate selection of splice sites during the splicing of precursors to messenger RNA requires both relatively well-characterized signals at the splice sites and auxiliary signals in the adjacent exons and introns. We previously described a feature generation algorithm (FGA) that is capable of achieving high classification accuracy on human 3 splice sites. In this paper, we extend the splice-site prediction to 5 splice sites and explore the generated features for biologically meaningful splicing signals.'),
(91766, 2007, 'bmc', 'Estimating genealogies from linked marker data: a Bayesian approach', 'Gasbarra, Dario|Pirinen, Matti|Sillanpää, Mikko J|Arjas, Elja', 'Department of Mathematics and Statistics, University of Helsinki, Finland. dag@rni.helsinki.fi|Department of Mathematics and Statistics, University of Helsinki, Finland. dag@rni.helsinki.fi|Department of Mathematics and Statistics, University of Helsinki, Finland. dag@rni.helsinki.fi|Department of Mathematics and Statistics, University of Helsinki, Finland. dag@rni.helsinki.fi', 'Finland|Finland|Finland|Finland', 8, 'Algorithms|Alleles|Bayes Theorem|Chromosome Mapping|Data Interpretation, Statistical|Female|Founder Effect|Gene Frequency|Genetic Linkage|Genetic Markers|Genetics, Population|Haplotypes|Humans|Male|Markov Chains|Models, Genetic|Monte Carlo Method|Pedigree|Quantitative Trait Loci', 'Journal Article', '10.1186/1471-2105-8-411', '17961219', 'Answers to several fundamental questions in statistical genetics would ideally require knowledge of the ancestral pedigree and of the gene flow therein. A few examples of such questions are haplotype estimation, relatedness and relationship estimation, gene mapping by combining pedigree and linkage disequilibrium information, and estimation of population structure.'),
(91767, 2007, 'bmc', 'Reproducibility of microarray data: a further analysis of microarray quality control (MAQC) data', 'Chen, James J|Hsueh, Huey-Miin|Delongchamp, Robert R|Lin, Chien-Ju|Tsai, Chen-An', 'Division of Personalized Nutrition and Medicine, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 72079, USA. jamesj.chen@fda.hhs.gov|Division of Personalized Nutrition and Medicine, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 72079, USA. jamesj.chen@fda.hhs.gov|Division of Personalized Nutrition and Medicine, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 72079, USA. jamesj.chen@fda.hhs.gov|Division of Personalized Nutrition and Medicine, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 72079, USA. jamesj.chen@fda.hhs.gov|Division of Personalized Nutrition and Medicine, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas 72079, USA. jamesj.chen@fda.hhs.gov', 'United States|United States|United States|United States|United States', 0, 'Cluster Analysis|DNA Probes|Databases, Genetic|Equipment Failure Analysis|False Positive Reactions|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Protein Array Analysis|Quality Control|Reference Standards|Regression Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-8-412', '17961233', 'Many researchers are concerned with the comparability and reliability of microarray gene expression data. Recent completion of the MicroArray Quality Control (MAQC) project provides a unique opportunity to assess reproducibility across multiple sites and the comparability across multiple platforms. The MAQC analysis presented for the conclusion of inter- and intra-platform comparability/reproducibility of microarray gene expression measurements is inadequate. We evaluate the reproducibility/comparability of the MAQC data for 12901 common genes in four titration samples generated from five high-density one-color microarray platforms and the TaqMan technology. We discuss some of the problems with the use of correlation coefficient as metric to evaluate the inter- and intra-platform reproducibility and the percent of overlapping genes (POG) as a measure for evaluation of a gene selection procedure by MAQC.'),
(91768, 2007, 'bmc', 'Identifying dynamical modules from genetic regulatory systems: applications to the segment polarity network', 'Irons, David J|Monk, Nicholas A M', 'Department of Computer Science, University of Sheffield, UK. d.irons@sheffield.ac.uk|Department of Computer Science, University of Sheffield, UK. d.irons@sheffield.ac.uk', 'United Kingdom|United Kingdom', 16, 'Algorithms|Animals|Body Patterning|Cluster Analysis|Drosophila Proteins|Drosophila melanogaster|Feedback, Physiological|Gene Expression Regulation, Developmental|Gene Regulatory Networks|Genes, Insect|Models, Genetic|Nonlinear Dynamics|Systems Biology', 'Journal Article', '10.1186/1471-2105-8-413', '17961242', 'It is widely accepted that genetic regulatory systems are modular, in that the whole system is made up of smaller subsystems corresponding to specific biological functions. Most attempts to identify modules in genetic regulatory systems have relied on the topology of the underlying network. However, it is the temporal activity (dynamics) of genes and proteins that corresponds to biological functions, and hence it is dynamics that we focus on here for identifying subsystems.'),
(91769, 2007, 'bmc', 'InPrePPI: an integrated evaluation method based on genomic context for predicting protein-protein interactions in prokaryotic genomes', 'Sun, Jingchun|Sun, Yan|Ding, Guohui|Liu, Qi|Wang, Chuan|He, Youyu|Shi, Tieliu|Li, Yixue|Zhao, Zhongming', 'Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23298, USA. jsun@vcu.edu|Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23298, USA. jsun@vcu.edu|Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23298, USA. jsun@vcu.edu|Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23298, USA. jsun@vcu.edu|Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23298, USA. jsun@vcu.edu|Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23298, USA. jsun@vcu.edu|Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23298, USA. jsun@vcu.edu|Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23298, USA. jsun@vcu.edu|Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23298, USA. jsun@vcu.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 26, 'Base Sequence|Cluster Analysis|Data Interpretation, Statistical|Databases, Genetic|Escherichia coli Proteins|Genome, Bacterial|Genomics|Pattern Recognition, Automated|Phylogeny|Predictive Value of Tests|Protein Binding|Protein Interaction Mapping|Reference Standards|Sequence Alignment|Systems Integration|User-Computer Interface', 'Comparative Study', '10.1186/1471-2105-8-414', '17963500', 'Although many genomic features have been used in the prediction of protein-protein interactions (PPIs), frequently only one is used in a computational method. After realizing the limited power in the prediction using only one genomic feature, investigators are now moving toward integration. So far, there have been few integration studies for PPI prediction, one failed to yield appreciable improvement of prediction and the others did not conduct performance comparison. It remains unclear whether an integration of multiple genomic features can improve the PPI prediction and, if it can, how to integrate these features.'),
(91770, 2007, 'bmc', 'Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets', 'Gormley, Michael|Dampier, William|Ertel, Adam|Karacali, Bilge|Tozeren, Aydin', 'School of Biomedical Engineering, Drexel University, Philadelphia, PA, USA. mpg33@drexel.edu|School of Biomedical Engineering, Drexel University, Philadelphia, PA, USA. mpg33@drexel.edu|School of Biomedical Engineering, Drexel University, Philadelphia, PA, USA. mpg33@drexel.edu|School of Biomedical Engineering, Drexel University, Philadelphia, PA, USA. mpg33@drexel.edu|School of Biomedical Engineering, Drexel University, Philadelphia, PA, USA. mpg33@drexel.edu', 'United States|United States|United States|United States|United States', 20, 'Artificial Intelligence|Biomarkers, Tumor|DNA-Binding Proteins|Databases, Genetic|Decision Support Techniques|Diagnostic Errors|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Predictive Value of Tests|Proto-Oncogene Proteins c-bcl-6|ROC Curve|Receptors, Estrogen|Research Design', 'Journal Article', '10.1186/1471-2105-8-415', '17963508', 'Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal) samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a) all genes on the microarray platform and b) a list of known disease-related genes (a priori selection). We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91771, 2007, 'bmc', 'ProCKSI: a decision support system for Protein (structure) Comparison, Knowledge, Similarity and Information', 'Barthel, Daniel|Hirst, Jonathan D|Bxc5x82azewicz, Jacek|Burke, Edmund K|Krasnogor, Natalio', 'ASAP, School of Computer Science and IT, University of Nottingham, Nottingham, NG8 1BB, UK. daniel.barthel@nottingham.ac.uk|ASAP, School of Computer Science and IT, University of Nottingham, Nottingham, NG8 1BB, UK. daniel.barthel@nottingham.ac.uk|ASAP, School of Computer Science and IT, University of Nottingham, Nottingham, NG8 1BB, UK. daniel.barthel@nottingham.ac.uk|ASAP, School of Computer Science and IT, University of Nottingham, Nottingham, NG8 1BB, UK. daniel.barthel@nottingham.ac.uk|ASAP, School of Computer Science and IT, University of Nottingham, Nottingham, NG8 1BB, UK. daniel.barthel@nottingham.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Amino Acid Motifs|Animals|Computational Biology|Databases, Protein|Expert Systems|Humans|Models, Molecular|Pattern Recognition, Automated|Proteins|ROC Curve|Reproducibility of Results|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structural Homology, Protein|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-416', '17963510', 'We introduce the decision support system for Protein (Structure) Comparison, Knowledge, Similarity and Information (ProCKSI). ProCKSI integrates various protein similarity measures through an easy to use interface that allows the comparison of multiple proteins simultaneously. It employs the Universal Similarity Metric (USM), the Maximum Contact Map Overlap (MaxCMO) of protein structures and other external methods such as the DaliLite and the TM-align methods, the Combinatorial Extension (CE) of the optimal path, and the FAST Align and Search Tool (FAST). Additionally, ProCKSI allows the user to upload a user-defined similarity matrix supplementing the methods mentioned, and computes a similarity consensus in order to provide a rich, integrated, multicriteria view of large datasets of protein structures.'),
(91772, 2007, 'bmc', 'How accurately is ncRNA aligned within whole-genome multiple alignments?', 'Wang, Adrienne X|Ruzzo, Walter L|Tompa, Martin', 'Department of Computer Science and Engineering, University of Washington, Box 352350, Seattle, WA 98195, USA. axwang@cs.washington.edu|Department of Computer Science and Engineering, University of Washington, Box 352350, Seattle, WA 98195, USA. axwang@cs.washington.edu|Department of Computer Science and Engineering, University of Washington, Box 352350, Seattle, WA 98195, USA. axwang@cs.washington.edu', 'United States|United States|United States', 0, 'Base Sequence|Computer Simulation|Databases, Nucleic Acid|Decision Support Techniques|Evaluation Studies as Topic|Genomics|Humans|Multigene Family|Quality Control|RNA, Untranslated|Sequence Alignment|Sequence Analysis, RNA|Software Validation', 'Journal Article', '10.1186/1471-2105-8-417', '17963514', 'Multiple alignment of homologous DNA sequences is of great interest to biologists since it provides a window into evolutionary processes. At present, the accuracy of whole-genome multiple alignments, particularly in noncoding regions, has not been thoroughly evaluated.'),
(91773, 2007, 'bmc', 'HeliCis: a DNA motif discovery tool for colocalized motif pairs with periodic spacing', 'Larsson, Erik|Lindahl, Per|Mostad, Petter', 'Wallenberg Laboratory for Cardiovascular Research, Bruna Stråket 16, Sahlgrenska University Hospital, SE-413 45 Göteborg, SWEDEN. erik.larsson@wlab.gu.se|Wallenberg Laboratory for Cardiovascular Research, Bruna Stråket 16, Sahlgrenska University Hospital, SE-413 45 Göteborg, SWEDEN. erik.larsson@wlab.gu.se|Wallenberg Laboratory for Cardiovascular Research, Bruna Stråket 16, Sahlgrenska University Hospital, SE-413 45 Göteborg, SWEDEN. erik.larsson@wlab.gu.se', '-|-|-', 9, 'Algorithms|Amino Acid Motifs|Animals|Base Sequence|Binding Sites|Computer Simulation|DNA|Databases, Genetic|Models, Genetic|Models, Structural|Pattern Recognition, Automated|Regulatory Elements, Transcriptional|Regulatory Sequences, Nucleic Acid|Sensitivity and Specificity|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-8-418', '17963524', 'Correct temporal and spatial gene expression during metazoan development relies on combinatorial interactions between different transcription factors. As a consequence, cis-regulatory elements often colocalize in clusters termed cis-regulatory modules. These may have requirements on organizational features such as spacing, order and helical phasing (periodic spacing) between binding sites. Due to the turning of the DNA helix, a small modification of the distance between a pair of sites may sometimes drastically disrupt function, while insertion of a full helical turn of DNA (10-11 bp) between cis elements may cause functionality to be restored. Recently, de novo motif discovery methods which incorporate organizational properties such as colocalization and order preferences have been developed, but there are no tools which incorporate periodic spacing into the model.'),
(91774, 2007, 'bmc', 'A dynamic programming approach for the alignment of signal peaks in multiple gas chromatography-mass spectrometry experiments', 'Robinson, Mark D|De Souza, David P|Keen, Woon Wai|Saunders, Eleanor C|McConville, Malcolm J|Speed, Terence P|Likixc4x87, Vladimir A', 'The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC 3050, Australia. mrobinson@wehi.edu.au|The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC 3050, Australia. mrobinson@wehi.edu.au|The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC 3050, Australia. mrobinson@wehi.edu.au|The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC 3050, Australia. mrobinson@wehi.edu.au|The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC 3050, Australia. mrobinson@wehi.edu.au|The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC 3050, Australia. mrobinson@wehi.edu.au|The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC 3050, Australia. mrobinson@wehi.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Algorithms|Artificial Intelligence|Gas Chromatography-Mass Spectrometry|Gene Expression Profiling|Pattern Recognition, Automated|Peptide Mapping', 'Journal Article', '10.1186/1471-2105-8-419', '17963529', 'Gas chromatography-mass spectrometry (GC-MS) is a robust platform for the profiling of certain classes of small molecules in biological samples. When multiple samples are profiled, including replicates of the same sample and/or different sample states, one needs to account for retention time drifts between experiments. This can be achieved either by the alignment of chromatographic profiles prior to peak detection, or by matching signal peaks after they have been extracted from chromatogram data matrices. Automated retention time correction is particularly important in non-targeted profiling studies.'),
(91775, 2007, 'bmc', 'Unite and conquer: enhanced prediction of protein subcellular localization by integrating multiple specialized tools', 'Shen, Yao Qing|Burger, Gertraud', 'Robert Cedergren Center for Bioinformatics and Genomics, Biochemistry Department, Université de Montréal, 2900 Edouard-Montpetit, Montreal, QC, H3T 1J4, Canada. yaoqing.shen@umontreal.ca|Robert Cedergren Center for Bioinformatics and Genomics, Biochemistry Department, Université de Montréal, 2900 Edouard-Montpetit, Montreal, QC, H3T 1J4, Canada. yaoqing.shen@umontreal.ca', 'Canada|Canada', 0, 'Algorithms|Amino Acid Motifs|Arabidopsis Proteins|Computational Biology|Databases, Protein|False Positive Reactions|Internet|Mitochondria|Peptides|Phylogeny|Protein Structure, Tertiary|Protein Transport|Proteins|Reproducibility of Results|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-8-420', '17967180', 'Knowing the subcellular location of proteins provides clues to their function as well as the interconnectivity of biological processes. Dozens of tools are available for predicting protein location in the eukaryotic cell. Each tool performs well on certain data sets, but their predictions often disagree for a given protein. Since the individual tools each have particular strengths, we set out to integrate them in a way that optimally exploits their potential. The method we present here is applicable to various subcellular locations, but tailored for predicting whether or not a protein is localized in mitochondria. Knowledge of the mitochondrial proteome is relevant to understanding the role of this organelle in global cellular processes.'),
(91776, 2007, 'bmc', 'A procedure for the estimation over time of metabolic fluxes in scenarios where measurements are uncertain and/or insufficient', 'Llaneras, Francisco|Picó, Jesús', 'Dept. of Systems Engineering and Control, Technical University of Valencia, Camino de Vera s/n, 46022 Valencia, Spain. frallaes@doctor.upv.es|Dept. of Systems Engineering and Control, Technical University of Valencia, Camino de Vera s/n, 46022 Valencia, Spain. frallaes@doctor.upv.es', 'Spain|Spain', 37, 'Algorithms|Animals|CHO Cells|Computer Simulation|Cricetinae|Cricetulus|Data Interpretation, Statistical|Models, Biological|Models, Statistical|Proteome|Signal Transduction', 'Journal Article', '10.1186/1471-2105-8-421', '17971203', 'An indirect approach is usually used to estimate the metabolic fluxes of an organism: couple the available measurements with known biological constraints (e.g. stoichiometry). Typically this estimation is done under a static point of view. Therefore, the fluxes so obtained are only valid while the environmental conditions and the cell state remain stable. However, estimating the evolution over time of the metabolic fluxes is valuable to investigate the dynamic behaviour of an organism and also to monitor industrial processes. Although Metabolic Flux Analysis can be successively applied with this aim, this approach has two drawbacks: i) sometimes it cannot be used because there is a lack of measurable fluxes, and ii) the uncertainty of experimental measurements cannot be considered. The Flux Balance Analysis could be used instead, but the assumption of optimal behaviour of the organism brings other difficulties.'),
(91777, 2007, 'bmc', 'SIRAC: Supervised Identification of Regions of Aberration in aCGH datasets', 'Lai, Carmen|Horlings, Hugo M|van de Vijver, Marc J|van Beers, Eric H|Nederlof, Petra M|Wessels, Lodewyk F A|Reinders, Marcel J T', 'Bioinformatics group, Delft University, Delft, The Netherlands. c.lai@tudelft.nl|Bioinformatics group, Delft University, Delft, The Netherlands. c.lai@tudelft.nl|Bioinformatics group, Delft University, Delft, The Netherlands. c.lai@tudelft.nl|Bioinformatics group, Delft University, Delft, The Netherlands. c.lai@tudelft.nl|Bioinformatics group, Delft University, Delft, The Netherlands. c.lai@tudelft.nl|Bioinformatics group, Delft University, Delft, The Netherlands. c.lai@tudelft.nl|Bioinformatics group, Delft University, Delft, The Netherlands. c.lai@tudelft.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Artificial Intelligence|Breast Neoplasms|Chromosome Mapping|DNA Mutational Analysis|Databases, Genetic|Humans|In Situ Hybridization|Neoplasm Proteins|Pattern Recognition, Automated|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-8-422', '17971227', 'Array comparative genome hybridization (aCGH) provides information about genomic aberrations. Alterations in the DNA copy number may cause the cell to malfunction, leading to cancer. Therefore, the identification of DNA amplifications or deletions across tumors may reveal key genes involved in cancer and improve our understanding of the underlying biological processes associated with the disease.'),
(91778, 2007, 'bmc', 'PubMed related articles: a probabilistic topic-based model for content similarity', 'Lin, Jimmy|Wilbur, W John', 'College of Information Studies, University of Maryland, College Park, Maryland, USA. jimmylin@umd.edu|College of Information Studies, University of Maryland, College Park, Maryland, USA. jimmylin@umd.edu', 'United States|United States', 124, 'Algorithms|Artificial Intelligence|Bibliometrics|Data Interpretation, Statistical|Models, Statistical|Natural Language Processing|Periodicals as Topic|PubMed|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-8-423', '17971238', 'We present a probabilistic topic-based model for content similarity called pmra that underlies the related article search feature in PubMed. Whether or not a document is about a particular topic is computed from term frequencies, modeled as Poisson distributions. Unlike previous probabilistic retrieval models, we do not attempt to estimate relevance-but rather our focus is relatedness, the probability that a user would want to examine a particular document given known interest in another. We also describe a novel technique for estimating parameters that does not require human relevance judgments, instead, the process is based on the existence of MeSH in MEDLINE.'),
(91779, 2007, 'bmc', 'Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction', 'Larsen, Mette V|Lundegaard, Claus|Lamberth, Kasper|Buus, Soren|Lund, Ole|Nielsen, Morten', 'Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. metteb@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. metteb@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. metteb@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. metteb@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. metteb@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. metteb@cbs.dtu.dk', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 280, 'Algorithms|Binding Sites|Epitope Mapping|Epitopes, T-Lymphocyte|Protein Binding|Sequence Analysis, Protein|T-Lymphocytes, Cytotoxic', 'Comparative Study', '10.1186/1471-2105-8-424', '17973982', 'Reliable predictions of Cytotoxic T lymphocyte (CTL) epitopes are essential for rational vaccine design. Most importantly, they can minimize the experimental effort needed to identify epitopes. NetCTL is a web-based tool designed for predicting human CTL epitopes in any given protein. It does so by integrating predictions of proteasomal cleavage, TAP transport efficiency, and MHC class I affinity. At least four other methods have been developed recently that likewise attempt to predict CTL epitopes: EpiJen, MAPPP, MHC-pathway, and WAPP. In order to compare the performance of prediction methods, objective benchmarks and standardized performance measures are needed. Here, we develop such large-scale benchmark and corresponding performance measures and report the performance of an updated version 1.2 of NetCTL in comparison with the four other methods.'),
(91780, 2007, 'bmc', 'SABERTOOTH: protein structural alignment based on a vectorial structure representation', 'Teichert, Florian|Bastolla, Ugo|Porto, Markus', 'Institut für Festkörperphysik, Technische Universität Darmstadt, Hochschulstr, 6-8, 64289 Darmstadt, Germany. floteich@fkp.tu-darmstadt.de|Institut für Festkörperphysik, Technische Universität Darmstadt, Hochschulstr, 6-8, 64289 Darmstadt, Germany. floteich@fkp.tu-darmstadt.de|Institut für Festkörperphysik, Technische Universität Darmstadt, Hochschulstr, 6-8, 64289 Darmstadt, Germany. floteich@fkp.tu-darmstadt.de', 'Germany|Germany|Germany', 0, 'Amino Acid Sequence|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structural Homology, Protein', 'Comparative Study', '10.1186/1471-2105-8-425', '17974011', 'The task of computing highly accurate structural alignments of proteins in very short computation time is still challenging. This is partly due to the complexity of protein structures. Therefore, instead of manipulating coordinates directly, matrices of inter-atomic distances, sets of vectors between protein backbone atoms, and other reduced representations are used. These decrease the effort of comparing large sets of coordinates, but protein structural alignment still remains computationally expensive.'),
(91781, 2007, 'bmc', 'DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis', 'Sherman, Brad T|Huang, Da Wei|Tan, Qina|Guo, Yongjian|Bour, Stephan|Liu, David|Stephens, Robert|Baseler, Michael W|Lane, H Clifford|Lempicki, Richard A', 'Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, MD 21702, USA. bsherman@mail.nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, MD 21702, USA. bsherman@mail.nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, MD 21702, USA. bsherman@mail.nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, MD 21702, USA. bsherman@mail.nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, MD 21702, USA. bsherman@mail.nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, MD 21702, USA. bsherman@mail.nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, MD 21702, USA. bsherman@mail.nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, MD 21702, USA. bsherman@mail.nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, MD 21702, USA. bsherman@mail.nih.gov|Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, MD 21702, USA. bsherman@mail.nih.gov', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 338, 'Algorithms|Animals|Computational Biology|Database Management Systems|Databases, Genetic|Databases, Protein|Genomics|Humans|Information Storage and Retrieval|Information Systems|Internet|Knowledge Bases|Models, Genetic|Multigene Family|Oligonucleotide Array Sequence Analysis|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-426', '17980028', 'Due to the complex and distributed nature of biological research, our current biological knowledge is spread over many redundant annotation databases maintained by many independent groups. Analysts usually need to visit many of these bioinformatics databases in order to integrate comprehensive annotation information for their genes, which becomes one of the bottlenecks, particularly for the analytic task associated with a large gene list. Thus, a highly centralized and ready-to-use gene-annotation knowledgebase is in demand for high throughput gene functional analysis.'),
(91782, 2007, 'bmc', 'Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes', 'Chou, Jeff W|Zhou, Tong|Kaufmann, William K|Paules, Richard S|Bushel, Pierre R', 'Microarray Group, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA. chou@niehs.nih.gov|Microarray Group, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA. chou@niehs.nih.gov|Microarray Group, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA. chou@niehs.nih.gov|Microarray Group, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA. chou@niehs.nih.gov|Microarray Group, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA. chou@niehs.nih.gov', 'United States|United States|United States|United States|United States', 39, 'Algorithms|Artificial Intelligence|Biological Assay|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Proteome|Signal Transduction', 'Journal Article', '10.1186/1471-2105-8-427', '17980031', 'A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions.'),
(91783, 2007, 'bmc', 'Cubic exact solutions for the estimation of pairwise haplotype frequencies: implications for linkage disequilibrium analyses and a web tool CubeX', 'Gaunt, Tom R|Rodríguez, Santiago|Day, Ian Nm', 'Bristol Genetic Epidemology Laboratories (BGEL) and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), Department of Social Medicine, University of Bristol, Canynge Hall, Whiteladies Road, Bristol, BS8 2PR, UK. tom.gaunt@bristol.ac.uk|Bristol Genetic Epidemology Laboratories (BGEL) and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), Department of Social Medicine, University of Bristol, Canynge Hall, Whiteladies Road, Bristol, BS8 2PR, UK. tom.gaunt@bristol.ac.uk|Bristol Genetic Epidemology Laboratories (BGEL) and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), Department of Social Medicine, University of Bristol, Canynge Hall, Whiteladies Road, Bristol, BS8 2PR, UK. tom.gaunt@bristol.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 201, 'Algorithms|Alleles|Animals|Computational Biology|Gene Frequency|Genetic Linkage|Genetic Predisposition to Disease|Genetics, Population|Haplotypes|Humans|Internet|Linkage Disequilibrium|Models, Genetic|Models, Statistical|Models, Theoretical|Software', 'Journal Article', '10.1186/1471-2105-8-428', '17980034', 'The frequency of a haplotype comprising one allele at each of two loci can be expressed as a cubic equation (the Hill equation), the solution of which gives that frequency. Most haplotype and linkage disequilibrium analysis programs use iteration-based algorithms which substitute an estimate of haplotype frequency into the equation, producing a new estimate which is repeatedly fed back into the equation until the values converge to a maximum likelihood estimate (expectation-maximisation).'),
(91784, 2007, 'bmc', 'CoryneRegNet 40 - A reference database for corynebacterial gene regulatory networks', 'Baumbach, Jan', 'Computational Methods for Emerging Technologies, Bielefeld University, Bielefeld, Germany. Jan.Baumbach@CeBiTec.Uni-Bielefeld.DE', 'Germany', 55, 'Algorithms|Bacterial Proteins|Corynebacterium glutamicum|Database Management Systems|Databases, Protein|Gene Expression Regulation, Bacterial|Information Storage and Retrieval|Reference Values|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-429', '17986320', 'Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression) and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum.'),
(91785, 2007, 'bmc', 'Analysis of feedback loops and robustness in network evolution based on Boolean models', 'Kwon, Yung-Keun|Cho, Kwang-Hyun', 'Department of Bio and Brain Engineering and KI for the BioCentury, Korea Advanced Institute of Science and Technology, 335 Gwahangno, Yuseong-gu, Daejeon, 305-701, Republic of Korea. kwon@soar.snu.ac.kr|Department of Bio and Brain Engineering and KI for the BioCentury, Korea Advanced Institute of Science and Technology, 335 Gwahangno, Yuseong-gu, Daejeon, 305-701, Republic of Korea. kwon@soar.snu.ac.kr', '-|-', 44, 'Animals|Cell Physiological Phenomena|Evolution, Molecular|Feedback, Physiological|Gene Expression Regulation|Humans|Logistic Models|Metabolic Networks and Pathways|Models, Biological|Neural Networks (Computer)|Nonlinear Dynamics|Protein Interaction Mapping|Selection, Genetic|Signal Transduction|Stochastic Processes|Systems Theory', 'Comparative Study', '10.1186/1471-2105-8-430', '17988389', 'Many biological networks such as protein-protein interaction networks, signaling networks, and metabolic networks have topological characteristics of a scale-free degree distribution. Preferential attachment has been considered as the most plausible evolutionary growth model to explain this topological property. Although various studies have been undertaken to investigate the structural characteristics of a network obtained using this growth model, its dynamical characteristics have received relatively less attention.'),
(91786, 2007, 'bmc', 'Comparative evaluation of gene-set analysis methods', 'Liu, Qi|Dinu, Irina|Adewale, Adeniyi J|Potter, John D|Yasui, Yutaka', 'School of Public Health, University of Alberta, Edmonton, Alberta, T6G2G3, Canada. qliu@phs.med.ualberta.ca|School of Public Health, University of Alberta, Edmonton, Alberta, T6G2G3, Canada. qliu@phs.med.ualberta.ca|School of Public Health, University of Alberta, Edmonton, Alberta, T6G2G3, Canada. qliu@phs.med.ualberta.ca|School of Public Health, University of Alberta, Edmonton, Alberta, T6G2G3, Canada. qliu@phs.med.ualberta.ca|School of Public Health, University of Alberta, Edmonton, Alberta, T6G2G3, Canada. qliu@phs.med.ualberta.ca', 'Canada|Canada|Canada|Canada|Canada', 77, 'Analysis of Variance|Cell Line, Tumor|Cluster Analysis|Computer Simulation|Data Interpretation, Statistical|Female|Gene Expression|Gene Expression Profiling|Genes, p53|Humans|Leukemia, Myeloid, Acute|Lymphoma|Male|Oligonucleotide Array Sequence Analysis|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Predictive Value of Tests|Reference Standards|Sample Size|Statistical Distributions', 'Comparative Study', '10.1186/1471-2105-8-431', '17988400', 'Multiple data-analytic methods have been proposed for evaluating gene-expression levels in specific biological pathways, assessing differential expression associated with a binary phenotype. Following Goeman and Bühlmanns recent review, we compared statistical performance of three methods, namely Global Test, ANCOVA Global Test, and SAM-GS, that test self-contained null hypotheses Via. subject sampling. The three methods were compared based on a simulation experiment and analyses of three real-world microarray datasets.'),
(91787, 2007, 'bmc', 'Identifications of conserved 7-mers in 3-UTRs and microRNAs in Drosophila', 'Gu, Jin|Fu, Hu|Zhang, Xuegong|Li, Yanda', 'Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University, Beijing 100084, China. wellgoo@gmail.com|Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University, Beijing 100084, China. wellgoo@gmail.com|Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University, Beijing 100084, China. wellgoo@gmail.com|Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University, Beijing 100084, China. wellgoo@gmail.com', 'China|China|China|China', 13, '3 Untranslated Regions|Animals|Artificial Intelligence|Base Pairing|Base Sequence|Computational Biology|Conserved Sequence|Databases, Genetic|Drosophila melanogaster|Evolution, Molecular|Gene Expression Regulation|Genes, Insect|Genome, Insect|MicroRNAs|Multigene Family|Phylogeny|Sequence Analysis, RNA|Species Specificity', 'Journal Article', '10.1186/1471-2105-8-432', '17996040', 'MicroRNAs (miRNAs) are a class of endogenous regulatory small RNAs which play an important role in posttranscriptional regulations by targeting mRNAs for cleavage or translational repression. The base-pairing between the 5-end of miRNA and the target mRNA 3-UTRs is essential for the miRNA:mRNA recognition. Recent studies show that many seed matches in 3-UTRs, which are fully complementary to miRNA 5-ends, are highly conserved. Based on these features, a two-stage strategy can be implemented to achieve the de novo identification of miRNAs by requiring the complete base-pairing between the 5-end of miRNA candidates and the potential seed matches in 3-UTRs.'),
(91788, 2007, 'bmc', 'Incremental and unifying modelling formalism for biological interaction networks', 'Yartseva, Anastasia|Klaudel, Hanna|Devillers, Raymond|Képès, François', 'IBISC - Université dEvry Val dEssonne, Tour Evry 2, 523 place des Terrasses de lAgora, F-91000 Evry, France. iartseva@gmail.com|IBISC - Université dEvry Val dEssonne, Tour Evry 2, 523 place des Terrasses de lAgora, F-91000 Evry, France. iartseva@gmail.com|IBISC - Université dEvry Val dEssonne, Tour Evry 2, 523 place des Terrasses de lAgora, F-91000 Evry, France. iartseva@gmail.com|IBISC - Université dEvry Val dEssonne, Tour Evry 2, 523 place des Terrasses de lAgora, F-91000 Evry, France. iartseva@gmail.com', 'France|France|France|France', 3, 'Algorithms|Animals|Bacteriophage lambda|Cell Physiological Phenomena|Computer Simulation|Feedback, Physiological|Gene Expression Regulation|Genes, Switch|Humans|Models, Biological|Nonlinear Dynamics|Protein Interaction Mapping|Sensitivity and Specificity|Signal Transduction|Stochastic Processes|Systems Biology|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-433', '17996051', 'An appropriate choice of the modeling formalism from the broad range of existing ones may be crucial for efficiently describing and analyzing biological systems.'),
(91789, 2007, 'bmc', 'A Hidden Markov Model to estimate population mixture and allelic copy-numbers in cancers using Affymetrix SNP arrays', 'Lamy, Philippe|Andersen, Claus L|Dyrskjot, Lars|Torring, Niels|Wiuf, Carsten', 'Bioinformatics Research Center, University of Aarhus, Hoegh-Guldbergsgade 10, Bldg 1090, 8000 Aarhus C, Denmark. plamy@birc.au.dk|Bioinformatics Research Center, University of Aarhus, Hoegh-Guldbergsgade 10, Bldg 1090, 8000 Aarhus C, Denmark. plamy@birc.au.dk|Bioinformatics Research Center, University of Aarhus, Hoegh-Guldbergsgade 10, Bldg 1090, 8000 Aarhus C, Denmark. plamy@birc.au.dk|Bioinformatics Research Center, University of Aarhus, Hoegh-Guldbergsgade 10, Bldg 1090, 8000 Aarhus C, Denmark. plamy@birc.au.dk|Bioinformatics Research Center, University of Aarhus, Hoegh-Guldbergsgade 10, Bldg 1090, 8000 Aarhus C, Denmark. plamy@birc.au.dk', 'Denmark|Denmark|Denmark|Denmark|Denmark', 23, 'Algorithms|Alleles|DNA Mutational Analysis|DNA, Neoplasm|Gene Dosage|Genome, Human|Genotype|Humans|Male|Markov Chains|Models, Statistical|Neoplasms|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-8-434', '17996079', 'Affymetrix SNP arrays can interrogate thousands of SNPs at the same time. This allows us to look at the genomic content of cancer cells and to investigate the underlying events leading to cancer. Genomic copy-numbers are today routinely derived from SNP array data, but the proposed algorithms for this task most often disregard the genotype information available from germline cells in paired germline-tumour samples. Including this information may deepen our understanding of the true biological situation e.g. by enabling analysis of allele specific copy-numbers. Here we rely on matched germline-tumour samples and have developed a Hidden Markov Model (HMM) to estimate allelic copy-number changes in tumour cells. Further with this approach we are able to estimate the proportion of normal cells in the tumour (mixture proportion).'),
(91790, 2007, 'bmc', 'An open source infrastructure for managing knowledge and finding potential collaborators in a domain-specific subset of PubMed, with an example from human genome epidemiology', 'Yu, Wei|Yesupriya, Ajay|Wulf, Anja|Qu, Junfeng|Khoury, Muin J|Gwinn, Marta', 'National Office of Public Health Genomics, Coordinating Center for Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA. WYu@cdc.gov|National Office of Public Health Genomics, Coordinating Center for Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA. WYu@cdc.gov|National Office of Public Health Genomics, Coordinating Center for Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA. WYu@cdc.gov|National Office of Public Health Genomics, Coordinating Center for Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA. WYu@cdc.gov|National Office of Public Health Genomics, Coordinating Center for Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA. WYu@cdc.gov|National Office of Public Health Genomics, Coordinating Center for Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA. WYu@cdc.gov', 'United States|United States|United States|United States|United States|United States', 12, 'Algorithms|Artificial Intelligence|Chromosome Mapping|Cooperative Behavior|Database Management Systems|Genetic Predisposition to Disease|Health Knowledge, Attitudes, Practice|Humans|Information Dissemination|Information Storage and Retrieval|Internet|Natural Language Processing|PubMed|Software', 'Journal Article', '10.1186/1471-2105-8-436', '17996092', 'Identifying relevant research in an ever-growing body of published literature is becoming increasingly difficult. Establishing domain-specific knowledge bases may be a more effective and efficient way to manage and query information within specific biomedical fields. Adopting controlled vocabulary is a critical step toward data integration and interoperability in any information system. We present an open source infrastructure that provides a powerful capacity for managing and mining data within a domain-specific knowledge base. As a practical application of our infrastructure, we presented two applications - Literature Finder and Investigator Browser - as well as a tool set for automating the data curating process for the human genome published literature database. The design of this infrastructure makes the system potentially extensible to other data sources.'),
(91791, 2007, 'bmc', 'Identification of tissue-specific cis-regulatory modules based on interactions between transcription factors', 'Yu, Xueping|Lin, Jimmy|Zack, Donald J|Qian, Jiang', 'Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. xyu15@jhmi.edu|Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. xyu15@jhmi.edu|Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. xyu15@jhmi.edu|Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. xyu15@jhmi.edu', 'United States|United States|United States|United States', 20, 'Algorithms|Animals|Base Sequence|Binding Sites|Humans|Molecular Sequence Data|Organ Specificity|Protein Binding|Regulatory Elements, Transcriptional|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-437', '17996093', 'Evolutionary conservation has been used successfully to help identify cis-acting DNA regions that are important in regulating tissue-specific gene expression. Motivated by increasing evidence that some DNA regulatory regions are not evolutionary conserved, we have developed an approach for cis-regulatory region identification that does not rely upon evolutionary sequence conservation.'),
(91792, 2007, 'bmc', 'Glycosylation site prediction using ensembles of Support Vector Machine classifiers', 'Caragea, Cornelia|Sinapov, Jivko|Silvescu, Adrian|Dobbs, Drena|Honavar, Vasant', 'Artificial Intelligence Research Laboratory, Computer Science Department, Iowa State University, USA. cornelia@cs.iastate.edu|Artificial Intelligence Research Laboratory, Computer Science Department, Iowa State University, USA. cornelia@cs.iastate.edu|Artificial Intelligence Research Laboratory, Computer Science Department, Iowa State University, USA. cornelia@cs.iastate.edu|Artificial Intelligence Research Laboratory, Computer Science Department, Iowa State University, USA. cornelia@cs.iastate.edu|Artificial Intelligence Research Laboratory, Computer Science Department, Iowa State University, USA. cornelia@cs.iastate.edu', 'United States|United States|United States|United States|United States', 125, 'Amino Acid Motifs|Amino Acid Sequence|Animals|Artificial Intelligence|Cluster Analysis|Computational Biology|Databases, Protein|Discriminant Analysis|Glycosylation|Humans|Internet|Pattern Recognition, Automated|Proteins|ROC Curve|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1186/1471-2105-8-438', '17996106', 'Glycosylation is one of the most complex post-translational modifications (PTMs) of proteins in eukaryotic cells. Glycosylation plays an important role in biological processes ranging from protein folding and subcellular localization, to ligand recognition and cell-cell interactions. Experimental identification of glycosylation sites is expensive and laborious. Hence, there is significant interest in the development of computational methods for reliable prediction of glycosylation sites from amino acid sequences.'),
(91793, 2007, 'bmc', 'BGX: a Bioconductor package for the Bayesian integrated analysis of Affymetrix GeneChips', 'Turro, Ernest|Bochkina, Natalia|Hein, Anne-Mette K|Richardson, Sylvia', 'Centre for Biostatistics, Imperial College London, UK. ernest.turro@ic.ac.uk|Centre for Biostatistics, Imperial College London, UK. ernest.turro@ic.ac.uk|Centre for Biostatistics, Imperial College London, UK. ernest.turro@ic.ac.uk|Centre for Biostatistics, Imperial College London, UK. ernest.turro@ic.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 18, 'Algorithms|Bayes Theorem|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Programming Languages|Sequence Analysis, DNA|Software|Systems Integration', 'Journal Article', '10.1186/1471-2105-8-439', '17997843', 'Affymetrix 3 GeneChip microarrays are widely used to profile the expression of thousands of genes simultaneously. They differ from many other microarray types in that GeneChips are hybridised using a single labelled extract and because they contain multiple match and mismatch sequences for each transcript. Most algorithms extract the signal from GeneChip experiments in a sequence of separate steps, including background correction and normalisation, which inhibits the simultaneous use of all available information. They principally provide a point estimate of gene expression and, in contrast to BGX, do not fully integrate the uncertainty arising from potentially heterogeneous responses of the probes.'),
(91794, 2007, 'bmc', 'Improving model construction of profile HMMs for remote homology detection through structural alignment', 'Bernardes, Juliana S|Dávila, Alberto M R|Costa, Vítor S|Zaverucha, Gerson', 'COPPE, Programa de Engenharia de Sistemas e Computação, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil. julibinho@gmail.com|COPPE, Programa de Engenharia de Sistemas e Computação, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil. julibinho@gmail.com|COPPE, Programa de Engenharia de Sistemas e Computação, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil. julibinho@gmail.com|COPPE, Programa de Engenharia de Sistemas e Computação, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil. julibinho@gmail.com', 'Brazil|Brazil|Brazil|Brazil', 16, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Data Interpretation, Statistical|Markov Chains|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1186/1471-2105-8-435', '17999748', 'Remote homology detection is a challenging problem in Bioinformatics. Arguably, profile Hidden Markov Models (pHMMs) are one of the most successful approaches in addressing this important problem. pHMM packages present a relatively small computational cost, and perform particularly well at recognizing remote homologies. This raises the question of whether structural alignments could impact the performance of pHMMs trained from proteins in the Twilight Zone, as structural alignments are often more accurate than sequence alignments at identifying motifs and functional residues. Next, we assess the impact of using structural alignments in pHMM performance.'),
(91795, 2007, 'bmc', 'A general and efficient method for estimating continuous IBD functions for use in genome scans for QTL', 'Besnier, Francois|Carlborg, Orjan', 'Linnaeus Centre for Bioinformatics, Uppsala University, SE-75124 Uppsala, Sweden. francois.besnier@lcb.uu.se|Linnaeus Centre for Bioinformatics, Uppsala University, SE-75124 Uppsala, Sweden. francois.besnier@lcb.uu.se', 'Sweden|Sweden', 5, 'Algorithms|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Genetic Variation|Molecular Sequence Data|Quantitative Trait Loci|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-8-440', '17999749', 'Identity by descent (IBD) matrix estimation is a central component in mapping of Quantitative Trait Loci (QTL) using variance component models. A large number of algorithms have been developed for estimation of IBD between individuals in populations at discrete locations in the genome for use in genome scans to detect QTL affecting various traits of interest in experimental animal, human and agricultural pedigrees. Here, we propose a new approach to estimate IBD as continuous functions rather than as discrete values.'),
(91796, 2007, 'bmc', 'A manually curated database of tetrapod mitochondrially encoded tRNA sequences and secondary structures', 'Popadin, Konstantin Yu|Mamirova, Leila A|Kondrashov, Fyodor A', 'Institute for Information Transmission Problems RAS, Bolshoi Karetny pereulok 19, Moscow. konstantinpopadin@gmail.com|Institute for Information Transmission Problems RAS, Bolshoi Karetny pereulok 19, Moscow. konstantinpopadin@gmail.com|Institute for Information Transmission Problems RAS, Bolshoi Karetny pereulok 19, Moscow. konstantinpopadin@gmail.com', '-|-|-', 4, 'Amphibians|Animals|Base Sequence|Databases, Nucleic Acid|Dinosaurs|Genome, Mitochondrial|Humans|Mammals|Nucleic Acid Conformation|RNA, Transfer|Sequence Alignment|Terminology as Topic', 'Journal Article', '10.1186/1471-2105-8-441', '17999775', 'Mitochondrial tRNAs have been the subject of study for structural biologists interested in their secondary structure characteristics, evolutionary biologists have researched patterns of compensatory and structural evolution and medical studies have been directed towards understanding the basis of human disease. However, an up to date, manually curated database of mitochondrially encoded tRNAs from higher animals is currently not available.'),
(91797, 2007, 'bmc', 'A general strategy to determine the congruence between a hierarchical and a non-hierarchical classification', 'Marco, Antonio|Marín, Ignacio', 'Departamento de Genética, Universidad de Valencia, Burjassot, Spain. marcasan@uv.es|Departamento de Genética, Universidad de Valencia, Burjassot, Spain. marcasan@uv.es', 'Spain|Spain', 0, 'Artificial Intelligence|Classification|Cluster Analysis|Databases, Protein|Decision Trees|Mitochondrial Proteins|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Protein Interaction Mapping|Reproducibility of Results|Saccharomyces cerevisiae Proteins|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-442', '18005402', 'Classification procedures are widely used in phylogenetic inference, the analysis of expression profiles, the study of biological networks, etc. Many algorithms have been proposed to establish the similarity between two different classifications of the same elements. However, methods to determine significant coincidences between hierarchical and non-hierarchical partitions are still poorly developed, in spite of the fact that the search for such coincidences is implicit in many analyses of massive data.'),
(91798, 2007, 'bmc', 'Insertions and the emergence of novel protein structure: a structure-based phylogenetic study of insertions', 'Jiang, Haiyan|Blouin, Christian', 'Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, B3H 1W5, Canada. haiyan.jiang@dal.ca|Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, B3H 1W5, Canada. haiyan.jiang@dal.ca', 'Canada|Canada', 37, 'Amino Acid Sequence|Computer Simulation|DNA Transposable Elements|Evolution, Molecular|Models, Chemical|Models, Genetic|Models, Molecular|Molecular Sequence Data|Phylogeny|Protein Conformation|Proteins|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-8-444', '18005425', 'In protein evolution, the mechanism of the emergence of novel protein domain is still an open question. The incremental growth of protein variable regions, which was produced by stochastic insertions, has the potential to generate large and complex sub-structures. In this study, a deterministic methodology is proposed to reconstruct phylogenies from protein structures, and to infer insertion events in protein evolution. The analysis was performed on a broad range of SCOP domain families.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91799, 2007, 'bmc', 'Predicting combinatorial binding of transcription factors to regulatory elements in the human genome by association rule mining', 'Morgan, Xochitl C|Ni, Shulin|Miranker, Daniel P|Iyer, Vishwanath R', 'Institute for Cellular and Molecular Biology and Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas 78712-0159, USA. morganx@mail.utexas.edu|Institute for Cellular and Molecular Biology and Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas 78712-0159, USA. morganx@mail.utexas.edu|Institute for Cellular and Molecular Biology and Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas 78712-0159, USA. morganx@mail.utexas.edu|Institute for Cellular and Molecular Biology and Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas 78712-0159, USA. morganx@mail.utexas.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Binding Sites|Databases, Factual|Electronic Data Processing|Forecasting|Gene Expression Profiling|Genome, Human|Humans|Microarray Analysis|Models, Biological|Protein Binding|Regulatory Elements, Transcriptional|Transcription Factors', 'Evaluation Studies', '10.1186/1471-2105-8-445', '18005433', 'Cis-acting transcriptional regulatory elements in mammalian genomes typically contain specific combinations of binding sites for various transcription factors. Although some cis-regulatory elements have been well studied, the combinations of transcription factors that regulate normal expression levels for the vast majority of the 20,000 genes in the human genome are unknown. We hypothesized that it should be possible to discover transcription factor combinations that regulate gene expression in concert by identifying over-represented combinations of sequence motifs that occur together in the genome. In order to detect combinations of transcription factor binding motifs, we developed a data mining approach based on the use of association rules, which are typically used in market basket analysis. We scored each segment of the genome for the presence or absence of each of 83 transcription factor binding motifs, then used association rule mining algorithms to mine this dataset, thus identifying frequently occurring pairs of distinct motifs within a segment.'),
(91800, 2007, 'bmc', 'Novel definition files for human GeneChips based on GeneAnnot', 'Ferrari, Francesco|Bortoluzzi, Stefania|Coppe, Alessandro|Sirota, Alexandra|Safran, Marilyn|Shmoish, Michael|Ferrari, Sergio|Lancet, Doron|Danieli, Gian Antonio|Bicciato, Silvio', 'Department of Biomedical Sciences, University of Modena and Reggio Emilia, via G. Campi 287, 41100, Modena, Italy. ferrari.francesco@unimore.it|Department of Biomedical Sciences, University of Modena and Reggio Emilia, via G. Campi 287, 41100, Modena, Italy. ferrari.francesco@unimore.it|Department of Biomedical Sciences, University of Modena and Reggio Emilia, via G. Campi 287, 41100, Modena, Italy. ferrari.francesco@unimore.it|Department of Biomedical Sciences, University of Modena and Reggio Emilia, via G. Campi 287, 41100, Modena, Italy. ferrari.francesco@unimore.it|Department of Biomedical Sciences, University of Modena and Reggio Emilia, via G. Campi 287, 41100, Modena, Italy. ferrari.francesco@unimore.it|Department of Biomedical Sciences, University of Modena and Reggio Emilia, via G. Campi 287, 41100, Modena, Italy. ferrari.francesco@unimore.it|Department of Biomedical Sciences, University of Modena and Reggio Emilia, via G. Campi 287, 41100, Modena, Italy. ferrari.francesco@unimore.it|Department of Biomedical Sciences, University of Modena and Reggio Emilia, via G. Campi 287, 41100, Modena, Italy. ferrari.francesco@unimore.it|Department of Biomedical Sciences, University of Modena and Reggio Emilia, via G. Campi 287, 41100, Modena, Italy. ferrari.francesco@unimore.it|Department of Biomedical Sciences, University of Modena and Reggio Emilia, via G. Campi 287, 41100, Modena, Italy. ferrari.francesco@unimore.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 87, 'Algorithms|Base Sequence|Chromosome Mapping|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Humans|Information Storage and Retrieval|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-446', '18005434', 'Improvements in genome sequence annotation revealed discrepancies in the original probeset/gene assignment in Affymetrix microarray and the existence of differences between annotations and effective alignments of probes and transcription products. In the current generation of Affymetrix human GeneChips, most probesets include probes matching transcripts from more than one gene and probes which do not match any transcribed sequence.'),
(91801, 2007, 'bmc', 'Application of a correlation correction factor in a microarray cross-platform reproducibility study', 'Archer, Kellie J|Dumur, Catherine I|Taylor, G Scott|Chaplin, Michael D|Guiseppi-Elie, Anthony|Grant, Geraldine|Ferreira-Gonzalez, Andrea|Garrett, Carleton T', 'Department of Biostatistics, Virginia Commonwealth University, 730 East Broad St,, Richmond, VA, USA. kjarcher@vcu.edu|Department of Biostatistics, Virginia Commonwealth University, 730 East Broad St,, Richmond, VA, USA. kjarcher@vcu.edu|Department of Biostatistics, Virginia Commonwealth University, 730 East Broad St,, Richmond, VA, USA. kjarcher@vcu.edu|Department of Biostatistics, Virginia Commonwealth University, 730 East Broad St,, Richmond, VA, USA. kjarcher@vcu.edu|Department of Biostatistics, Virginia Commonwealth University, 730 East Broad St,, Richmond, VA, USA. kjarcher@vcu.edu|Department of Biostatistics, Virginia Commonwealth University, 730 East Broad St,, Richmond, VA, USA. kjarcher@vcu.edu|Department of Biostatistics, Virginia Commonwealth University, 730 East Broad St,, Richmond, VA, USA. kjarcher@vcu.edu|Department of Biostatistics, Virginia Commonwealth University, 730 East Broad St,, Richmond, VA, USA. kjarcher@vcu.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Calibration|Gene Expression Profiling|Humans|Microarray Analysis|Statistics as Topic', 'Comparative Study', '10.1186/1471-2105-8-447', '18005444', 'Recent research examining cross-platform correlation of gene expression intensities has yielded mixed results. In this study, we demonstrate use of a correction factor for estimating cross-platform correlations.'),
(91802, 2007, 'bmc', 'PedGenie: meta genetic association testing in mixed family and case-control designs', 'Curtin, Karen|Wong, Jathine|Allen-Brady, Kristina|Camp, Nicola J', 'Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, USA. karen.curtin@hsc.utah.edu|Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, USA. karen.curtin@hsc.utah.edu|Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, USA. karen.curtin@hsc.utah.edu|Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, USA. karen.curtin@hsc.utah.edu', 'United States|United States|United States|United States', 0, 'Case-Control Studies|Chi-Square Distribution|Confidence Intervals|Family|Genetic Linkage|Genetic Testing|Genotype|Humans|Likelihood Functions|Meta-Analysis as Topic|Models, Genetic|Odds Ratio|Pedigree|Phenotype|Predictive Value of Tests|Research Design|Software', 'Journal Article', '10.1186/1471-2105-8-448', '18005446', 'PedGenie software, introduced in 2006, includes genetic association testing of cases and controls that may be independent or related (nuclear families or extended pedigrees) or mixtures thereof using Monte Carlo significance testing. Our aim is to demonstrate that PedGenie, a unique and flexible analysis tool freely available in Genie 2.4 software, is significantly enhanced by incorporating meta statistics for detecting genetic association with disease using data across multiple study groups.'),
(91803, 2007, 'bmc', 'A comparison of Affymetrix gene expression arrays', 'Robinson, Mark D|Speed, Terence P', 'Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3050, Australia. mrobinson@wehi.edu.au|Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3050, Australia. mrobinson@wehi.edu.au', 'Australia|Australia', 53, 'Equipment Design|Equipment Failure Analysis|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1186/1471-2105-8-449', '18005448', 'Affymetrix GeneChips are an important tool in many facets of biological research. Recently, notable design changes to the chips have been made. In this study, we use publicly available data from Affymetrix to gauge the performance of three human gene expression arrays: Human Genome U133 Plus 2.0 (U133), Human Exon 1.0 ST (HuEx) and Human Gene 1.0 ST (HuGene).'),
(91804, 2007, 'bmc', 'Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines', 'Tian, Jian|Wu, Ningfeng|Guo, Xuexia|Guo, Jun|Zhang, Juhua|Fan, Yunliu', 'Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China. tianjian3721@163.com|Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China. tianjian3721@163.com|Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China. tianjian3721@163.com|Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China. tianjian3721@163.com|Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China. tianjian3721@163.com|Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China. tianjian3721@163.com', 'China|China|China|China|China|China', 36, 'Algorithms|Artificial Intelligence|Base Sequence|DNA Mutational Analysis|Genetic Variation|Humans|Molecular Sequence Data|Pattern Recognition, Automated|Phenotype|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-8-450', '18005451', 'Human genetic variations primarily result from single nucleotide polymorphisms (SNPs) that occur approximately every 1000 bases in the overall human population. The non-synonymous SNPs (nsSNPs) that lead to amino acid changes in the protein product may account for nearly half of the known genetic variations linked to inherited human diseases. One of the key problems of medical genetics today is to identify nsSNPs that underlie disease-related phenotypes in humans. As such, the development of computational tools that can identify such nsSNPs would enhance our understanding of genetic diseases and help predict the disease.'),
(91805, 2007, 'bmc', 'Peptide ligand screening of alpha-synuclein aggregation modulators by in silico panning', 'Abe, Koichi|Kobayashi, Natsuki|Sode, Koji|Ikebukuro, Kazunori', 'Department of Biotechnology, Tokyo University of Agriculture and Technology, 2-24-13 Naka-cho, Koganei-shi, Tokyo, 184-8588, Japan. 50007831201@st.tuat.ac.jp|Department of Biotechnology, Tokyo University of Agriculture and Technology, 2-24-13 Naka-cho, Koganei-shi, Tokyo, 184-8588, Japan. 50007831201@st.tuat.ac.jp|Department of Biotechnology, Tokyo University of Agriculture and Technology, 2-24-13 Naka-cho, Koganei-shi, Tokyo, 184-8588, Japan. 50007831201@st.tuat.ac.jp|Department of Biotechnology, Tokyo University of Agriculture and Technology, 2-24-13 Naka-cho, Koganei-shi, Tokyo, 184-8588, Japan. 50007831201@st.tuat.ac.jp', 'Japan|Japan|Japan|Japan', 31, 'Amino Acid Sequence|Binding Sites|Computer Simulation|Dimerization|Drug Design|Ligands|Models, Chemical|Models, Molecular|Molecular Sequence Data|Multiprotein Complexes|Peptides|Protein Binding|Protein Conformation|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-8-451', '18005454', 'alpha-Synuclein is a Parkinsons-disease-related protein. It forms aggregates in vivo, and these aggregates cause cell cytotoxicity. Aggregation inhibitors are expected to reduce alpha-synuclein cytotoxicity, and an aggregation accelerator has recently been reported to reduce alpha-synuclein cytotoxicity. Therefore, amyloid aggregation modulating ligands are expected to serve as therapeutic medicines.'),
(91806, 2007, 'bmc', 'Inferring activity changes of transcription factors by binding association with sorted expression profiles', 'Cheng, Chao|Yan, Xiting|Sun, Fengzhu|Li, Lei M', 'Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089-2910, USA. chaochen@usc.edu|Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089-2910, USA. chaochen@usc.edu|Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089-2910, USA. chaochen@usc.edu|Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089-2910, USA. chaochen@usc.edu', 'United States|United States|United States|United States', 48, 'Algorithms|Base Sequence|Binding Sites|Gene Expression Profiling|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Structure-Activity Relationship|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-452', '18021409', 'The identification of transcription factors (TFs) associated with a biological process is fundamental to understanding its regulatory mechanisms. From microarray data, however, the activity changes of TFs often cannot be directly observed due to their relatively low expression levels, post-transcriptional modifications, and other complications. Several approaches have been proposed to infer TF activity changes from microarray data. In some models, a linear relationship between gene expression and TF-gene binding strength is assumed. In some other models, the target genes of a TF are first determined by a significance cutoff to binding affinity scores, and then expression differentiation is checked between the target and other genes.'),
(91807, 2007, 'bmc', 'Inferring biological functions and associated transcriptional regulators using gene set expression coherence analysis', 'Kim, Tae-Min|Chung, Yeun-Jun|Rhyu, Mun-Gan|Jung, Myeong Ho', 'Division of Metabolic Disease, Center for Biomedical Science, National Institute of Health, Nokbun-dong 5, Eunpyung-gu, Seoul, Republic of Korea. tmkim@catholic.ac.kr|Division of Metabolic Disease, Center for Biomedical Science, National Institute of Health, Nokbun-dong 5, Eunpyung-gu, Seoul, Republic of Korea. tmkim@catholic.ac.kr|Division of Metabolic Disease, Center for Biomedical Science, National Institute of Health, Nokbun-dong 5, Eunpyung-gu, Seoul, Republic of Korea. tmkim@catholic.ac.kr|Division of Metabolic Disease, Center for Biomedical Science, National Institute of Health, Nokbun-dong 5, Eunpyung-gu, Seoul, Republic of Korea. tmkim@catholic.ac.kr', '-|-|-|-', 8, 'Algorithms|Gene Expression Profiling|Multigene Family|Regression Analysis|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Structure-Activity Relationship|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-453', '18021416', 'Gene clustering has been widely used to group genes with similar expression pattern in microarray data analysis. Subsequent enrichment analysis using predefined gene sets can provide clues on which functional themes or regulatory sequence motifs are associated with individual gene clusters. In spite of the potential utility, gene clustering and enrichment analysis have been used in separate platforms, thus, the development of integrative algorithm linking both methods is highly challenging.'),
(91808, 2007, 'bmc', 'Transcription factor target prediction using multiple short expression time series from Arabidopsis thaliana', 'Redestig, Henning|Weicht, Daniel|Selbig, Joachim|Hannah, Matthew A', 'Max Planck Institute for Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam-Golm, Germany. redestig@mpimp-golm.mpg.de|Max Planck Institute for Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam-Golm, Germany. redestig@mpimp-golm.mpg.de|Max Planck Institute for Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam-Golm, Germany. redestig@mpimp-golm.mpg.de|Max Planck Institute for Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam-Golm, Germany. redestig@mpimp-golm.mpg.de', 'Germany|Germany|Germany|Germany', 0, 'Arabidopsis Proteins|Base Sequence|Binding Sites|DNA, Plant|Gene Expression Profiling|Gene Targeting|Molecular Sequence Data|Protein Binding|Sequence Analysis, DNA|Time Factors|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-454', '18021423', 'The central role of transcription factors (TFs) in higher eukaryotes has led to much interest in deciphering transcriptional regulatory interactions. Even in the best case, experimental identification of TF target genes is error prone, and has been shown to be improved by considering additional forms of evidence such as expression data. Previous expression based methods have not explicitly tried to associate TFs with their targets and therefore largely ignored the treatment specific and time dependent nature of transcription regulation.'),
(91809, 2007, 'bmc', 'Use of genomic DNA control features and predicted operon structure in microarray data analysis: ArrayLeaRNA - a Bayesian approach', 'Pin, Carmen|Reuter, Mark', 'Institute of Food Research, Norwich, NR4 7UA, UK. carmen.pin@bbsrc.ac.uk|Institute of Food Research, Norwich, NR4 7UA, UK. carmen.pin@bbsrc.ac.uk', 'United Kingdom|United Kingdom', 4, 'Algorithms|Bayes Theorem|Campylobacter jejuni|DNA, Complementary|Escherichia coli K12|Genome, Bacterial|Oligonucleotide Array Sequence Analysis|Operon|Software|Streptococcus pneumoniae', 'Comparative Study', '10.1186/1471-2105-8-455', '18021437', 'Microarrays are widely used for the study of gene expression, however deciding on whether observed differences in expression are significant remains a challenge.'),
(91810, 2007, 'bmc', 'The Firegoose: two-way integration of diverse data from different bioinformatics web resources with desktop applications', 'Bare, J Christopher|Shannon, Paul T|Schmid, Amy K|Baliga, Nitin S', 'Institute for Systems Biology, 1441 N 34th Street, Seattle, WA 98103, USA. cbare@systemsbiology.org|Institute for Systems Biology, 1441 N 34th Street, Seattle, WA 98103, USA. cbare@systemsbiology.org|Institute for Systems Biology, 1441 N 34th Street, Seattle, WA 98103, USA. cbare@systemsbiology.org|Institute for Systems Biology, 1441 N 34th Street, Seattle, WA 98103, USA. cbare@systemsbiology.org', 'United States|United States|United States|United States', 25, 'Computational Biology|Data Display|Databases, Genetic|Gene Expression Profiling|Halobacterium salinarum|Humans|Hypermedia|Information Dissemination|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Software Design|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-456', '18021453', 'Information resources on the World Wide Web play an indispensable role in modern biology. But integrating data from multiple sources is often encumbered by the need to reformat data files, convert between naming systems, or perform ongoing maintenance of local copies of public databases. Opportunities for new ways of combining and re-using data are arising as a result of the increasing use of web protocols to transmit structured data.'),
(91811, 2007, 'bmc', 'GEDI: a user-friendly toolbox for analysis of large-scale gene expression data', 'Fujita, André|Sato, João R|Ferreira, Carlos E|Sogayar, Mari C', 'Chemistry Institute, University of São Paulo, Av, Lineu Prestes, 748 - São Paulo, 05508-900, SP, Brazil. fujita@ime.usp.br|Chemistry Institute, University of São Paulo, Av, Lineu Prestes, 748 - São Paulo, 05508-900, SP, Brazil. fujita@ime.usp.br|Chemistry Institute, University of São Paulo, Av, Lineu Prestes, 748 - São Paulo, 05508-900, SP, Brazil. fujita@ime.usp.br|Chemistry Institute, University of São Paulo, Av, Lineu Prestes, 748 - São Paulo, 05508-900, SP, Brazil. fujita@ime.usp.br', 'Brazil|Brazil|Brazil|Brazil', 0, 'Algorithms|Artificial Intelligence|Chromosome Mapping|Computer Graphics|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-457', '18021455', 'Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experience difficulties when they attempting to use those methods in their research. Here we present an user-friendly toolbox which allows large-scale gene expression analysis to be carried out by biomedical researchers with limited programming skills.'),
(91812, 2007, 'bmc', 'Recodon: coalescent simulation of coding DNA sequences with recombination, migration and demography', 'Arenas, Miguel|Posada, David', 'Departamento de Bioquímica, Genética e Inmunología, Universidad de Vigo, 36310 Vigo, Spain. miguelab@uvigo.es|Departamento de Bioquímica, Genética e Inmunología, Universidad de Vigo, 36310 Vigo, Spain. miguelab@uvigo.es', 'Spain|Spain', 0, 'Codon|Computer Simulation|Emigration and Immigration|Evolution, Molecular|Gene Frequency|Genetic Variation|Genetics, Population|Humans|Models, Genetic|Population Growth|Recombination, Genetic|Selection, Genetic|Software', 'Journal Article', '10.1186/1471-2105-8-458', '18028540', 'Coalescent simulations have proven very useful in many population genetics studies. In order to arrive to meaningful conclusions, it is important that these simulations resemble the process of molecular evolution as much as possible. To date, no single coalescent program is able to simulate codon sequences sampled from populations with recombination, migration and growth.'),
(91813, 2007, 'bmc', 'Predicting peptides binding to MHC class II molecules using multi-objective evolutionary algorithms', 'Rajapakse, Menaka|Schmidt, Bertil|Feng, Lin|Brusic, Vladimir', 'Institute for Infocomm Research, 21 Heng Mui Keng Terrace, 119613 Singapore. menaka@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, 119613 Singapore. menaka@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, 119613 Singapore. menaka@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, 119613 Singapore. menaka@i2r.a-star.edu.sg', 'Singapore|Singapore|Singapore|Singapore', 0, 'Binding Sites|Computer Simulation|HLA Antigens|Models, Chemical|Peptides|Protein Binding|Protein Interaction Mapping|Protein Structure, Tertiary|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-8-459', '18031584', 'Peptides binding to Major Histocompatibility Complex (MHC) class II molecules are crucial for initiation and regulation of immune responses. Predicting peptides that bind to a specific MHC molecule plays an important role in determining potential candidates for vaccines. The binding groove in class II MHC is open at both ends, allowing peptides longer than 9-mer to bind. Finding the consensus motif facilitating the binding of peptides to a MHC class II molecule is difficult because of different lengths of binding peptides and varying location of 9-mer binding core. The level of difficulty increases when the molecule is promiscuous and binds to a large number of low affinity peptides. In this paper, we propose two approaches using multi-objective evolutionary algorithms (MOEA) for predicting peptides binding to MHC class II molecules. One uses the information from both binders and non-binders for self-discovery of motifs. The other, in addition, uses information from experimentally determined motifs for guided-discovery of motifs.'),
(91814, 2007, 'bmc', 'Dendroscope: An interactive viewer for large phylogenetic trees', 'Huson, Daniel H|Richter, Daniel C|Rausch, Christian|Dezulian, Tobias|Franz, Markus|Rupp, Regula', 'Center for Bioinformatics Tübingen (ZBIT), Eberhard-Karls-Universität Tübingen, Sand 14, 72076 Tübingen, Germany. huson@informatik.uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), Eberhard-Karls-Universität Tübingen, Sand 14, 72076 Tübingen, Germany. huson@informatik.uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), Eberhard-Karls-Universität Tübingen, Sand 14, 72076 Tübingen, Germany. huson@informatik.uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), Eberhard-Karls-Universität Tübingen, Sand 14, 72076 Tübingen, Germany. huson@informatik.uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), Eberhard-Karls-Universität Tübingen, Sand 14, 72076 Tübingen, Germany. huson@informatik.uni-tuebingen.de|Center for Bioinformatics Tübingen (ZBIT), Eberhard-Karls-Universität Tübingen, Sand 14, 72076 Tübingen, Germany. huson@informatik.uni-tuebingen.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Biological Evolution|Computer Graphics|Computer Simulation|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Models, Genetic|Pedigree|Phylogeny|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-460', '18034891', 'Research in evolution requires software for visualizing and editing phylogenetic trees, for increasingly very large datasets, such as arise in expression analysis or metagenomics, for example. It would be desirable to have a program that provides these services in an efficient and user-friendly way, and that can be easily installed and run on all major operating systems. Although a large number of tree visualization tools are freely available, some as a part of more comprehensive analysis packages, all have drawbacks in one or more domains. They either lack some of the standard tree visualization techniques or basic graphics and editing features, or they are restricted to small trees containing only tens of thousands of taxa. Moreover, many programs are difficult to install or are not available for all common operating systems.'),
(91815, 2007, 'bmc', 'In situ analysis of cross-hybridisation on microarrays and the inference of expression correlation', 'Casneuf, Tineke|Van de Peer, Yves|Huber, Wolfgang', 'Department of Plant Systems Biology, VIB, B-9052 Ghent, Belgium. tineke.casneuf@psb.ugent.be|Department of Plant Systems Biology, VIB, B-9052 Ghent, Belgium. tineke.casneuf@psb.ugent.be|Department of Plant Systems Biology, VIB, B-9052 Ghent, Belgium. tineke.casneuf@psb.ugent.be', 'Belgium|Belgium|Belgium', 0, 'Algorithms|Arabidopsis|Artifacts|Cluster Analysis|Data Display|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Pattern Recognition, Automated', 'Journal Article', '10.1186/1471-2105-8-461', '18039370', 'Microarray co-expression signatures are an important tool for studying gene function and relations between genes. In addition to genuine biological co-expression, correlated signals can result from technical deficiencies like hybridization of reporters with off-target transcripts. An approach that is able to distinguish these factors permits the detection of more biologically relevant co-expression signatures.'),
(91816, 2007, 'bmc', 'Dynamic simulation of regulatory networks using SQUAD', 'Di Cara, Alessandro|Garg, Abhishek|De Micheli, Giovanni|Xenarios, Ioannis|Mendoza, Luis', 'Swiss Institute of Bioinformatics, Vital-IT Group, Quartier Sorge - Batiment Genopode, CH-1015 Lausanne, Switzerland. alessandro.dicara@merckserono.net|Swiss Institute of Bioinformatics, Vital-IT Group, Quartier Sorge - Batiment Genopode, CH-1015 Lausanne, Switzerland. alessandro.dicara@merckserono.net|Swiss Institute of Bioinformatics, Vital-IT Group, Quartier Sorge - Batiment Genopode, CH-1015 Lausanne, Switzerland. alessandro.dicara@merckserono.net|Swiss Institute of Bioinformatics, Vital-IT Group, Quartier Sorge - Batiment Genopode, CH-1015 Lausanne, Switzerland. alessandro.dicara@merckserono.net|Swiss Institute of Bioinformatics, Vital-IT Group, Quartier Sorge - Batiment Genopode, CH-1015 Lausanne, Switzerland. alessandro.dicara@merckserono.net', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 50, 'Animals|Cell Differentiation|Cluster Analysis|Computer Graphics|Computer Simulation|Decision Trees|Enzymes|Homeostasis|Humans|Kinetics|Models, Biological|Nonlinear Dynamics|Protein Interaction Mapping|Signal Transduction|Software|Systems Biology|T-Lymphocytes, Helper-Inducer', 'Journal Article', '10.1186/1471-2105-8-462', '18039375', 'The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology.'),
(91817, 2007, 'bmc', 'Identification of DNA-binding proteins using support vector machines and evolutionary profiles', 'Kumar, Manish|Gromiha, Michael M|Raghava, Gajendra P S', 'Bioinformatics Centre, Institute of Microbial Technology, Sector 39A, Chandigarh-160036, India. manish@imtech.res.in|Bioinformatics Centre, Institute of Microbial Technology, Sector 39A, Chandigarh-160036, India. manish@imtech.res.in|Bioinformatics Centre, Institute of Microbial Technology, Sector 39A, Chandigarh-160036, India. manish@imtech.res.in', 'India|India|India', 149, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Base Sequence|Binding Sites|DNA-Binding Proteins|Evolution, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Binding|Sequence Analysis', 'Journal Article', '10.1186/1471-2105-8-463', '18042272', 'Identification of DNA-binding proteins is one of the major challenges in the field of genome annotation, as these proteins play a crucial role in gene-regulation. In this paper, we developed various SVM modules for predicting DNA-binding domains and proteins. All models were trained and tested on multiple datasets of non-redundant proteins.'),
(91818, 2007, 'bmc', 'Predicting RNA secondary structure by the comparative approach: how to select the homologous sequences', 'Engelen, Stéfan|Tahi, Fariza', 'Laboratoire IBISC - FRE CNRS 2873, CNRS, Université dEvry Val-dEssonne, Genopole, 523, place des Terrasses, 91000 Evry, France. stefan.engelen@ibisc.univ-evry.fr|Laboratoire IBISC - FRE CNRS 2873, CNRS, Université dEvry Val-dEssonne, Genopole, 523, place des Terrasses, 91000 Evry, France. stefan.engelen@ibisc.univ-evry.fr', 'France|France', 0, 'Algorithms|Base Pairing|Base Sequence|Computational Biology|Escherichia coli|Evolution, Molecular|Genetic Variation|Models, Genetic|RNA|Sequence Alignment|Sequence Homology', 'Comparative Study', '10.1186/1471-2105-8-464', '18045491', 'The secondary structure of an RNA must be known before the relationship between its structure and function can be determined. One way to predict the secondary structure of an RNA is to identify covarying residues that maintain the pairings (Watson-Crick, Wobble and non-canonical pairings). This comparative approach consists of identifying mutations from homologous sequence alignments. The sequences must covary enough for compensatory mutations to be revealed, but comparison is difficult if they are too different. Thus the choice of homologous sequences is critical. While many possible combinations of homologous sequences may be used for prediction, only a few will give good structure predictions. This can be due to poor quality alignment in stems or to the variability of certain sequences. This problem of sequence selection is currently unsolved.'),
(91819, 2007, 'bmc', 'SAT, a flexible and optimized Web application for SSR marker development', 'Dereeper, Alexis|Argout, Xavier|Billot, Claire|Rami, Jean-François|Ruiz, Manuel', 'CIRAD, UMR DAP, TA A-96/03, Avenue Agropolis, Montpellier, France. Alexis.Dereeper@igs.cnrs-mrs.fr|CIRAD, UMR DAP, TA A-96/03, Avenue Agropolis, Montpellier, France. Alexis.Dereeper@igs.cnrs-mrs.fr|CIRAD, UMR DAP, TA A-96/03, Avenue Agropolis, Montpellier, France. Alexis.Dereeper@igs.cnrs-mrs.fr|CIRAD, UMR DAP, TA A-96/03, Avenue Agropolis, Montpellier, France. Alexis.Dereeper@igs.cnrs-mrs.fr|CIRAD, UMR DAP, TA A-96/03, Avenue Agropolis, Montpellier, France. Alexis.Dereeper@igs.cnrs-mrs.fr', 'France|France|France|France|France', 33, 'Algorithms|Artificial Intelligence|Base Sequence|Genetic Markers|Internet|Microsatellite Repeats|Molecular Sequence Data|Pattern Recognition, Automated|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-8-465', '18047663', 'Simple Sequence Repeats (SSRs), or microsatellites, are among the most powerful genetic markers known. A common method for the development of SSR markers is the construction of genomic DNA libraries enriched for SSR sequences, followed by DNA sequencing. However, designing optimal SSR markers from bulk sequence data is a laborious and time-consuming process.'),
(91820, 2007, 'bmc', 'Subcellular location prediction of proteins using support vector machines with alignment of block sequences utilizing amino acid composition', 'Tamura, Takeyuki|Akutsu, Tatsuya', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. tamura@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. tamura@kuicr.kyoto-u.ac.jp', 'Japan|Japan', 44, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Cluster Analysis|Computational Biology|Databases, Protein|Internet|Intracellular Space|Models, Biological|Pattern Recognition, Automated|Plant Proteins|Predictive Value of Tests|Protein Transport|Reproducibility of Results|Sequence Alignment|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-8-466', '18047679', 'Subcellular location prediction of proteins is an important and well-studied problem in bioinformatics. This is a problem of predicting which part in a cell a given protein is transported to, where an amino acid sequence of the protein is given as an input. This problem is becoming more important since information on subcellular location is helpful for annotation of proteins and genes and the number of complete genomes is rapidly increasing. Since existing predictors are based on various heuristics, it is important to develop a simple method with high prediction accuracies.'),
(91821, 2007, 'bmc', 'Framework for a protein ontology', 'Natale, Darren A|Arighi, Cecilia N|Barker, Winona C|Blake, Judith|Chang, Ti-Cheng|Hu, Zhangzhi|Liu, Hongfang|Smith, Barry|Wu, Cathy H', 'Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, 3300 Whitehaven St, NW, Washington, DC 20007, USA. dan5@georgetown.edu|Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, 3300 Whitehaven St, NW, Washington, DC 20007, USA. dan5@georgetown.edu|Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, 3300 Whitehaven St, NW, Washington, DC 20007, USA. dan5@georgetown.edu|Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, 3300 Whitehaven St, NW, Washington, DC 20007, USA. dan5@georgetown.edu|Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, 3300 Whitehaven St, NW, Washington, DC 20007, USA. dan5@georgetown.edu|Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, 3300 Whitehaven St, NW, Washington, DC 20007, USA. dan5@georgetown.edu|Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, 3300 Whitehaven St, NW, Washington, DC 20007, USA. dan5@georgetown.edu|Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, 3300 Whitehaven St, NW, Washington, DC 20007, USA. dan5@georgetown.edu|Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, 3300 Whitehaven St, NW, Washington, DC 20007, USA. dan5@georgetown.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Database Management Systems|Databases, Protein|Evolution, Molecular|Information Storage and Retrieval|Proteins|Sequence Alignment|Sequence Analysis|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-S9-S1', '18047702', 'Biomedical ontologies are emerging as critical tools in genomic and proteomic research, where complex data in disparate resources need to be integrated. A number of ontologies describe properties that can be attributed to proteins. For example, protein functions are described by the Gene Ontology (GO) and human diseases by SNOMED CT or ICD10. There is, however, a gap in the current set of ontologies - one that describes the protein entities themselves and their relationships. We have designed the PRotein Ontology (PRO) to facilitate protein annotation and to guide new experiments. The components of PRO extend from the classification of proteins on the basis of evolutionary relationships to the representation of the multiple protein forms of a gene (products generated by genetic variation, alternative splicing, proteolytic cleavage, and other post-translational modifications). PRO will allow the specification of relationships between PRO, GO and other ontologies in the OBO Foundry. Here we describe the initial development of PRO, illustrated using human and mouse proteins involved in the transforming growth factor-beta and bone morphogenetic protein signaling pathways.'),
(91822, 2007, 'bmc', 'BioCAD: an information fusion platform for bio-network inference and analysis', 'Lee, Doheon|Kim, Sangwoo|Kim, Younghoon', 'Department of Bio and Brain Engineering, KAIST, 373-1 Guseong-Dong, Yuseong-Gu, Daejeon, 305-701, Republic of Korea. dhlee@biosoft.kaist.ac.kr|Department of Bio and Brain Engineering, KAIST, 373-1 Guseong-Dong, Yuseong-Gu, Daejeon, 305-701, Republic of Korea. dhlee@biosoft.kaist.ac.kr|Department of Bio and Brain Engineering, KAIST, 373-1 Guseong-Dong, Yuseong-Gu, Daejeon, 305-701, Republic of Korea. dhlee@biosoft.kaist.ac.kr', '-|-|-', 7, 'Computer Simulation|Databases, Factual|Internet|Models, Biological|Natural Language Processing|Protein Interaction Mapping|Proteome|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-S9-S2', '18047703', 'As systems biology has begun to draw growing attention, bio-network inference and analysis have become more and more important. Though there have been many efforts for bio-network inference, they are still far from practical applications due to too many false inferences and lack of comprehensible interpretation in the biological viewpoints. In order for applying to real problems, they should provide effective inference, reliable validation, rational elucidation, and sufficient extensibility to incorporate various relevant information sources.'),
(91823, 2007, 'bmc', 'GO for gene documents', 'Srinivasan, Padmini|Qiu, Xin Ying', 'School of Library and Information Science, University of Iowa, Iowa City, IA, USA. padmini-srinivasan@uiowa.edu|School of Library and Information Science, University of Iowa, Iowa City, IA, USA. padmini-srinivasan@uiowa.edu', 'United States|United States', 2, 'Artificial Intelligence|Database Management Systems|Databases, Protein|Documentation|Information Storage and Retrieval|Natural Language Processing|Proteins', 'Journal Article', '10.1186/1471-2105-8-S9-S3', '18047704', 'Annotating genes and their products with Gene Ontology codes is an important area of research. One approach is to use the information available about these genes in the biomedical literature. The goal in this paper, based on this approach, is to develop automatic annotation methods that can supplement the expensive manual annotation processes currently in place.'),
(91824, 2007, 'bmc', 'A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluation method', 'Yoo, Illhoi|Hu, Xiaohua|Song, Il-Yeol', 'Department of Health Management and Informatics, School of Medicine, University of Missouri-Columbia, USA. yooil@health.missouri.edu|Department of Health Management and Informatics, School of Medicine, University of Missouri-Columbia, USA. yooil@health.missouri.edu|Department of Health Management and Informatics, School of Medicine, University of Missouri-Columbia, USA. yooil@health.missouri.edu', 'United States|United States|United States', 37, 'Algorithms|Artificial Intelligence|Cluster Analysis|Database Management Systems|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Semantics|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-S9-S4', '18047705', 'A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free text, document clustering and text summarization together are used as a solution for text information overload problem. In this paper, we introduce a coherent graph-based semantic clustering and summarization approach for biomedical literature.'),
(91825, 2007, 'bmc', 'A comparison study on algorithms of detecting long forms for short forms in biomedical text', 'Torii, Manabu|Hu, Zhang-zhi|Song, Min|Wu, Cathy H|Liu, Hongfang', 'Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, 4000 Resevoir Rd, NW, Washington, DC 20057, USA. mt352@georgetown.edu|Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, 4000 Resevoir Rd, NW, Washington, DC 20057, USA. mt352@georgetown.edu|Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, 4000 Resevoir Rd, NW, Washington, DC 20057, USA. mt352@georgetown.edu|Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, 4000 Resevoir Rd, NW, Washington, DC 20057, USA. mt352@georgetown.edu|Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, 4000 Resevoir Rd, NW, Washington, DC 20057, USA. mt352@georgetown.edu', 'United States|United States|United States|United States|United States', 22, 'Algorithms|Artificial Intelligence|Cluster Analysis|Database Management Systems|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Semantics|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-S9-S5', '18047706', 'With more and more research dedicated to literature mining in the biomedical domain, more and more systems are available for people to choose from when building literature mining applications. In this study, we focus on one specific kind of literature mining task, i.e., detecting definitions of acronyms, abbreviations, and symbols in biomedical text. We denote acronyms, abbreviations, and symbols as short forms (SFs) and their corresponding definitions as long forms (LFs). The study was designed to answer the following questions, i) how well a system performs in detecting LFs from novel text, ii) what the coverage is for various terminological knowledge bases in including SFs as synonyms of their LFs, and iii) how to combine results from various SF knowledge bases.'),
(91826, 2007, 'bmc', 'Extracting unrecognized gene relationships from the biomedical literature via matrix factorizations', 'Kim, Hyunsoo|Park, Haesun|Drake, Barry L', 'College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, USA. hskim@cc.gatech.edu|College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, USA. hskim@cc.gatech.edu|College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, USA. hskim@cc.gatech.edu', 'Georgia|Georgia|Georgia', 12, 'Algorithms|Artificial Intelligence|Cluster Analysis|Database Management Systems|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Protein Interaction Mapping|Semantics|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-S9-S6', '18047707', 'The construction of literature-based networks of gene-gene interactions is one of the most important applications of text mining in bioinformatics. Extracting potential gene relationships from the biomedical literature may be helpful in building biological hypotheses that can be explored further experimentally. Recently, latent semantic indexing based on the singular value decomposition (LSI/SVD) has been applied to gene retrieval. However, the determination of the number of factors k used in the reduced rank matrix is still an open problem.'),
(91827, 2007, 'bmc', 'Proceedings of the Fourth Annual Conference of the MidSouth Computational Biology and Bioinformatics Society', 'Wilkins, Dawn|Gusev, Yuriy|Loganantharaj, Raja|Bridges, Susan|Winters-Hilt, Stephen|Wren, Jonathan D', 'Computer & Information Science Department, The University of Mississippi, University, MS, USA. dwilkins@cs.olemiss.edu|Computer & Information Science Department, The University of Mississippi, University, MS, USA. dwilkins@cs.olemiss.edu|Computer & Information Science Department, The University of Mississippi, University, MS, USA. dwilkins@cs.olemiss.edu|Computer & Information Science Department, The University of Mississippi, University, MS, USA. dwilkins@cs.olemiss.edu|Computer & Information Science Department, The University of Mississippi, University, MS, USA. dwilkins@cs.olemiss.edu|Computer & Information Science Department, The University of Mississippi, University, MS, USA. dwilkins@cs.olemiss.edu', 'United States|United States|United States|United States|United States|United States', 1, 'Artificial Intelligence|Combinatorial Chemistry Techniques|Computational Biology|Gene Expression Profiling|Genomics|Oligonucleotide Array Sequence Analysis', 'Congress', '10.1186/1471-2105-8-S7-S1', '18047708', '-'),
(91828, 2007, 'bmc', 'Nanopore current transduction analysis of protein binding to non-terminal and terminal DNA regions: analysis of transcription factor binding, retroviral DNA terminus dynamics, and retroviral integrase-DNA binding', 'Winters-Hilt, Stephen|Davis, Amanda|Amin, Iftekhar|Morales, Eric', 'Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu', 'United States|United States|United States|United States', 8, 'Algorithms|Binding Sites|DNA, Viral|Integrases|Nanostructures|Porosity|Protein Binding|Protein Interaction Mapping|Retroviridae|Sequence Analysis, DNA|Sequence Analysis, Protein|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-S7-S10', '18047709', 'Synthetic transcription factors (STFs) promise to offer a powerful new therapeutic against Cancer, AIDS, and genetic disease. Currently, 10% of drugs are of this type, including salicylate and tamoxifen. STFs that can appropriately target (and release) their transcription factor binding sites on native genomic DNA provide a means to directly influence cellular mRNA production. An effective mechanism for screening amongst transcription factor (TF) candidates would itself be highly valued, and such may be possible with nanopore cheminformatics methods.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91829, 2007, 'bmc', 'Preliminary nanopore cheminformatics analysis of aptamer-target binding strength', 'Thomson, Karen|Amin, Iftekhar|Morales, Eric|Winters-Hilt, Stephen', 'Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. kthomson@uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. kthomson@uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. kthomson@uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. kthomson@uno.edu', 'United States|United States|United States|United States', 12, 'Antibodies|Aptamers, Nucleotide|Bacterial Toxins|Biosensing Techniques|Equipment Design|Equipment Failure Analysis|Hemolysin Proteins|Immunoassay|Nanotechnology|Pilot Projects|Porosity|Reproducibility of Results|Sensitivity and Specificity|Transducers', 'Journal Article', '10.1186/1471-2105-8-S7-S11', '18047710', 'Aptamers are nucleic acids selected for their ability to bind to molecules of interest and may provide the basis for a whole new class of medicines. If the aptamer is simply a dsDNA molecule with a ssDNA overhang (a sticky end) then the segment of ssDNA that complements that overhang provides a known binding target with binding strength adjustable according to length of overhang.'),
(91830, 2007, 'bmc', 'Analysis of nanopore detector measurements using Machine-Learning methods, with application to single-molecule kinetic analysis', 'Landry, Matthew|Winters-Hilt, Stephen', 'Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. mlandry@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. mlandry@cs.uno.edu', 'United States|United States', 6, 'Algorithms|Aptamers, Nucleotide|Artificial Intelligence|Bacterial Toxins|Biosensing Techniques|Equipment Design|Equipment Failure Analysis|Hemolysin Proteins|Kinetics|Nanotechnology|Pattern Recognition, Automated|Porosity|Reproducibility of Results|Sensitivity and Specificity|Transducers', 'Journal Article', '10.1186/1471-2105-8-S7-S12', '18047711', 'A nanopore detector has a nanometer-scale trans-membrane channel across which a potential difference is established, resulting in an ionic current through the channel in the pA-nA range. A distinctive channel current blockade signal is created as individually captured DNA molecules interact with the channel and modulate the channels ionic current. The nanopore detector is sensitive enough that nearly identical DNA molecules can be classified with very high accuracy using machine learning techniques such as Hidden Markov Models (HMMs) and Support Vector Machines (SVMs).'),
(91831, 2007, 'bmc', 'Comparison of probabilistic Boolean network and dynamic Bayesian network approaches for inferring gene regulatory networks', 'Li, Peng|Zhang, Chaoyang|Perkins, Edward J|Gong, Ping|Deng, Youping', 'School of Computing, University of Southern Mississippi, Hattiesburg, MS 39406, USA. peng.li@usm.edu|School of Computing, University of Southern Mississippi, Hattiesburg, MS 39406, USA. peng.li@usm.edu|School of Computing, University of Southern Mississippi, Hattiesburg, MS 39406, USA. peng.li@usm.edu|School of Computing, University of Southern Mississippi, Hattiesburg, MS 39406, USA. peng.li@usm.edu|School of Computing, University of Southern Mississippi, Hattiesburg, MS 39406, USA. peng.li@usm.edu', 'United States|United States|United States|United States|United States', 0, 'Animals|Data Interpretation, Statistical|Drosophila|Drosophila Proteins|Gene Expression Profiling|Gene Expression Regulation|Logistic Models|Models, Biological|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Signal Transduction', 'Comparative Study', '10.1186/1471-2105-8-S7-S13', '18047712', 'The regulation of gene expression is achieved through gene regulatory networks (GRNs) in which collections of genes interact with one another and other substances in a cell. In order to understand the underlying function of organisms, it is necessary to study the behavior of genes in a gene regulatory network context. Several computational approaches are available for modeling gene regulatory networks with different datasets. In order to optimize modeling of GRN, these approaches must be compared and evaluated in terms of accuracy and efficiency.'),
(91832, 2007, 'bmc', 'Duration learning for analysis of nanopore ionic current blockades', 'Churbanov, Alexander|Baribault, Carl|Winters-Hilt, Stephen', 'The Research Institute for Children, 200 Henry Clay Ave, New Orleans, LA 70118, USA. atchourb@cs.uno.edu|The Research Institute for Children, 200 Henry Clay Ave, New Orleans, LA 70118, USA. atchourb@cs.uno.edu|The Research Institute for Children, 200 Henry Clay Ave, New Orleans, LA 70118, USA. atchourb@cs.uno.edu', 'United States|United States|United States', 11, 'Algorithms|Aptamers, Nucleotide|Artificial Intelligence|Bacterial Toxins|Biosensing Techniques|Equipment Design|Equipment Failure Analysis|Hemolysin Proteins|Ion Channel Gating|Kinetics|Membrane Potentials|Nanotechnology|Pattern Recognition, Automated|Porosity|Reproducibility of Results|Sensitivity and Specificity|Transducers', 'Journal Article', '10.1186/1471-2105-8-S7-S14', '18047713', 'Ionic current blockade signal processing, for use in nanopore detection, offers a promising new way to analyze single molecule properties, with potential implications for DNA sequencing. The alpha-Hemolysin transmembrane channel interacts with a translocating molecule in a nontrivial way, frequently evidenced by a complex ionic flow blockade pattern. Typically, recorded current blockade signals have several levels of blockade, with various durations, all obeying a fixed statistical profile for a given molecule. Hidden Markov Model (HMM) based duration learning experiments on artificial two-level Gaussian blockade signals helped us to identify proper modeling framework. We then apply our framework to the real multi-level DNA hairpin blockade signal.'),
(91833, 2007, 'bmc', 'Analysis of circadian pattern reveals tissue-specific alternative transcription in leptin signaling pathway', 'Ptitsyn, Andrey A|Gimble, Jeffrey M', 'Experimental Obesity Laboratory, Louisiana State University Pennington Biomedical Research Center, 6400 Perkins Rd, Baton Rouge, LA 70808, USA. Andrey.Ptitsyn@colostate.edu|Experimental Obesity Laboratory, Louisiana State University Pennington Biomedical Research Center, 6400 Perkins Rd, Baton Rouge, LA 70808, USA. Andrey.Ptitsyn@colostate.edu', 'United States|United States', 16, 'Adipose Tissue, Brown|Animals|Biological Clocks|Circadian Rhythm|Leptin|Mice|Models, Biological|Oscillometry|Pattern Recognition, Automated|Signal Transduction|Suppressor of Cytokine Signaling 3 Protein|Suppressor of Cytokine Signaling Proteins|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1186/1471-2105-8-S7-S15', '18047714', 'It has been previously reported that most mammalian genes display a circadian oscillation in their baseline expression. Consequently, the phase and amplitude of each component of a signal transduction cascade has downstream consequences.'),
(91834, 2007, 'bmc', 'Computational analysis of biological functions and pathways collectively targeted by co-expressed microRNAs in cancer', 'Gusev, Yuriy|Schmittgen, Thomas D|Lerner, Megan|Postier, Russell|Brackett, Daniel', 'Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA. yuriy-gusev@ouhsc.edu|Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA. yuriy-gusev@ouhsc.edu|Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA. yuriy-gusev@ouhsc.edu|Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA. yuriy-gusev@ouhsc.edu|Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA. yuriy-gusev@ouhsc.edu', 'United States|United States|United States|United States|United States', 0, 'Animals|Computer Simulation|Gene Targeting|Humans|MicroRNAs|Models, Genetic|Neoplasms|Sequence Analysis, RNA|Signal Transduction|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-8-S7-S16', '18047715', 'Multiple recent studies have found aberrant expression profiles of microRNAome in human cancers. While several target genes have been experimentally identified for some microRNAs in various tumors, the global pattern of cellular functions and pathways affected by co-expressed microRNAs in cancer remains elusive. The goal of this study was to develop a computational approach to global analysis of the major biological processes and signaling pathways that are most likely to be affected collectively by co-expressed microRNAs in cancer cells.'),
(91835, 2007, 'bmc', 'Automatic delineation of malignancy in histopathological head and neck slides', 'Mete, Mutlu|Xu, Xiaowei|Fan, Chun-Yang|Shafirstein, Gal', 'Department of Applied Science, University of Arkansas at Little Rock, Little Rock, Arkansas, USA. mxmete@ualr.edu|Department of Applied Science, University of Arkansas at Little Rock, Little Rock, Arkansas, USA. mxmete@ualr.edu|Department of Applied Science, University of Arkansas at Little Rock, Little Rock, Arkansas, USA. mxmete@ualr.edu|Department of Applied Science, University of Arkansas at Little Rock, Little Rock, Arkansas, USA. mxmete@ualr.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Cluster Analysis|Head and Neck Neoplasms|Humans|Image Enhancement|Image Interpretation, Computer-Assisted|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-8-S7-S17', '18047716', 'Histopathology, which is one of the most important routines of all laboratory procedures used in pathology, is decisive for the diagnosis of cancer. Experienced histopathologists review the histological slides acquired from biopsy specimen in order to outline malignant areas. Recently, improvements in imaging technologies in terms of histological image analysis led to the discovery of virtual histological slides. In this technique, a computerized microscope scans a glass slide and generates virtual slides at a resolution of 0.25 mum/pixel. As the recognition of intrinsic cancer areas is time consuming and error prone, in this study we develop a novel method to tackle automatic squamous cell carcinoma of the head and neck detection problem in high-resolution, wholly-scanned histopathological slides.'),
(91836, 2007, 'bmc', 'SVM clustering', 'Winters-Hilt, Stephen|Merat, Sam', 'Department of Computer Science, University of New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, LA 70148, USA. winters@cs.uno.edu', 'United States|United States', 15, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computer Simulation|Models, Biological|Pattern Recognition, Automated', 'Journal Article', '10.1186/1471-2105-8-S7-S18', '18047717', 'Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being considered in a number of different ways.'),
(91837, 2007, 'bmc', 'A novel, fast, HMM-with-Duration implementation - for application with a new, pattern recognition informed, nanopore detector', 'Winters-Hilt, Stephen|Baribault, Carl', 'Dept. of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Dept. of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu', 'United States|United States', 12, 'Algorithms|Aptamers, Nucleotide|Artificial Intelligence|Bacterial Toxins|Biosensing Techniques|Data Interpretation, Statistical|Equipment Design|Equipment Failure Analysis|Hemolysin Proteins|Kinetics|Markov Chains|Nanotechnology|Pattern Recognition, Automated|Porosity|Reproducibility of Results|Sensitivity and Specificity|Transducers', 'Journal Article', '10.1186/1471-2105-8-S7-S19', '18047718', 'Hidden Markov Models (HMMs) provide an excellent means for structure identification and feature extraction on stochastic sequential data. An HMM-with-Duration (HMMwD) is an HMM that can also exactly model the hidden-label length (recurrence) distributions - while the regular HMM will impose a best-fit geometric distribution in its modeling/representation.'),
(91838, 2007, 'bmc', 'Systems biology approach for mapping the response of human urothelial cells to infection by Enterococcus faecalis', 'Dozmorov, Mikhail G|Kyker, Kimberly D|Saban, Ricardo|Shankar, Nathan|Baghdayan, Arto S|Centola, Michael B|Hurst, Robert E', 'Department of Urology, College of Medicine, Oklahoma University Health Sciences Center, PO Box 26901, Oklahoma City, OK 73190, USA. Mikhail-Dozmorov@ouhsc.edu|Department of Urology, College of Medicine, Oklahoma University Health Sciences Center, PO Box 26901, Oklahoma City, OK 73190, USA. Mikhail-Dozmorov@ouhsc.edu|Department of Urology, College of Medicine, Oklahoma University Health Sciences Center, PO Box 26901, Oklahoma City, OK 73190, USA. Mikhail-Dozmorov@ouhsc.edu|Department of Urology, College of Medicine, Oklahoma University Health Sciences Center, PO Box 26901, Oklahoma City, OK 73190, USA. Mikhail-Dozmorov@ouhsc.edu|Department of Urology, College of Medicine, Oklahoma University Health Sciences Center, PO Box 26901, Oklahoma City, OK 73190, USA. Mikhail-Dozmorov@ouhsc.edu|Department of Urology, College of Medicine, Oklahoma University Health Sciences Center, PO Box 26901, Oklahoma City, OK 73190, USA. Mikhail-Dozmorov@ouhsc.edu|Department of Urology, College of Medicine, Oklahoma University Health Sciences Center, PO Box 26901, Oklahoma City, OK 73190, USA. Mikhail-Dozmorov@ouhsc.edu', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Cells, Cultured|Chromosome Mapping|Enterococcus faecalis|Epithelial Cells|Gene Expression Profiling|Gene Expression Regulation|Genetic Variation|Humans|Proteome|Systems Biology|Urothelium', 'Journal Article', '10.1186/1471-2105-8-S7-S2', '18047719', 'To better understand the response of urinary epithelial (urothelial) cells to Enterococcus faecalis, a uropathogen that exhibits resistance to multiple antibiotics, a genome-wide scan of gene expression was obtained as a time series from urothelial cells growing as a layered 3-dimensional culture similar to normal urothelium. We herein describe a novel means of analysis that is based on deconvolution of gene variability into technical and biological components.'),
(91839, 2007, 'bmc', 'Nanopore-based kinetics analysis of individual antibody-channel and antibody-antigen interactions', 'Winters-Hilt, Stephen|Morales, Eric|Amin, Iftekhar|Stoyanov, Alexander', 'The Research Institute for Children, 200 Henry Clay Ave, New Orleans, LA 70118, USA. winters@cs.uno.edu|The Research Institute for Children, 200 Henry Clay Ave, New Orleans, LA 70118, USA. winters@cs.uno.edu|The Research Institute for Children, 200 Henry Clay Ave, New Orleans, LA 70118, USA. winters@cs.uno.edu|The Research Institute for Children, 200 Henry Clay Ave, New Orleans, LA 70118, USA. winters@cs.uno.edu', 'United States|United States|United States|United States', 6, 'Algorithms|Antigen-Antibody Complex|Artificial Intelligence|Bacterial Toxins|Biosensing Techniques|Equipment Design|Equipment Failure Analysis|Hemolysin Proteins|Immunoassay|Kinetics|Nanotechnology|Pattern Recognition, Automated|Porosity|Reproducibility of Results|Sensitivity and Specificity|Transducers', 'Journal Article', '10.1186/1471-2105-8-S7-S20', '18047720', 'The UNO/RIC Nanopore Detector provides a new way to study the binding and conformational changes of individual antibodies. Many critical questions regarding antibody function are still unresolved, questions that can be approached in a new way with the nanopore detector.'),
(91840, 2007, 'bmc', 'A survey of DNA motif finding algorithms', 'Das, Modan K|Dai, Ho-Kwok', 'Computer Science Department, Oklahoma State University, Stillwater, Oklahoma 74078, USA. mkdas@email.arizona.edu|Computer Science Department, Oklahoma State University, Stillwater, Oklahoma 74078, USA. mkdas@email.arizona.edu', 'United States|United States', 300, 'Algorithms|Base Sequence|Binding Sites|DNA|Molecular Sequence Data|Promoter Regions, Genetic|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Comparative Study', '10.1186/1471-2105-8-S7-S21', '18047721', 'Unraveling the mechanisms that regulate gene expression is a major challenge in biology. An important task in this challenge is to identify regulatory elements, especially the binding sites in deoxyribonucleic acid (DNA) for transcription factors. These binding sites are short DNA segments that are called motifs. Recent advances in genome sequence availability and in high-throughput gene expression analysis technologies have allowed for the development of computational methods for motif finding. As a result, a large number of motif finding algorithms have been implemented and applied to various motif models over the past decade. This survey reviews the latest developments in DNA motif finding algorithms.'),
(91841, 2007, 'bmc', 'Comparison of gene expression profiles altered by comfrey and riddelliine in rat liver', 'Guo, Lei|Mei, Nan|Dial, Stacey|Fuscoe, James|Chen, Tao', 'Division of Systems Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov', 'United States|United States|United States|United States|United States', 0, 'Animals|Carcinogenicity Tests|Carcinogens|Comfrey|Gene Expression Profiling|Gene Expression Regulation|Liver|Proteome|Pyrrolizidine Alkaloids|Rats|Signal Transduction', 'Comparative Study', '10.1186/1471-2105-8-S7-S22', '18047722', 'Comfrey (Symphytum officinale) is a perennial plant and has been consumed by humans as a vegetable, a tea and an herbal medicine for more than 2000 years. It, however, is hepatotoxic and carcinogenic in experimental animals and hepatotoxic in humans. Pyrrolizidine alkaloids (PAs) exist in many plants and many of them cause liver toxicity and/or cancer in humans and experimental animals. In our previous study, we found that the mutagenicity of comfrey was associated with the PAs contained in the plant. Therefore, we suggest that carcinogenicity of comfrey result from those PAs. To confirm our hypothesis, we compared the expression of genes and processes of biological functions that were altered by comfrey (mixture of the plant with PAs) and riddelliine (a prototype of carcinogenic PA) in rat liver for carcinogenesis in this study.'),
(91842, 2007, 'bmc', 'Prediction of peptides observable by mass spectrometry applied at the experimental set level', 'Sanders, William S|Bridges, Susan M|McCarthy, Fiona M|Nanduri, Bindu|Burgess, Shane C', 'Department of Biochemistry & Molecular Biology, Mississippi State University, MS, USA. wss2@msstate.edu|Department of Biochemistry & Molecular Biology, Mississippi State University, MS, USA. wss2@msstate.edu|Department of Biochemistry & Molecular Biology, Mississippi State University, MS, USA. wss2@msstate.edu|Department of Biochemistry & Molecular Biology, Mississippi State University, MS, USA. wss2@msstate.edu|Department of Biochemistry & Molecular Biology, Mississippi State University, MS, USA. wss2@msstate.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Databases, Protein|Mass Spectrometry|Molecular Sequence Data|Pattern Recognition, Automated|Peptide Mapping|Proteins|Research|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-8-S7-S23', '18047723', 'When proteins are subjected to proteolytic digestion and analyzed by mass spectrometry using a method such as 2D LC MS/MS, only a portion of the proteotypic peptides associated with each protein will be observed. The ability to predict which peptides can and cannot potentially be observed for a particular experimental dataset has several important applications in proteomics research including calculation of peptide coverage in terms of potentially detectable peptides, systems biology analysis of data sets, and protein quantification.'),
(91843, 2007, 'bmc', 'ProtQuant: a tool for the label-free quantification of MudPIT proteomics data', 'Bridges, Susan M|Magee, G Bryce|Wang, Nan|Williams, W Paul|Burgess, Shane C|Nanduri, Bindu', 'Department of Computer Science and Engineering, Mississippi State University, Starkville, MS 39762, USA. bridges@cse.msstate.edu|Department of Computer Science and Engineering, Mississippi State University, Starkville, MS 39762, USA. bridges@cse.msstate.edu|Department of Computer Science and Engineering, Mississippi State University, Starkville, MS 39762, USA. bridges@cse.msstate.edu|Department of Computer Science and Engineering, Mississippi State University, Starkville, MS 39762, USA. bridges@cse.msstate.edu|Department of Computer Science and Engineering, Mississippi State University, Starkville, MS 39762, USA. bridges@cse.msstate.edu|Department of Computer Science and Engineering, Mississippi State University, Starkville, MS 39762, USA. bridges@cse.msstate.edu', 'United States|United States|United States|United States|United States|United States', 45, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Data Interpretation, Statistical|Databases, Protein|Mass Spectrometry|Molecular Sequence Data|Pattern Recognition, Automated|Peptide Mapping|Proteins|Research|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-8-S7-S24', '18047724', 'Effective and economical methods for quantitative analysis of high throughput mass spectrometry data are essential to meet the goals of directly identifying, characterizing, and quantifying proteins from a particular cell state. Multidimensional Protein Identification Technology (MudPIT) is a common approach used in protein identification. Two types of methods are used to detect differential protein expression in MudPIT experiments: those involving stable isotope labelling and the so-called label-free methods. Label-free methods are based on the relationship between protein abundance and sampling statistics such as peptide count, spectral count, probabilistic peptide identification scores, and sum of peptide Sequest XCorr scores (SigmaXCorr). Although a number of label-free methods for protein quantification have been described in the literature, there are few publicly available tools that implement these methods. We describe ProtQuant, a Java-based tool for label-free protein quantification that uses the previously published SigmaXCorr method for quantification and includes an improved method for handling missing data.'),
(91844, 2007, 'bmc', 'Towards validating the hypothesis of phylogenetic profiling', 'Loganantharaj, Raja|Atwi, Mazen', 'Bioinformatics Research Lab, The Center for Advanced Computer Studies, PO Box 44330, University of Louisiana, Lafayette, LA 70504, USA. logan@cacs.louisiana.edu|Bioinformatics Research Lab, The Center for Advanced Computer Studies, PO Box 44330, University of Louisiana, Lafayette, LA 70504, USA. logan@cacs.louisiana.edu', 'United States|United States', 11, 'Animals|Biological Evolution|Chromosome Mapping|Conserved Sequence|Evolution, Molecular|Genome|Humans|Mice|Models, Genetic|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Species Specificity', 'Evaluation Studies', '10.1186/1471-2105-8-S7-S25', '18047725', 'As the number of fully sequenced genome increases, the need is greater for bioinformatics to predict or annotate genes of a newly sequenced genome. Ever since Eisenberg and his colleagues introduced phylogenetic profiling for assigning or predicting protein functions using comparative genomic analysis, the approach has been used in predicting function of some prokaryotic genomes quite successfully. Very little work has been reported in functional prediction of eukaryotes such as mouse and Homo sapiens species from phylogenetic profiles.'),
(91845, 2007, 'bmc', 'Metabonomics evaluations of age-related changes in the urinary compositions of male Sprague Dawley rats and effects of data normalization methods on statistical and quantitative analysis', 'Schnackenberg, Laura K|Sun, Jinchun|Espandiari, Parvaneh|Holland, Ricky D|Hanig, Joseph|Beger, Richard D', 'National Center for Toxicological Research (NCTR), Jefferson, AR 72079, USA. laura.schnackenberg@fda.hhs.gov|National Center for Toxicological Research (NCTR), Jefferson, AR 72079, USA. laura.schnackenberg@fda.hhs.gov|National Center for Toxicological Research (NCTR), Jefferson, AR 72079, USA. laura.schnackenberg@fda.hhs.gov|National Center for Toxicological Research (NCTR), Jefferson, AR 72079, USA. laura.schnackenberg@fda.hhs.gov|National Center for Toxicological Research (NCTR), Jefferson, AR 72079, USA. laura.schnackenberg@fda.hhs.gov|National Center for Toxicological Research (NCTR), Jefferson, AR 72079, USA. laura.schnackenberg@fda.hhs.gov', 'United States|United States|United States|United States|United States|United States', 47, 'Aging|Animals|Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation, Developmental|Male|Proteome|Rats|Rats, Sprague-Dawley|Rats, Wistar|Rats, Zucker|Species Specificity|Urinalysis', 'Journal Article', '10.1186/1471-2105-8-S7-S3', '18047726', 'Urine from male Sprague-Dawley rats 25, 40, and 80 days old was analyzed by NMR and UPLC/MS. The effects of data normalization procedures on principal component analysis (PCA) and quantitative analysis of NMR-based metabonomics data were investigated. Additionally, the effects of age on the metabolic profiles were examined by both NMR and UPLC/MS analyses.'),
(91846, 2007, 'bmc', 'Gene expression changes induced by the tumorigenic pyrrolizidine alkaloid riddelliine in liver of Big Blue rats', 'Mei, Nan|Guo, Lei|Liu, Ruqing|Fuscoe, James C|Chen, Tao', 'Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov', 'United States|United States|United States|United States|United States', 0, 'Animals|Carcinogenicity Tests|Carcinogens|Gene Expression Profiling|Gene Expression Regulation|Liver|Proteome|Pyrrolizidine Alkaloids|Rats|Signal Transduction', 'Journal Article', '10.1186/1471-2105-8-S7-S4', '18047727', 'Pyrrolizidine alkaloids (PAs) are probably the most common plant constituents that poison livestock, wildlife, and humans worldwide. Riddelliine is isolated from plants grown in the western United States and is a prototype of genotoxic PAs. Riddelliine was used to investigate the genotoxic effects of PAs via analysis of gene expression in the target tissue of rats in this study. Previously we observed that the mutant frequency in the liver of rats gavaged with riddelliine was 3-fold higher than that in the control group. Molecular analysis of the mutants indicated that there was a statistically significant difference between the mutational spectra from riddelliine-treated and control rats.'),
(91847, 2007, 'bmc', 'Structure and function predictions of the Msa protein in Staphylococcus aureus', 'Nagarajan, Vijayaraj|Elasri, Mohamed O', 'Department of Biological Sciences, The University of Southern Mississippi, Hattiesburg, MS 39406, USA. vijayaraj.nagarajan@usm.edu|Department of Biological Sciences, The University of Southern Mississippi, Hattiesburg, MS 39406, USA. vijayaraj.nagarajan@usm.edu', 'United States|United States', 0, 'Amino Acid Sequence|Base Sequence|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Conformation|Sequence Alignment|Sequence Analysis|Staphylococcus aureus|Structure-Activity Relationship|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-S7-S5', '18047728', 'Staphylococcus aureus is a human pathogen that causes a wide variety of life-threatening infections using a large number of virulence factors. One of the major global regulators used by S. aureus is the staphylococcal accessory regulator (sarA). We have identified and characterized a new gene (modulator of sarA: msa) that modulates the expression of sarA. Genetic and functional analysis shows that msa has a global effect on gene expression in S. aureus. However, the mechanism of Msa function is still unknown. Function predictions of Msa are complicated by the fact that it does not have a homologous partner in any other organism. This work aims at predicting the structure and function of the Msa protein.'),
(91848, 2007, 'bmc', 'Statistical tools for transgene copy number estimation based on real-time PCR', 'Yuan, Joshua S|Burris, Jason|Stewart, Nathan R|Mentewab, Ayalew|Stewart, C Neal', 'Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA. syuan@utk.edu|Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA. syuan@utk.edu|Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA. syuan@utk.edu|Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA. syuan@utk.edu|Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA. syuan@utk.edu', 'United States|United States|United States|United States|United States', 52, 'Algorithms|Base Sequence|Chromosome Mapping|Data Interpretation, Statistical|Gene Dosage|Molecular Sequence Data|Reverse Transcriptase Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-8-S7-S6', '18047729', 'As compared with traditional transgene copy number detection technologies such as Southern blot analysis, real-time PCR provides a fast, inexpensive and high-throughput alternative. However, the real-time PCR based transgene copy number estimation tends to be ambiguous and subjective stemming from the lack of proper statistical analysis and data quality control to render a reliable estimation of copy number with a prediction value. Despite the recent progresses in statistical analysis of real-time PCR, few publications have integrated these advancements in real-time PCR based transgene copy number determination.'),
(91849, 2007, 'bmc', 'Cloning, analysis and functional annotation of expressed sequence tags from the Earthworm Eisenia fetida', 'Pirooznia, Mehdi|Gong, Ping|Guan, Xin|Inouye, Laura S|Yang, Kuan|Perkins, Edward J|Deng, Youping', 'Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, MS 39406, USA. Mehdi.Pirooznia@usm.edu|Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, MS 39406, USA. Mehdi.Pirooznia@usm.edu|Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, MS 39406, USA. Mehdi.Pirooznia@usm.edu|Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, MS 39406, USA. Mehdi.Pirooznia@usm.edu|Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, MS 39406, USA. Mehdi.Pirooznia@usm.edu|Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, MS 39406, USA. Mehdi.Pirooznia@usm.edu|Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, MS 39406, USA. Mehdi.Pirooznia@usm.edu', 'United States|United States|United States|United States|United States|United States|United States', 48, 'Animals|Base Sequence|Chromosome Mapping|Cloning, Molecular|Explosive Agents|Expressed Sequence Tags|Molecular Sequence Data|Oligochaeta|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-8-S7-S7', '18047730', 'Eisenia fetida, commonly known as red wiggler or compost worm, belongs to the Lumbricidae family of the Annelida phylum. Little is known about its genome sequence although it has been extensively used as a test organism in terrestrial ecotoxicology. In order to understand its gene expression response to environmental contaminants, we cloned 4032 cDNAs or expressed sequence tags (ESTs) from two E. fetida libraries enriched with genes responsive to ten ordnance related compounds using suppressive subtractive hybridization-PCR.'),
(91850, 2007, 'bmc', 'Robust clustering in high dimensional data using statistical depths', 'Ding, Yuanyuan|Dang, Xin|Peng, Hanxiang|Wilkins, Dawn', 'Computer & Information Science Department, The University of Mississippi, University, MS, USA. yding@olemiss.edu|Computer & Information Science Department, The University of Mississippi, University, MS, USA. yding@olemiss.edu|Computer & Information Science Department, The University of Mississippi, University, MS, USA. yding@olemiss.edu|Computer & Information Science Department, The University of Mississippi, University, MS, USA. yding@olemiss.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-8-S7-S8', '18047731', 'Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor center representative for high dimensional data. We need a new algorithm that is robust and works well in high dimensional data sets e.g. gene expression data.'),
(91851, 2007, 'bmc', 'The alpha-hemolysin nanopore transduction detector - single-molecule binding studies and immunological screening of antibodies and aptamers', 'Winters-Hilt, Stephen', 'Research Institute for Children, Childrens Hospital, 200 Henry Clay Ave, New Orleans, LA 70118, USA. winters@cs.uno.edu', 'United States', 15, 'Antibodies|Aptamers, Nucleotide|Bacterial Toxins|Biosensing Techniques|Equipment Design|Equipment Failure Analysis|Hemolysin Proteins|Immunoassay|Nanotechnology|Porosity|Reproducibility of Results|Sensitivity and Specificity|Transducers', 'Journal Article', '10.1186/1471-2105-8-S7-S9', '18047732', 'Nanopore detection is based on observations of the ionic current threading a single, highly stable, nanometer-scale channel. The dimensions are such that small biomolecules and biopolymers (like DNA and peptides) can translocate or be captured in the channel. The identities of translocating or captured molecules can often be discerned, one from another, based on their channel blockade signatures. There is a self-limiting aspect to a translocation-based detection mechanism: as the channel fits tighter around the translocating molecule the dynamic range of the ionic current signal is reduced. In this study, a lengthy, highly structure, high dynamic-range, molecular capture is sought as a key component of a transduction-based nanopore detection platform.'),
(91852, 2007, 'bmc', 'Abstracts from the 3rd International Society for Computational Biology (ISCB) Student Council Symposium at the 15th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), Vienna, Austria, 21 July 2007', '-', '-', '-', 15, 'Computational Biology', 'Congress', '10.1186/1471-2105-8-S7-S9', '18053117', '-'),
(91853, 2007, 'bmc', 'Generating confidence intervals on biological networks', 'Thorne, Thomas|Stumpf, Michael P H', 'Division of Molecular Biosciences, Imperial College London, Wolfson Building, London SW7 2AZ, UK. thomas.thorne@imperial.ac.uk|Division of Molecular Biosciences, Imperial College London, Wolfson Building, London SW7 2AZ, UK. thomas.thorne@imperial.ac.uk', 'United Kingdom|United Kingdom', 15, 'Algorithms|Amino Acid Motifs|Cluster Analysis|Computer Simulation|Confidence Intervals|Databases, Protein|Evolution, Molecular|Genes, Fungal|Models, Genetic|Models, Statistical|Neural Networks (Computer)|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/1471-2105-8-467', '18053130', 'In the analysis of networks we frequently require the statistical significance of some network statistic, such as measures of similarity for the properties of interacting nodes. The structure of the network may introduce dependencies among the nodes and it will in general be necessary to account for these dependencies in the statistical analysis. To this end we require some form of Null model of the network: generally rewired replicates of the network are generated which preserve only the degree (number of interactions) of each node. We show that this can fail to capture important features of network structure, and may result in unrealistic significance levels, when potentially confounding additional information is available.'),
(91854, 2007, 'bmc', 'Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational proteomics', 'Pfeifer, Nico|Leinenbach, Andreas|Huber, Christian G|Kohlbacher, Oliver', 'Division for Simulation of Biological Systems, Center for Bioinformatics, Eberhard-Karls University, 72076 Tübingen, Germany. npfeifer@informatik.uni-tuebingen.de|Division for Simulation of Biological Systems, Center for Bioinformatics, Eberhard-Karls University, 72076 Tübingen, Germany. npfeifer@informatik.uni-tuebingen.de|Division for Simulation of Biological Systems, Center for Bioinformatics, Eberhard-Karls University, 72076 Tübingen, Germany. npfeifer@informatik.uni-tuebingen.de|Division for Simulation of Biological Systems, Center for Bioinformatics, Eberhard-Karls University, 72076 Tübingen, Germany. npfeifer@informatik.uni-tuebingen.de', 'Germany|Germany|Germany|Germany', 55, 'Animals|Cattle|Chickens|Chromatography, Liquid|Computational Biology|Horses|Humans|Learning|Peptides|Proteomics|Sequence Analysis, Protein|Tandem Mass Spectrometry', 'Comparative Study', '10.1186/1471-2105-8-468', '18053132', 'High-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination with database searching algorithms. A major problem with existing methods lies within the significant number of false positive and false negative annotations. So far, standard algorithms for protein identification do not use the information gained from separation processes usually involved in peptide analysis, such as retention time information, which are readily available from chromatographic separation of the sample. Identification can thus be improved by comparing measured retention times to predicted retention times. Current prediction models are derived from a set of measured test analytes but they usually require large amounts of training data.'),
(91855, 2007, 'bmc', 'A structural analysis of in vitro catalytic activities of hammerhead ribozymes', 'Shao, Yu|Wu, Susan|Chan, Chi Yu|Klapper, Jessie R|Schneider, Erasmus|Ding, Ye', 'Wadsworth Center, New York State Department of Health, 150 New Scotland Avenue, Albany, NY 12208, USA. yushao04@yahoo.com|Wadsworth Center, New York State Department of Health, 150 New Scotland Avenue, Albany, NY 12208, USA. yushao04@yahoo.com|Wadsworth Center, New York State Department of Health, 150 New Scotland Avenue, Albany, NY 12208, USA. yushao04@yahoo.com|Wadsworth Center, New York State Department of Health, 150 New Scotland Avenue, Albany, NY 12208, USA. yushao04@yahoo.com|Wadsworth Center, New York State Department of Health, 150 New Scotland Avenue, Albany, NY 12208, USA. yushao04@yahoo.com|Wadsworth Center, New York State Department of Health, 150 New Scotland Avenue, Albany, NY 12208, USA. yushao04@yahoo.com', 'United States|United States|United States|United States|United States|United States', 11, 'ATP Binding Cassette Transporter, Subfamily G, Member 2|ATP-Binding Cassette Transporters|Base Pairing|Catalysis|DNA Primers|Genetic Engineering|Neoplasm Proteins|RNA Processing, Post-Transcriptional|RNA, Catalytic|RNA, Messenger|Reverse Transcriptase Polymerase Chain Reaction|Thermodynamics', 'Comparative Study', '10.1186/1471-2105-8-469', '18053134', 'Ribozymes are small catalytic RNAs that possess the dual functions of sequence-specific RNA recognition and site-specific cleavage. Trans-cleaving ribozymes can inhibit translation of genes at the messenger RNA (mRNA) level in both eukaryotic and prokaryotic systems and are thus useful tools for studies of gene function. However, identification of target sites for efficient cleavage poses a challenge. Here, we have considered a number of structural and thermodynamic parameters that can affect the efficiency of target cleavage, in an attempt to identify rules for the selection of functional ribozymes.'),
(91856, 2007, 'bmc', 'Domain motions of Argonaute, the catalytic engine of RNA interference', 'Ming, Dengming|Wall, Michael E|Sanbonmatsu, Kevin Y', 'Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, USA. dming@lanl.gov|Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, USA. dming@lanl.gov|Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, USA. dming@lanl.gov', 'United States|United States|United States', 16, 'Archaeal Proteins|Archaeoglobus fulgidus|Binding Sites|Catalysis|Crystallography, X-Ray|Models, Molecular|Motion|Protein Conformation|Pyrococcus furiosus|RNA|RNA Interference|RNA-Induced Silencing Complex|Thermodynamics|Torsion, Mechanical|Vibration', 'Journal Article', '10.1186/1471-2105-8-470', '18053142', 'The Argonaute protein is the core component of the RNA-induced silencing complex, playing the central role of cleaving the mRNA target. Visual inspection of static crystal structures already has enabled researchers to suggest conformational changes of Argonaute that might occur during RNA interference. We have taken the next step by performing an all-atom normal mode analysis of the Pyrococcus furiosus and Aquifex aeolicus Argonaute crystal structures, allowing us to quantitatively assess the feasibility of these conformational changes. To perform the analysis, we begin with the energy-minimized X-ray structures. Normal modes are then calculated using an all-atom molecular mechanics force field.'),
(91857, 2007, 'bmc', 'Predicting and improving the protein sequence alignment quality by support vector regression', 'Lee, Minho|Jeong, Chan-seok|Kim, Dongsup', 'Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea. MinhoLee@kaist.edu|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea. MinhoLee@kaist.edu|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea. MinhoLee@kaist.edu', '-|-|-', 11, 'Amino Acid Sequence|Animals|Artificial Intelligence|Humans|Models, Molecular|Pattern Recognition, Automated|Predictive Value of Tests|Protein Conformation|Proteins|Quality Control|Reference Values|Regression Analysis|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-8-471', '18053160', 'For successful protein structure prediction by comparative modeling, in addition to identifying a good template protein with known structure, obtaining an accurate sequence alignment between a query protein and a template protein is critical. It has been known that the alignment accuracy can vary significantly depending on our choice of various alignment parameters such as gap opening penalty and gap extension penalty. Because the accuracy of sequence alignment is typically measured by comparing it with its corresponding structure alignment, there is no good way of evaluating alignment accuracy without knowing the structure of a query protein, which is obviously not available at the time of structure prediction. Moreover, there is no universal alignment parameter option that would always yield the optimal alignment.'),
(91858, 2007, 'bmc', 'Direct maximum parsimony phylogeny reconstruction from genotype data', 'Sridhar, Srinath|Lam, Fumei|Blelloch, Guy E|Ravi, R|Schwartz, Russell', 'Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, USA. srinath@cs.cmu.edu|Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, USA. srinath@cs.cmu.edu|Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, USA. srinath@cs.cmu.edu|Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, USA. srinath@cs.cmu.edu|Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, USA. srinath@cs.cmu.edu', 'United States|United States|United States|United States|United States', 12, 'Algorithms|Animals|Base Sequence|Conserved Sequence|DNA, Chloroplast|DNA, Mitochondrial|Data Interpretation, Statistical|Databases, Genetic|Evolution, Molecular|Factor Analysis, Statistical|Genomics|Genotype|Haplotypes|Humans|Likelihood Functions|Models, Genetic|Models, Statistical|Mutation|Phylogeny|Programming, Linear|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-8-472', '18053244', 'Maximum parsimony phylogenetic tree reconstruction from genetic variation data is a fundamental problem in computational genetics with many practical applications in population genetics, whole genome analysis, and the search for genetic predictors of disease. Efficient methods are available for reconstruction of maximum parsimony trees from haplotype data, but such data are difficult to determine directly for autosomal DNA. Data more commonly is available in the form of genotypes, which consist of conflated combinations of pairs of haplotypes from homologous chromosomes. Currently, there are no general algorithms for the direct reconstruction of maximum parsimony phylogenies from genotype data. Hence phylogenetic applications for autosomal data must therefore rely on other methods for first computationally inferring haplotypes from genotypes.'),
(91859, 2007, 'bmc', 'A systematic approach to detecting transcription factors in response to environmental stresses', 'Lin, Li-Hsieh|Lee, Hsiao-Ching|Li, Wen-Hsiung|Chen, Bor-Sen', 'Lab of Systems Biology, Department of Electronical Engineering, National Tsing Hua University, 101, Sec 2, Kuang Fu Hsinchu, 300, Taiwan. LHlin@moti.ee.nthu.edu.tw|Lab of Systems Biology, Department of Electronical Engineering, National Tsing Hua University, 101, Sec 2, Kuang Fu Hsinchu, 300, Taiwan. LHlin@moti.ee.nthu.edu.tw|Lab of Systems Biology, Department of Electronical Engineering, National Tsing Hua University, 101, Sec 2, Kuang Fu Hsinchu, 300, Taiwan. LHlin@moti.ee.nthu.edu.tw|Lab of Systems Biology, Department of Electronical Engineering, National Tsing Hua University, 101, Sec 2, Kuang Fu Hsinchu, 300, Taiwan. LHlin@moti.ee.nthu.edu.tw', '-|-|-|-', 12, 'Environmental Exposure|Gene Expression Regulation|Gene Regulatory Networks|Oxidative Stress|Saccharomyces cerevisiae|Transcription Factors', 'Comparative Study', '10.1186/1471-2105-8-473', '18067669', 'Eukaryotic cells have developed mechanisms to respond to external environmental or physiological changes (stresses). In order to increase the activities of stress-protection functions in response to an environmental change, the internal cell mechanisms need to induce certain specific gene expression patterns and pathways by changing the expression levels of specific transcription factors (TFs). The conventional methods to find these specific TFs and their interactivities are slow and laborious. In this study, a novel efficient method is proposed to detect the TFs and their interactivities that regulate yeast genes that respond to any specific environment change.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91860, 2007, 'bmc', 'High-throughput sequence alignment using Graphics Processing Units', 'Schatz, Michael C|Trapnell, Cole|Delcher, Arthur L|Varshney, Amitabh', 'Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA. mschatz@umiacs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA. mschatz@umiacs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA. mschatz@umiacs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA. mschatz@umiacs.umd.edu', 'United States|United States|United States|United States', 218, 'Animals|Bacillus anthracis|Base Sequence|Caenorhabditis|Computer Graphics|Computers|Contig Mapping|DNA|Database Management Systems|Databases, Genetic|Genomic Library|Listeria monocytogenes|Sequence Alignment|Sequence Analysis, DNA|Streptococcus suis|Time Factors|Work Simplification', 'Journal Article', '10.1186/1471-2105-8-474', '18070356', 'The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and de novo genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies.'),
(91861, 2007, 'bmc', 'Predicting gene ontology functions from proteins regional surface structures', 'Liu, Zhi-Ping|Wu, Ling-Yun|Wang, Yong|Chen, Luonan|Zhang, Xiang-Sun', 'Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China. zhiping.liu@hotmail.com|Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China. zhiping.liu@hotmail.com|Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China. zhiping.liu@hotmail.com|Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China. zhiping.liu@hotmail.com|Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China. zhiping.liu@hotmail.com', 'China|China|China|China|China', 19, 'Binding Sites|Cluster Analysis|Computational Biology|Databases, Genetic|Models, Molecular|Pattern Recognition, Automated|Predictive Value of Tests|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Proteomics|Structural Homology, Protein|Structure-Activity Relationship|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-8-475', '18070366', 'Annotation of protein functions is an important task in the post-genomic era. Most early approaches for this task exploit only the sequence or global structure information. However, protein surfaces are believed to be crucial to protein functions because they are the main interfaces to facilitate biological interactions. Recently, several databases related to structural surfaces, such as pockets and cavities, have been constructed with a comprehensive library of identified surface structures. For example, CASTp provides identification and measurements of surface accessible pockets as well as interior inaccessible cavities.'),
(91862, 2007, 'bmc', 'Penalized likelihood for sparse contingency tables with an application to full-length cDNA libraries', 'Dahinden, Corinne|Parmigiani, Giovanni|Emerick, Mark C|Bühlmann, Peter', 'Seminar für Statistik, ETH Zürich, CH-8092 Zürich, Switzerland. dahinden@stat.math.ethz.ch|Seminar für Statistik, ETH Zürich, CH-8092 Zürich, Switzerland. dahinden@stat.math.ethz.ch|Seminar für Statistik, ETH Zürich, CH-8092 Zürich, Switzerland. dahinden@stat.math.ethz.ch|Seminar für Statistik, ETH Zürich, CH-8092 Zürich, Switzerland. dahinden@stat.math.ethz.ch', 'Switzerland|Switzerland|Switzerland|Switzerland', 21, 'Bayes Theorem|Computer Graphics|DNA, Recombinant|Exons|Gene Library|Likelihood Functions|Linear Models|Logistic Models|Mathematical Computing|Pattern Recognition, Automated|Regression Analysis|Sensitivity and Specificity|Systems Biology', 'Journal Article', '10.1186/1471-2105-8-476', '18072965', 'The joint analysis of several categorical variables is a common task in many areas of biology, and is becoming central to systems biology investigations whose goal is to identify potentially complex interaction among variables belonging to a network. Interactions of arbitrary complexity are traditionally modeled in statistics by log-linear models. It is challenging to extend these to the high dimensional and potentially sparse data arising in computational biology. An important example, which provides the motivation for this article, is the analysis of so-called full-length cDNA libraries of alternatively spliced genes, where we investigate relationships among the presence of various exons in transcript species.'),
(91863, 2007, 'bmc', 'On the analysis of glycomics mass spectrometry data via the regularized area under the ROC curve', 'Ye, Jingjing|Liu, Hao|Kirmiz, Crystal|Lebrilla, Carlito B|Rocke, David M', 'Department of Statistics, University of California, Davis, Davis, CA, 95616, USA. jingjingye@gmail.com|Department of Statistics, University of California, Davis, Davis, CA, 95616, USA. jingjingye@gmail.com|Department of Statistics, University of California, Davis, Davis, CA, 95616, USA. jingjingye@gmail.com|Department of Statistics, University of California, Davis, Davis, CA, 95616, USA. jingjingye@gmail.com|Department of Statistics, University of California, Davis, Davis, CA, 95616, USA. jingjingye@gmail.com', 'United States|United States|United States|United States|United States', 11, 'Algorithms|Biomarkers, Tumor|Computer Simulation|Confidence Intervals|Diagnosis, Computer-Assisted|Female|Glycomics|Humans|Mass Spectrometry|Models, Statistical|Neoplasm Proteins|Ovarian Neoplasms|Pattern Recognition, Automated|Peptide Mapping|ROC Curve|Retrospective Studies', 'Journal Article', '10.1186/1471-2105-8-477', '18076765', 'Novel molecular and statistical methods are in rising demand for disease diagnosis and prognosis with the help of recent advanced biotechnology. High-resolution mass spectrometry (MS) is one of those biotechnologies that are highly promising to improve health outcome. Previous literatures have identified some proteomics biomarkers that can distinguish healthy patients from cancer patients using MS data. In this paper, an MS study is demonstrated which uses glycomics to identify ovarian cancer. Glycomics is the study of glycans and glycoproteins. The glycans on the proteins may deviate between a cancer cell and a normal cell and may be visible in the blood. High-resolution MS has been applied to measure relative abundances of potential glycan biomarkers in human serum. Multiple potential glycan biomarkers are measured in MS spectra. With the objection of maximizing the empirical area under the ROC curve (AUC), an analysis method was considered which combines potential glycan biomarkers for the diagnosis of cancer.'),
(91864, 2007, 'bmc', 'Ab initio identification of human microRNAs based on structure motifs', 'Brameier, Markus|Wiuf, Carsten', 'Bioinformatics Research Center (BiRC), University of Aarhus, 8000 Aarhus C, Denmark. brameier@birc.au.dk|Bioinformatics Research Center (BiRC), University of Aarhus, 8000 Aarhus C, Denmark. brameier@birc.au.dk', 'Denmark|Denmark', 46, 'Algorithms|Base Pairing|Computational Biology|Expressed Sequence Tags|Genomics|Humans|MicroRNAs|Species Specificity', 'Journal Article', '10.1186/1471-2105-8-478', '18088431', 'MicroRNAs (miRNAs) are short, non-coding RNA molecules that are directly involved in post-transcriptional regulation of gene expression. The mature miRNA sequence binds to more or less specific target sites on the mRNA. Both their small size and sequence specificity make the detection of completely new miRNAs a challenging task. This cannot be based on sequence information alone, but requires structure information about the miRNA precursor. Unlike comparative genomics approaches, ab initio approaches are able to discover species-specific miRNAs without known sequence homology.'),
(91865, 2007, 'bmc', 'The Personal Sequence Database: a suite of tools to create and maintain web-accessible sequence databases', 'Givan, Scott A|Sullivan, Christopher M|Carrington, James C', 'Center for Genome Research and Biocomputing, Oregon State University, Corvallis, Oregon, USA. givans@cgrb.oregonstate.edu|Center for Genome Research and Biocomputing, Oregon State University, Corvallis, Oregon, USA. givans@cgrb.oregonstate.edu|Center for Genome Research and Biocomputing, Oregon State University, Corvallis, Oregon, USA. givans@cgrb.oregonstate.edu', 'United States|United States|United States', 2, 'Algorithms|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-8-479', '18088438', 'Large molecular sequence databases are fundamental resources for modern bioscientists. Whether for project-specific purposes or sharing data with colleagues, it is often advantageous to maintain smaller sequence databases. However, this is usually not an easy task for the average bench scientist.'),
(91866, 2007, 'bmc', 'TABASCO: A single molecule, base-pair resolved gene expression simulator', 'Kosuri, Sriram|Kelly, Jason R|Endy, Drew', 'Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave,, Cambridge, MA 02139 USA. skosuri@mit.edu|Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave,, Cambridge, MA 02139 USA. skosuri@mit.edu|Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave,, Cambridge, MA 02139 USA. skosuri@mit.edu', 'United States|United States|United States', 18, 'Bacteriophage T7|Base Pairing|Binding Sites|Computer Simulation|DNA-Directed RNA Polymerases|Escherichia coli|Gene Expression|Gene Expression Profiling|Gene Expression Regulation|Genome, Fungal|Knowledge Bases|Logistic Models|Regulatory Elements, Transcriptional|Sensitivity and Specificity|Sequence Analysis, DNA|Software Design|Transcription Factors|Viral Proteins', 'Journal Article', '10.1186/1471-2105-8-480', '18093293', 'Experimental studies of gene expression have identified some of the individual molecular components and elementary reactions that comprise and control cellular behavior. Given our current understanding of gene expression, and the goals of biotechnology research, both scientists and engineers would benefit from detailed simulators that can explicitly compute genome-wide expression levels as a function of individual molecular events, including the activities and interactions of molecules on DNA at single base pair resolution. However, for practical reasons including computational tractability, available simulators have not been able to represent genome-scale models of gene expression at this level of detail.'),
(91867, 2007, 'bmc', 'Effective transcription factor binding site prediction using a combination of optimization, a genetic algorithm and discriminant analysis to capture distant interactions', 'Levitsky, Victor G|Ignatieva, Elena V|Ananko, Elena A|Turnaev, Igor I|Merkulova, Tatyana I|Kolchanov, Nikolay A|Hodgman, T C', 'Institute of Cytology and Genetics SB RAS, Novosibirsk, 630090, Russia. levitsky@bionet.nsc.ru|Institute of Cytology and Genetics SB RAS, Novosibirsk, 630090, Russia. levitsky@bionet.nsc.ru|Institute of Cytology and Genetics SB RAS, Novosibirsk, 630090, Russia. levitsky@bionet.nsc.ru|Institute of Cytology and Genetics SB RAS, Novosibirsk, 630090, Russia. levitsky@bionet.nsc.ru|Institute of Cytology and Genetics SB RAS, Novosibirsk, 630090, Russia. levitsky@bionet.nsc.ru|Institute of Cytology and Genetics SB RAS, Novosibirsk, 630090, Russia. levitsky@bionet.nsc.ru|Institute of Cytology and Genetics SB RAS, Novosibirsk, 630090, Russia. levitsky@bionet.nsc.ru', '-|-|-|-|-|-|-', 0, 'Algorithms|Base Sequence|Binding Sites|Computer Simulation|DNA|Discriminant Analysis|Models, Genetic|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1186/1471-2105-8-481', '18093302', 'Reliable transcription factor binding site (TFBS) prediction methods are essential for computer annotation of large amount of genome sequence data. However, current methods to predict TFBSs are hampered by the high false-positive rates that occur when only sequence conservation at the core binding-sites is considered.'),
(91868, 2007, 'bmc', 'Identifying protein complexes directly from high-throughput TAP data with Markov random fields', 'Rungsarityotin, Wasinee|Krause, Roland|Schödl, Arno|Schliep, Alexander', 'Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestr, 73, D-14195 Berlin, Germany. rungsari@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestr, 73, D-14195 Berlin, Germany. rungsari@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestr, 73, D-14195 Berlin, Germany. rungsari@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestr, 73, D-14195 Berlin, Germany. rungsari@molgen.mpg.de', 'Germany|Germany|Germany|Germany', 13, 'Artifacts|Artificial Intelligence|Cluster Analysis|Data Interpretation, Statistical|Databases, Protein|Likelihood Functions|Models, Biological|Observer Variation|Protein Binding|Protein Interaction Mapping|Recombinant Fusion Proteins|Reproducibility of Results|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Stochastic Processes', 'Journal Article', '10.1186/1471-2105-8-482', '18093306', 'Predicting protein complexes from experimental data remains a challenge due to limited resolution and stochastic errors of high-throughput methods. Current algorithms to reconstruct the complexes typically rely on a two-step process. First, they construct an interaction graph from the data, predominantly using heuristics, and subsequently cluster its vertices to identify protein complexes.'),
(91869, 2007, 'bmc', 'PARPs database: a LIMS systems for protein-protein interaction data mining or laboratory information management system', 'Droit, Arnaud|Hunter, Joanna M|Rouleau, Michèle|Ethier, Chantal|Picard-Cloutier, Aude|Bourgais, David|Poirier, Guy G', 'Health and Environment Unit, Laval University Medical research Center, CHUQ, Québec, Canada. arnaud.droit@gmail.com|Health and Environment Unit, Laval University Medical research Center, CHUQ, Québec, Canada. arnaud.droit@gmail.com|Health and Environment Unit, Laval University Medical research Center, CHUQ, Québec, Canada. arnaud.droit@gmail.com|Health and Environment Unit, Laval University Medical research Center, CHUQ, Québec, Canada. arnaud.droit@gmail.com|Health and Environment Unit, Laval University Medical research Center, CHUQ, Québec, Canada. arnaud.droit@gmail.com|Health and Environment Unit, Laval University Medical research Center, CHUQ, Québec, Canada. arnaud.droit@gmail.com|Health and Environment Unit, Laval University Medical research Center, CHUQ, Québec, Canada. arnaud.droit@gmail.com', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 15, 'Binding Sites|Chromatography, High Pressure Liquid|Computational Biology|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Mass Spectrometry|Poly (ADP-Ribose) Polymerase-1|Poly(ADP-ribose) Polymerases|Protein Binding|Protein Interaction Mapping', 'Journal Article', '10.1186/1471-2105-8-483', '18093328', 'In the post-genome era, mass spectrometry (MS) has become an important method for the analysis of proteins and the rapid advancement of this technique, in combination with other proteomics methods, results in an increasing amount of proteome data. This data must be archived and analysed using specialized bioinformatics tools.'),
(91870, 2007, 'bmc', 'Effective selection of informative SNPs and classification on the HapMap genotype data', 'Zhou, Nina|Wang, Lipo', 'Electrical and Electronic Engineering, Nanyang Technology University, Block S1, 50 Nanyang Avenue, 639798 Singapore. zhounina@ntu.edu.sg|Electrical and Electronic Engineering, Nanyang Technology University, Block S1, 50 Nanyang Avenue, 639798 Singapore. zhounina@ntu.edu.sg', 'Singapore|Singapore', 0, 'Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Databases, Genetic|Genetic Variation|Genotype|Haplotypes|Molecular Sequence Data|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1186/1471-2105-8-484', '18093342', 'Since the single nucleotide polymorphisms (SNPs) are genetic variations which determine the difference between any two unrelated individuals, the SNPs can be used to identify the correct source population of an individual. For efficient population identification with the HapMap genotype data, as few informative SNPs as possible are required from the original 4 million SNPs. Recently, Park et al. (2006) adopted the nearest shrunken centroid method to classify the three populations, i.e., Utah residents with ancestry from Northern and Western Europe (CEU), Yoruba in Ibadan, Nigeria in West Africa (YRI), and Han Chinese in Beijing together with Japanese in Tokyo (CHB+JPT), from which 100,736 SNPs were obtained and the top 82 SNPs could completely classify the three populations.'),
(91871, 2007, 'bmc', 'Characterization and simulation of cDNA microarray spots using a novel mathematical model', 'Kim, Hye Young|Lee, Seo Eun|Kim, Min Jung|Han, Jin Il|Kim, Bo Kyung|Lee, Yong Sung|Lee, Young Seek|Kim, Jin Hyuk', 'Department of Physiology, College of Medicine, Hanyang University, Seoul, 133-791, Korea. hykim121@hanyang.ac.kr|Department of Physiology, College of Medicine, Hanyang University, Seoul, 133-791, Korea. hykim121@hanyang.ac.kr|Department of Physiology, College of Medicine, Hanyang University, Seoul, 133-791, Korea. hykim121@hanyang.ac.kr|Department of Physiology, College of Medicine, Hanyang University, Seoul, 133-791, Korea. hykim121@hanyang.ac.kr|Department of Physiology, College of Medicine, Hanyang University, Seoul, 133-791, Korea. hykim121@hanyang.ac.kr|Department of Physiology, College of Medicine, Hanyang University, Seoul, 133-791, Korea. hykim121@hanyang.ac.kr|Department of Physiology, College of Medicine, Hanyang University, Seoul, 133-791, Korea. hykim121@hanyang.ac.kr|Department of Physiology, College of Medicine, Hanyang University, Seoul, 133-791, Korea. hykim121@hanyang.ac.kr', '-|-|-|-|-|-|-|-', 12, 'Computer Simulation|Image Interpretation, Computer-Assisted|In Situ Hybridization, Fluorescence|Microfluidics|Microscopy, Fluorescence|Models, Chemical|Models, Genetic|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-8-485', '18096047', 'The quality of cDNA microarray data is crucial for expanding its application to other research areas, such as the study of gene regulatory networks. Despite the fact that a number of algorithms have been suggested to increase the accuracy of microarray gene expression data, it is necessary to obtain reliable microarray images by improving wet-lab experiments. As the first step of a cDNA microarray experiment, spotting cDNA probes is critical to determining the quality of spot images.'),
(91872, 2007, 'bmc', 'H-Profile plots for the discovery and exploration of patterns in gene expression data with an application to time course data', 'Pittelkow, Yvonne E|Wilson, Susan R', 'Mathematical Sciences Institute, Australian National University, Building 27, Canberra, ACT 0200, Australia. yvonne.pittelkow@anu.edu.au|Mathematical Sciences Institute, Australian National University, Building 27, Canberra, ACT 0200, Australia. yvonne.pittelkow@anu.edu.au', 'Australia|Australia', 0, 'Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation|Protein Array Analysis|Time Factors|Yeasts', 'Comparative Study', '10.1186/1471-2105-8-486', '18096081', 'An ever increasing number of techniques are being used to find genes with similar profiles from microarray studies. Visualization of gene expression profiles can aid this process, potentially contributing to the identification of co-regulated genes and gene function as well as network development.'),
(91873, 2007, 'bmc', 'Userscripts for the life sciences', 'Willighagen, Egon L|OBoyle, Noel M|Gopalakrishnan, Harini|Jiao, Dazhi|Guha, Rajarshi|Steinbeck, Christoph|Wild, David J', 'Cologne University Bioinformatics Center, Cologne University, Cologne, Germany. egonw@users.sf.net|Cologne University Bioinformatics Center, Cologne University, Cologne, Germany. egonw@users.sf.net|Cologne University Bioinformatics Center, Cologne University, Cologne, Germany. egonw@users.sf.net|Cologne University Bioinformatics Center, Cologne University, Cologne, Germany. egonw@users.sf.net|Cologne University Bioinformatics Center, Cologne University, Cologne, Germany. egonw@users.sf.net|Cologne University Bioinformatics Center, Cologne University, Cologne, Germany. egonw@users.sf.net|Cologne University Bioinformatics Center, Cologne University, Cologne, Germany. egonw@users.sf.net', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 15, 'Artificial Intelligence|Biological Science Disciplines|Computer-Assisted Instruction|Database Management Systems|Education, Distance|Humans|Hypermedia|Information Services|Information Storage and Retrieval|Internet|Medical Informatics|Programming Languages|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-487', '18154664', 'The web has seen an explosion of chemistry and biology related resources in the last 15 years: thousands of scientific journals, databases, wikis, blogs and resources are available with a wide variety of types of information. There is a huge need to aggregate and organise this information. However, the sheer number of resources makes it unrealistic to link them all in a centralised manner. Instead, search engines to find information in those resources flourish, and formal languages like Resource Description Framework and Web Ontology Language are increasingly used to allow linking of resources. A recent development is the use of userscripts to change the appearance of web pages, by on-the-fly modification of the web content. This opens possibilities to aggregate information and computational results from different web resources into the web page of one of those resources.'),
(91874, 2007, 'bmc', 'Background frequencies for residue variability estimates: BLOSUM revisited', 'Mihalek, I|Res, I|Lichtarge, O', 'Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. ivanam@bii.a-star.edu.sg|Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. ivanam@bii.a-star.edu.sg|Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA. ivanam@bii.a-star.edu.sg', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Molecular Sequence Data|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-8-488', '18162129', 'Shannon entropy applied to columns of multiple sequence alignments as a score of residue conservation has proven one of the most fruitful ideas in bioinformatics. This straightforward and intuitively appealing measure clearly shows the regions of a protein under increased evolutionary pressure, highlighting their functional importance. The inability of the column entropy to differentiate between residue types, however, limits its resolution power.'),
(91875, 2008, 'bmc', 'Evaluation of time profile reconstruction from complex two-color microarray designs', 'Fierro, Ana C|Thuret, Raphael|Engelen, Kristof|Bernot, Gilles|Marchal, Kathleen|Pollet, Nicolas', 'CNRS UMR 8080, Laboratoire Développement et Evolution, Bat 445, F-91405 Orsay, France. carolina.fierro@gmail.com|CNRS UMR 8080, Laboratoire Développement et Evolution, Bat 445, F-91405 Orsay, France. carolina.fierro@gmail.com|CNRS UMR 8080, Laboratoire Développement et Evolution, Bat 445, F-91405 Orsay, France. carolina.fierro@gmail.com|CNRS UMR 8080, Laboratoire Développement et Evolution, Bat 445, F-91405 Orsay, France. carolina.fierro@gmail.com|CNRS UMR 8080, Laboratoire Développement et Evolution, Bat 445, F-91405 Orsay, France. carolina.fierro@gmail.com|CNRS UMR 8080, Laboratoire Développement et Evolution, Bat 445, F-91405 Orsay, France. carolina.fierro@gmail.com', 'France|France|France|France|France|France', 0, 'Equipment Design|Equipment Failure Analysis|Image Interpretation, Computer-Assisted|In Situ Hybridization|Microscopy, Fluorescence, Multiphoton|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Time Factors', 'Comparative Study', '10.1186/1471-2105-9-1', '18173834', 'As an alternative to the frequently used reference design for two-channel microarrays, other designs have been proposed. These designs have been shown to be more profitable from a theoretical point of view (more replicates of the conditions of interest for the same number of arrays). However, the interpretation of the measurements is less straightforward and a reconstruction method is needed to convert the observed ratios into the genuine profile of interest (e.g. a time profile). The potential advantages of using these alternative designs thus largely depend on the success of the profile reconstruction. Therefore, we compared to what extent different linear models agree with each other in reconstructing expression ratios and corresponding time profiles from a complex design.'),
(91876, 2008, 'bmc', 'Supervised inference of gene-regulatory networks', 'To, Cuong C|Vohradsky, Jiri', 'Laboratory of Bioinformatics, Institute of Microbiology ASCR, Prague, Czech Republic. cuongto@biomed.cas.cz|Laboratory of Bioinformatics, Institute of Microbiology ASCR, Prague, Czech Republic. cuongto@biomed.cas.cz', '-|-', 4, 'Algorithms|Artificial Intelligence|Computer Simulation|Gene Expression Regulation|Models, Biological|Pattern Recognition, Automated|Protein Interaction Mapping|Proteome|Signal Transduction', 'Journal Article', '10.1186/1471-2105-9-2', '18177495', 'Inference of protein interaction networks from various sources of data has become an important topic of both systems and computational biology. Here we present a supervised approach to identification of gene expression regulatory networks.'),
(91877, 2008, 'bmc', 'Extending pathways based on gene lists using InterPro domain signatures', 'Hahne, Florian|Mehrle, Alexander|Arlt, Dorit|Poustka, Annemarie|Wiemann, Stefan|Beissbarth, Tim', 'German Cancer Research Center, Molecular Genome Analysis, Im Neuenheimer Feld 580,69120 Heidelberg, Germany. f.hahne@dkfz.de|German Cancer Research Center, Molecular Genome Analysis, Im Neuenheimer Feld 580,69120 Heidelberg, Germany. f.hahne@dkfz.de|German Cancer Research Center, Molecular Genome Analysis, Im Neuenheimer Feld 580,69120 Heidelberg, Germany. f.hahne@dkfz.de|German Cancer Research Center, Molecular Genome Analysis, Im Neuenheimer Feld 580,69120 Heidelberg, Germany. f.hahne@dkfz.de|German Cancer Research Center, Molecular Genome Analysis, Im Neuenheimer Feld 580,69120 Heidelberg, Germany. f.hahne@dkfz.de|German Cancer Research Center, Molecular Genome Analysis, Im Neuenheimer Feld 580,69120 Heidelberg, Germany. f.hahne@dkfz.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 11, 'Algorithms|Amino Acid Sequence|Database Management Systems|Databases, Protein|Gene Expression Profiling|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Protein Structure, Tertiary|Proteins|Signal Transduction|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-9-3', '18177498', 'High-throughput technologies like functional screens and gene expression analysis produce extended lists of candidate genes. Gene-Set Enrichment Analysis is a commonly used and well established technique to test for the statistically significant over-representation of particular pathways. A shortcoming of this method is however, that most genes that are investigated in the experiments have very sparse functional or pathway annotation and therefore cannot be the target of such an analysis. The approach presented here aims to assign lists of genes with limited annotation to previously described functional gene collections or pathways. This works by comparing InterPro domain signatures of the candidate gene lists with domain signatures of gene sets derived from known classifications, e.g. KEGG pathways.'),
(91878, 2008, 'bmc', 'An open-source representation for 2-DE-centric proteomics and support infrastructure for data storage and analysis', 'Stanislaus, Romesh|Arthur, John M|Rajagopalan, Balaji|Moerschell, Rick|McGlothlen, Brian|Almeida, Jonas S', 'The University of Texas M, D, Anderson Cancer Center, 1515 Holcombe Blvd,, Houston, TX 77030, USA. rstanisl@mdanderson.org|The University of Texas M, D, Anderson Cancer Center, 1515 Holcombe Blvd,, Houston, TX 77030, USA. rstanisl@mdanderson.org|The University of Texas M, D, Anderson Cancer Center, 1515 Holcombe Blvd,, Houston, TX 77030, USA. rstanisl@mdanderson.org|The University of Texas M, D, Anderson Cancer Center, 1515 Holcombe Blvd,, Houston, TX 77030, USA. rstanisl@mdanderson.org|The University of Texas M, D, Anderson Cancer Center, 1515 Holcombe Blvd,, Houston, TX 77030, USA. rstanisl@mdanderson.org|The University of Texas M, D, Anderson Cancer Center, 1515 Holcombe Blvd,, Houston, TX 77030, USA. rstanisl@mdanderson.org', 'United States|United States|United States|United States|United States|United States', 0, 'Animals|Database Management Systems|Electrophoresis, Gel, Two-Dimensional|Humans|Hypermedia|Information Dissemination|Information Storage and Retrieval|Internet|Knowledge Bases|Proteomics|Reference Values|Research Design|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-4', '18179696', 'In spite of two-dimensional gel electrophoresis (2-DE) being an effective and widely used method to screen the proteome, its data standardization has still not matured to the level of microarray genomics data or mass spectrometry approaches. The trend toward identifying encompassing data standards has been expanding from genomics to transcriptomics, and more recently to proteomics. The relative success of genomic and transcriptomic data standardization has enabled the development of central repositories such as GenBank and Gene Expression Omnibus. An equivalent 2-DE-centric data structure would similarly have to include a balance among raw data, basic feature detection results, sufficiency in the description of the experimental context and methods, and an overall structure that facilitates a diversity of usages, from central reposition to local data representation in LIMs systems.'),
(91879, 2008, 'bmc', 'EST2uni: an open, parallel tool for automated EST analysis and database creation, with a data mining web interface and microarray expression data integration', 'Forment, Javier|Gilabert, Francisco|Robles, Antonio|Conejero, Vicente|Nuez, Fernando|Blanca, Jose M', 'Centro para la Conservación y Mejora de la Agrodiversidad Valenciana (COMAV), Universidad Politécnica de Valencia, Avenida de los Naranjos s/n, 46022 Valencia, Spain. jforment@ibmcp.upv.es|Centro para la Conservación y Mejora de la Agrodiversidad Valenciana (COMAV), Universidad Politécnica de Valencia, Avenida de los Naranjos s/n, 46022 Valencia, Spain. jforment@ibmcp.upv.es|Centro para la Conservación y Mejora de la Agrodiversidad Valenciana (COMAV), Universidad Politécnica de Valencia, Avenida de los Naranjos s/n, 46022 Valencia, Spain. jforment@ibmcp.upv.es|Centro para la Conservación y Mejora de la Agrodiversidad Valenciana (COMAV), Universidad Politécnica de Valencia, Avenida de los Naranjos s/n, 46022 Valencia, Spain. jforment@ibmcp.upv.es|Centro para la Conservación y Mejora de la Agrodiversidad Valenciana (COMAV), Universidad Politécnica de Valencia, Avenida de los Naranjos s/n, 46022 Valencia, Spain. jforment@ibmcp.upv.es|Centro para la Conservación y Mejora de la Agrodiversidad Valenciana (COMAV), Universidad Politécnica de Valencia, Avenida de los Naranjos s/n, 46022 Valencia, Spain. jforment@ibmcp.upv.es', 'Spain|Spain|Spain|Spain|Spain|Spain', 38, 'Base Sequence|Databases, Genetic|Expressed Sequence Tags|Information Storage and Retrieval|Internet|Molecular Sequence Data|Protein Array Analysis|Software', 'Comparative Study', '10.1186/1471-2105-9-5', '18179701', 'Expressed sequence tag (EST) collections are composed of a high number of single-pass, redundant, partial sequences, which need to be processed, clustered, and annotated to remove low-quality and vector regions, eliminate redundancy and sequencing errors, and provide biologically relevant information. In order to provide a suitable way of performing the different steps in the analysis of the ESTs, flexible computation pipelines adapted to the local needs of specific EST projects have to be developed. Furthermore, EST collections must be stored in highly structured relational databases available to researchers through user-friendly interfaces which allow efficient and complex data mining, thus offering maximum capabilities for their full exploitation.'),
(91880, 2008, 'bmc', 'Can molecular dynamics simulations help in discriminating correct from erroneous protein 3D models?', 'Taly, Jean-François|Marin, Antoine|Gibrat, Jean-François', 'INRA, Unité Mathématique Informatique et Génome UR1077, F-78350 Jouy-en-Josas, France. jean-francois.taly@jouy.inra.fr|INRA, Unité Mathématique Informatique et Génome UR1077, F-78350 Jouy-en-Josas, France. jean-francois.taly@jouy.inra.fr|INRA, Unité Mathématique Informatique et Génome UR1077, F-78350 Jouy-en-Josas, France. jean-francois.taly@jouy.inra.fr', 'France|France|France', 0, 'Amino Acid Sequence|Binding Sites|Computer Simulation|Kinetics|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Conformation|Protein Folding|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1186/1471-2105-9-6', '18179702', 'Recent approaches for predicting the three-dimensional (3D) structure of proteins such as de novo or fold recognition methods mostly rely on simplified energy potential functions and a reduced representation of the polypeptide chain. These simplifications facilitate the exploration of the protein conformational space but do not permit to capture entirely the subtle relationship that exists between the amino acid sequence and its native structure. It has been proposed that physics-based energy functions together with techniques for sampling the conformational space, e.g., Monte Carlo or molecular dynamics (MD) simulations, are better suited to the task of modelling proteins at higher resolutions than those of models obtained with the former type of methods. In this study we monitor different protein structural properties along MD trajectories to discriminate correct from erroneous models. These models are based on the sequence-structure alignments provided by our fold recognition method, FROST. We define correct models as being built from alignments of sequences with structures similar to their native structures and erroneous models from alignments of sequences with structures unrelated to their native structures.'),
(91881, 2008, 'bmc', 'A PATO-compliant zebrafish screening database (MODB): management of morpholino knockdown screen information', 'Knowlton, Michelle N|Li, Tongbin|Ren, Yongliang|Bill, Brent R|Ellis, Lynda Bm|Ekker, Stephen C', 'Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA. mnk@informatics.jax.org|Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA. mnk@informatics.jax.org|Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA. mnk@informatics.jax.org|Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA. mnk@informatics.jax.org|Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA. mnk@informatics.jax.org|Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA. mnk@informatics.jax.org', 'United States|United States|United States|United States|United States|United States', 16, 'Animals|Antisense Elements (Genetics)|Chromosome Mapping|Computational Biology|Database Management Systems|Databases, Genetic|Embryo, Nonmammalian|Gene Expression|Gene Expression Profiling|Genomics|Internet|Oligonucleotides|Phenotype|Species Specificity|User-Computer Interface|Vocabulary, Controlled|Zebrafish', 'Journal Article', '10.1186/1471-2105-9-7', '18179718', 'The zebrafish is a powerful model vertebrate amenable to high throughput in vivo genetic analyses. Examples include reverse genetic screens using morpholino knockdown, expression-based screening using enhancer trapping and forward genetic screening using transposon insertional mutagenesis. We have created a database to facilitate web-based distribution of data from such genetic studies.'),
(91882, 2008, 'bmc', 'A novel method for high accuracy sumoylation site prediction from protein sequences', 'Xu, Jialin|He, Yun|Qiang, Boqin|Yuan, Jiangang|Peng, Xiaozhong|Pan, Xian-Ming', 'The Key Laboratory of Bioinformatics, Ministry of Education, China, Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, 100084, China. jialinx@gmail.com|The Key Laboratory of Bioinformatics, Ministry of Education, China, Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, 100084, China. jialinx@gmail.com|The Key Laboratory of Bioinformatics, Ministry of Education, China, Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, 100084, China. jialinx@gmail.com|The Key Laboratory of Bioinformatics, Ministry of Education, China, Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, 100084, China. jialinx@gmail.com|The Key Laboratory of Bioinformatics, Ministry of Education, China, Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, 100084, China. jialinx@gmail.com|The Key Laboratory of Bioinformatics, Ministry of Education, China, Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing, 100084, China. jialinx@gmail.com', 'China|China|China|China|China|China', 0, 'Algorithms|Amino Acid Sequence|Binding Sites|Molecular Sequence Data|Protein Binding|Protein Processing, Post-Translational|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein|Small Ubiquitin-Related Modifier Proteins|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-9-8', '18179724', 'Protein sumoylation is an essential dynamic, reversible post translational modification that plays a role in dozens of cellular activities, especially the regulation of gene expression and the maintenance of genomic stability. Currently, the complexities of sumoylation mechanism can not be perfectly solved by experimental approaches. In this regard, computational approaches might represent a promising method to direct experimental identification of sumoylation sites and shed light on the understanding of the reaction mechanism.'),
(91883, 2008, 'bmc', 'SCOWLP classification: structural comparison and analysis of protein binding regions', 'Teyra, Joan|Paszkowski-Rogacz, Maciej|Anders, Gerd|Pisabarro, M Teresa', 'Structural Bioinformatics, BIOTEC TU-Dresden, Tatzberg 47-51, 01307 Dresden, Germany. joan.teyra@biotec.tu-dresden.de|Structural Bioinformatics, BIOTEC TU-Dresden, Tatzberg 47-51, 01307 Dresden, Germany. joan.teyra@biotec.tu-dresden.de|Structural Bioinformatics, BIOTEC TU-Dresden, Tatzberg 47-51, 01307 Dresden, Germany. joan.teyra@biotec.tu-dresden.de|Structural Bioinformatics, BIOTEC TU-Dresden, Tatzberg 47-51, 01307 Dresden, Germany. joan.teyra@biotec.tu-dresden.de', 'Germany|Germany|Germany|Germany', 34, 'Classification|Computational Biology|Databases, Protein|Internet|Protein Interaction Domains and Motifs|Proteomics', 'Journal Article', '10.1186/1471-2105-9-9', '18182098', 'Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design.'),
(91884, 2008, 'bmc', 'Corpus annotation for mining biomedical events from literature', 'Kim, Jin-Dong|Ohta, Tomoko|Tsujii, Junichi', 'Department of Computer Science, School of Information Science and Technology, University of Tokyo, Tokyo, Japan. jdkim@is.s.u-tokyo.ac.jp|Department of Computer Science, School of Information Science and Technology, University of Tokyo, Tokyo, Japan. jdkim@is.s.u-tokyo.ac.jp|Department of Computer Science, School of Information Science and Technology, University of Tokyo, Tokyo, Japan. jdkim@is.s.u-tokyo.ac.jp', 'Japan|Japan|Japan', 0, 'Abstracting and Indexing as Topic|Artificial Intelligence|Database Management Systems|Documentation|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-9-10', '18182099', 'Advanced Text Mining (TM) such as semantic enrichment of papers, event or relation extraction, and intelligent Question Answering have increasingly attracted attention in the bio-medical domain. For such attempts to succeed, text annotation from the biological point of view is indispensable. However, due to the complexity of the task, semantic annotation has never been tried on a large scale, apart from relatively simple term annotation.'),
(91885, 2008, 'bmc', 'SeqAn an efficient, generic C++ library for sequence analysis', 'Döring, Andreas|Weese, David|Rausch, Tobias|Reinert, Knut', 'Algorithmische Bioinformatik, Institut für Informatik, Takustr, 9, 14195 Berlin, Germany. doering@inf.fu-berlin.de|Algorithmische Bioinformatik, Institut für Informatik, Takustr, 9, 14195 Berlin, Germany. doering@inf.fu-berlin.de|Algorithmische Bioinformatik, Institut für Informatik, Takustr, 9, 14195 Berlin, Germany. doering@inf.fu-berlin.de|Algorithmische Bioinformatik, Institut für Informatik, Takustr, 9, 14195 Berlin, Germany. doering@inf.fu-berlin.de', 'Germany|Germany|Germany|Germany', 179, 'Algorithms|Database Management Systems|Databases, Genetic|Programming Languages|Sequence Alignment|Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-11', '18184432', 'The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome 1 would not have been possible without advanced assembly algorithms. However, owing to the high speed of technological progress and the urgent need for bioinformatics tools, there is a widening gap between state-of-the-art algorithmic techniques and the actual algorithmic components of tools that are in widespread use.'),
(91886, 2008, 'bmc', 'Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes', 'Brock, Guy N|Shaffer, John R|Blakesley, Richard E|Lotz, Meredith J|Tseng, George C', 'Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, Universtiy of Louisville, Louisville, KY 40292, USA. guy.brock@louisville.edu|Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, Universtiy of Louisville, Louisville, KY 40292, USA. guy.brock@louisville.edu|Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, Universtiy of Louisville, Louisville, KY 40292, USA. guy.brock@louisville.edu|Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, Universtiy of Louisville, Louisville, KY 40292, USA. guy.brock@louisville.edu|Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, Universtiy of Louisville, Louisville, KY 40292, USA. guy.brock@louisville.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Artifacts|Data Interpretation, Statistical|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Software', 'Comparative Study', '10.1186/1471-2105-9-12', '18186917', 'Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures x time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set.'),
(91887, 2008, 'bmc', 'FCI: an R-based algorithm for evaluating uncertainty of absolute real-time PCR quantification', 'Verderio, Paolo|Pizzamiglio, Sara|Gallo, Fabio|Ramsden, Simon C', 'National Genetics Reference Laboratory (Manchester), St, Marys Hospital, Manchester, UK. paolo.verderio@istitutotumori.mi.it|National Genetics Reference Laboratory (Manchester), St, Marys Hospital, Manchester, UK. paolo.verderio@istitutotumori.mi.it|National Genetics Reference Laboratory (Manchester), St, Marys Hospital, Manchester, UK. paolo.verderio@istitutotumori.mi.it|National Genetics Reference Laboratory (Manchester), St, Marys Hospital, Manchester, UK. paolo.verderio@istitutotumori.mi.it', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|DNA|Data Interpretation, Statistical|Programming Languages|Reproducibility of Results|Reverse Transcriptase Polymerase Chain Reaction|Sensitivity and Specificity|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-9-13', '18186926', 'FCI is an R code for analyzing data from real-time PCR experiments. This algorithm estimates standard curve features as well as nucleic acid concentrations and confidence intervals according to Fiellers theorem.'),
(91888, 2008, 'bmc', 'Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models', 'Binder, Harald|Schumacher, Martin', 'Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstr, 1, 79104 Freiburg, Germany. binderh@fdm.uni-freiburg.de|Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstr, 1, 79104 Freiburg, Germany. binderh@fdm.uni-freiburg.de', 'Germany|Germany', 85, 'Biomarkers, Tumor|Computer Simulation|Gene Expression Profiling|Humans|Lymphoma, B-Cell|Models, Biological|Neoplasm Proteins|Prevalence|Proportional Hazards Models|Reproducibility of Results|Risk Assessment|Risk Factors|Sensitivity and Specificity|Software|Survival Analysis|Survival Rate', 'Evaluation Studies', '10.1186/1471-2105-9-14', '18186927', 'When predictive survival models are built from high-dimensional data, there are often additional covariates, such as clinical scores, that by all means have to be included into the final model. While there are several techniques for the fitting of sparse high-dimensional survival models by penalized parameter estimation, none allows for explicit consideration of such mandatory covariates.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91889, 2008, 'bmc', 'Multiple organism algorithm for finding ultraconserved elements', 'Christley, Scott|Lobo, Neil F|Madey, Greg', 'Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA. schristl@nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA. schristl@nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA. schristl@nd.edu', 'United States|United States|United States', 3, 'Algorithms|Animals|Base Sequence|Chromosome Mapping|Conserved Sequence|Humans|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Species Specificity', 'Journal Article', '10.1186/1471-2105-9-15', '18186941', 'Ultraconserved elements are nucleotide or protein sequences with 100% identity (no mismatches, insertions, or deletions) in the same organism or between two or more organisms. Studies indicate that these conserved regions are associated with micro RNAs, mRNA processing, development and transcription regulation. The identification and characterization of these elements among genomes is necessary for the further understanding of their functionality.'),
(91890, 2008, 'bmc', 'A new method for class prediction based on signed-rank algorithms applied to Affymetrix microarray experiments', 'Rème, Thierry|Hose, Dirk|De Vos, John|Vassal, Aurélien|Poulain, Pierre-Olivier|Pantesco, Véronique|Goldschmidt, Hartmut|Klein, Bernard', 'INSERM, U847, 99 rue Puech Villa, 34197 Montpellier, France. reme@montp.inserm.fr|INSERM, U847, 99 rue Puech Villa, 34197 Montpellier, France. reme@montp.inserm.fr|INSERM, U847, 99 rue Puech Villa, 34197 Montpellier, France. reme@montp.inserm.fr|INSERM, U847, 99 rue Puech Villa, 34197 Montpellier, France. reme@montp.inserm.fr|INSERM, U847, 99 rue Puech Villa, 34197 Montpellier, France. reme@montp.inserm.fr|INSERM, U847, 99 rue Puech Villa, 34197 Montpellier, France. reme@montp.inserm.fr|INSERM, U847, 99 rue Puech Villa, 34197 Montpellier, France. reme@montp.inserm.fr|INSERM, U847, 99 rue Puech Villa, 34197 Montpellier, France. reme@montp.inserm.fr', 'France|France|France|France|France|France|France|France', 0, 'Algorithms|Data Interpretation, Statistical|Europe|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-9-16', '18190711', 'The huge amount of data generated by DNA chips is a powerful basis to classify various pathologies. However, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix(R) technology provides both a quantitative fluorescence signal and a decision (detection call: absent or present) based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization. We developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data were obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM) patients.'),
(91891, 2008, 'bmc', 'Prediction of enzyme function based on 3D templates of evolutionarily important amino acids', 'Kristensen, David M|Ward, R Matthew|Lisewski, Andreas Martin|Erdin, Serkan|Chen, Brian Y|Fofanov, Viacheslav Y|Kimmel, Marek|Kavraki, Lydia E|Lichtarge, Olivier', 'Department of Molecular and Human Genetics, Biophysics, Baylor College of Medicine, Houston, TX 77030, USA. dk131363@gmail.com|Department of Molecular and Human Genetics, Biophysics, Baylor College of Medicine, Houston, TX 77030, USA. dk131363@gmail.com|Department of Molecular and Human Genetics, Biophysics, Baylor College of Medicine, Houston, TX 77030, USA. dk131363@gmail.com|Department of Molecular and Human Genetics, Biophysics, Baylor College of Medicine, Houston, TX 77030, USA. dk131363@gmail.com|Department of Molecular and Human Genetics, Biophysics, Baylor College of Medicine, Houston, TX 77030, USA. dk131363@gmail.com|Department of Molecular and Human Genetics, Biophysics, Baylor College of Medicine, Houston, TX 77030, USA. dk131363@gmail.com|Department of Molecular and Human Genetics, Biophysics, Baylor College of Medicine, Houston, TX 77030, USA. dk131363@gmail.com|Department of Molecular and Human Genetics, Biophysics, Baylor College of Medicine, Houston, TX 77030, USA. dk131363@gmail.com|Department of Molecular and Human Genetics, Biophysics, Baylor College of Medicine, Houston, TX 77030, USA. dk131363@gmail.com', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 62, 'Amino Acid Motifs|Artificial Intelligence|Databases, Protein|Enzymes|Evolution, Molecular|Likelihood Functions|Models, Biological|Pattern Recognition, Automated|Protein Conformation|Proteome|Sequence Alignment|Sequence Homology, Amino Acid|Structural Homology, Protein|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-9-17', '18190718', 'Structural genomics projects such as the Protein Structure Initiative (PSI) yield many new structures, but often these have no known molecular functions. One approach to recover this information is to use 3D templates - structure-function motifs that consist of a few functionally critical amino acids and may suggest functional similarity when geometrically matched to other structures. Since experimentally determined functional sites are not common enough to define 3D templates on a large scale, this work tests a computational strategy to select relevant residues for 3D templates.'),
(91892, 2007, 'bmc', 'Computational frontiers in biomedicine Proceedings of the Fourth Annual Conference of the MidSouth Computational Biology and Bioinformatics Society February 1-3, 2007 New Orleans, Louisiana, USA', '-', '-', '-', 62, 'Animals|Computational Biology|Humans', 'Congress', '10.1186/1471-2105-9-17', '18193535', '-'),
(91893, 2008, 'bmc', 'LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons', 'Ellinghaus, David|Kurtz, Stefan|Willhoeft, Ute', 'ZBH - Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany. dellinghaus@zbh.uni-hamburg.de|ZBH - Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany. dellinghaus@zbh.uni-hamburg.de|ZBH - Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany. dellinghaus@zbh.uni-hamburg.de', 'Germany|Germany|Germany', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Molecular Sequence Data|Programming Languages|Retroelements|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-9-18', '18194517', 'Transposable elements are abundant in eukaryotic genomes and it is believed that they have a significant impact on the evolution of gene and chromosome structure. While there are several completed eukaryotic genome projects, there are only few high quality genome wide annotations of transposable elements. Therefore, there is a considerable demand for computational identification of transposable elements. LTR retrotransposons, an important subclass of transposable elements, are well suited for computational identification, as they contain long terminal repeats (LTRs).'),
(91894, 2008, 'bmc', 'NestedMICA as an ab initio protein motif discovery tool', 'Doxc4x9fruel, Mutlu|Down, Thomas A|Hubbard, Tim Jp', 'Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1HH, UK. md5@sanger.ac.uk|Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1HH, UK. md5@sanger.ac.uk|Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1HH, UK. md5@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 25, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-9-19', '18194537', 'Discovering overrepresented patterns in amino acid sequences is an important step in protein functional element identification. We adapted and extended NestedMICA, an ab initio motif finder originally developed for finding transcription binding site motifs, to find short protein signals, and compared its performance with another popular protein motif finder, MEME. NestedMICA, an open source protein motif discovery tool written in Java, is driven by a Monte Carlo technique called Nested Sampling. It uses multi-class sequence background models to represent different uninteresting parts of sequences that do not contain motifs of interest. In order to assess NestedMICA as a protein motif finder, we have tested it on synthetic datasets produced by spiking instances of known motifs into a randomly selected set of protein sequences. NestedMICA was also tested using a biologically-authentic test set, where we evaluated its performance with respect to varying sequence length.'),
(91895, 2008, 'bmc', 'A simplified approach to disulfide connectivity prediction from protein sequences', 'Vincent, Marc|Passerini, Andrea|Labbé, Matthieu|Frasconi, Paolo', 'Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Università degli Studi di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy. vincent@dsi.unifi.it|Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Università degli Studi di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy. vincent@dsi.unifi.it|Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Università degli Studi di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy. vincent@dsi.unifi.it|Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Università degli Studi di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy. vincent@dsi.unifi.it', 'Italy|Italy|Italy|Italy', 0, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Disulfides|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-9-20', '18194539', 'Prediction of disulfide bridges from protein sequences is useful for characterizing structural and functional properties of proteins. Several methods based on different machine learning algorithms have been applied to solve this problem and public domain prediction services exist. These methods are however still potentially subject to significant improvements both in terms of prediction accuracy and overall architectural complexity.'),
(91896, 2008, 'bmc', 'LeARN: a platform for detecting, clustering and annotating non-coding RNAs', 'Noirot, Céline|Gaspin, Christine|Schiex, Thomas|Gouzy, Jérôme', 'Laboratoire Interactions Plantes Micro-organismes UMR441/2594, INRA/CNRS, F-31320 Castanet Tolosan, France. Celine.Noirot@toulouse.inra.fr|Laboratoire Interactions Plantes Micro-organismes UMR441/2594, INRA/CNRS, F-31320 Castanet Tolosan, France. Celine.Noirot@toulouse.inra.fr|Laboratoire Interactions Plantes Micro-organismes UMR441/2594, INRA/CNRS, F-31320 Castanet Tolosan, France. Celine.Noirot@toulouse.inra.fr|Laboratoire Interactions Plantes Micro-organismes UMR441/2594, INRA/CNRS, F-31320 Castanet Tolosan, France. Celine.Noirot@toulouse.inra.fr', 'France|France|France|France', 8, 'Amino Acid Sequence|Cluster Analysis|Database Management Systems|Databases, Nucleic Acid|Genome, Archaeal|Genomics|Knowledge Bases|Multigene Family|Pattern Recognition, Automated|Pyrococcus abyssi|Pyrococcus furiosus|Pyrococcus horikoshii|RNA, Untranslated|Sequence Alignment|Thermococcus|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-21', '18194551', 'In the last decade, sequencing projects have led to the development of a number of annotation systems dedicated to the structural and functional annotation of protein-coding genes. These annotation systems manage the annotation of the non-protein coding genes (ncRNAs) in a very crude way, allowing neither the edition of the secondary structures nor the clustering of ncRNA genes into families which are crucial for appropriate annotation of these molecules.'),
(91897, 2008, 'bmc', 'MeInfoText: associated gene methylation and cancer information from text mining', 'Fang, Yu-Ching|Huang, Hsuan-Cheng|Juan, Hsueh-Fen', 'Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 106, Taiwan. d94b43002@ntu.edu.tw|Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 106, Taiwan. d94b43002@ntu.edu.tw|Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 106, Taiwan. d94b43002@ntu.edu.tw', '-|-|-', 26, 'DNA Methylation|Databases, Nucleic Acid|Epigenesis, Genetic|Gene Expression Regulation, Neoplastic|Humans|Information Storage and Retrieval|Neoplasms', 'Comparative Study', '10.1186/1471-2105-9-22', '18194557', 'DNA methylation is an important epigenetic modification of the genome. Abnormal DNA methylation may result in silencing of tumor suppressor genes and is common in a variety of human cancer cells. As more epigenetics research is published electronically, it is desirable to extract relevant information from biological literature. To facilitate epigenetics research, we have developed a database called MeInfoText to provide gene methylation information from text mining.'),
(91898, 2008, 'bmc', 'Function approximation approach to the inference of reduced NGnet models of genetic networks', 'Kimura, Shuhei|Sonoda, Katsuki|Yamane, Soichiro|Maeda, Hideki|Matsumura, Koki|Hatakeyama, Mariko', 'Faculty of Engineering, Tottori University, 4-101 Koyama-Minami, Tottori, Japan. kimura@ike.tottori-u.ac.jp|Faculty of Engineering, Tottori University, 4-101 Koyama-Minami, Tottori, Japan. kimura@ike.tottori-u.ac.jp|Faculty of Engineering, Tottori University, 4-101 Koyama-Minami, Tottori, Japan. kimura@ike.tottori-u.ac.jp|Faculty of Engineering, Tottori University, 4-101 Koyama-Minami, Tottori, Japan. kimura@ike.tottori-u.ac.jp|Faculty of Engineering, Tottori University, 4-101 Koyama-Minami, Tottori, Japan. kimura@ike.tottori-u.ac.jp|Faculty of Engineering, Tottori University, 4-101 Koyama-Minami, Tottori, Japan. kimura@ike.tottori-u.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Bacterial Proteins|Computational Biology|Gene Expression Profiling|Gene Regulatory Networks|Models, Genetic|Oligonucleotide Array Sequence Analysis', 'Comparative Study', '10.1186/1471-2105-9-23', '18194576', 'The inference of a genetic network is a problem in which mutual interactions among genes are deduced using time-series of gene expression patterns. While a number of models have been proposed to describe genetic regulatory networks, this study focuses on a set of differential equations since it has the ability to model dynamic behavior of gene expression. When we use a set of differential equations to describe genetic networks, the inference problem can be defined as a function approximation problem. On the basis of this problem definition, we propose in this study a new method to infer reduced NGnet models of genetic networks.'),
(91899, 2008, 'bmc', 'Combining sequence-based prediction methods and circular dichroism and infrared spectroscopic data to improve protein secondary structure determinations', 'Lees, Jonathan G|Janes, Robert W', 'School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, UK. lees@biochem.ucl.ac.uk|School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, UK. lees@biochem.ucl.ac.uk', 'United Kingdom|United Kingdom', 8, 'Algorithms|Amino Acid Sequence|Circular Dichroism|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Peptide Mapping|Protein Structure, Secondary|Proteins|Sequence Analysis, Protein|Spectrophotometry, Infrared|Systems Integration', 'Journal Article', '10.1186/1471-2105-9-24', '18197968', 'A number of sequence-based methods exist for protein secondary structure prediction. Protein secondary structures can also be determined experimentally from circular dichroism, and infrared spectroscopic data using empirical analysis methods. It has been proposed that comparable accuracy can be obtained from sequence-based predictions as from these biophysical measurements. Here we have examined the secondary structure determination accuracies of sequence prediction methods with the empirically determined values from the spectroscopic data on datasets of proteins for which both crystal structures and spectroscopic data are available.'),
(91900, 2008, 'bmc', 'Using generalized procrustes analysis (GPA) for normalization of cDNA microarray data', 'Xiong, Huiling|Zhang, Dapeng|Martyniuk, Christopher J|Trudeau, Vance L|Xia, Xuhua', 'Centre for Advanced Research in Environmental Genomics, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada. hxion102@uottawa.ca|Centre for Advanced Research in Environmental Genomics, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada. hxion102@uottawa.ca|Centre for Advanced Research in Environmental Genomics, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada. hxion102@uottawa.ca|Centre for Advanced Research in Environmental Genomics, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada. hxion102@uottawa.ca|Centre for Advanced Research in Environmental Genomics, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada. hxion102@uottawa.ca', 'Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Data Interpretation, Statistical|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1186/1471-2105-9-25', '18199333', 'Normalization is essential in dual-labelled microarray data analysis to remove non-biological variations and systematic biases. Many normalization methods have been used to remove such biases within slides (Global, Lowess) and across slides (Scale, Quantile and VSN). However, all these popular approaches have critical assumptions about data distribution, which is often not valid in practice.'),
(91901, 2008, 'bmc', 'Cross-species and cross-platform gene expression studies with the Bioconductor-compliant R package annotationTools', 'Kuhn, Alexandre|Luthi-Carter, Ruth|Delorenzi, Mauro', 'Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne, Switzerland. alexandre.kuhn@isb-sib.ch|Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne, Switzerland. alexandre.kuhn@isb-sib.ch|Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne, Switzerland. alexandre.kuhn@isb-sib.ch', 'Switzerland|Switzerland|Switzerland', 37, 'Algorithms|Database Management Systems|Databases, Genetic|Documentation|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Programming Languages|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-9-26', '18201381', 'The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cross-species studies, in particular, have the power of identifying conserved, functionally important molecular processes. Validation of discoveries can now often be performed in readily available public data which frequently requires cross-platform studies.Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models (e.g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles.'),
(91902, 2008, 'bmc', 'T2prhd: a tool to study the patterns of repeat evolution', 'Sipos, Botond|Somogyi, Kálmán|Andó, István|Pénzes, Zsolt', 'Institute of Genetics, Biological Research Center of the Hungarian Academy of Sciences, P.O. Box 521, H-6701 Szeged, Hungary. sbotond@gmail.com|Institute of Genetics, Biological Research Center of the Hungarian Academy of Sciences, P.O. Box 521, H-6701 Szeged, Hungary. sbotond@gmail.com|Institute of Genetics, Biological Research Center of the Hungarian Academy of Sciences, P.O. Box 521, H-6701 Szeged, Hungary. sbotond@gmail.com|Institute of Genetics, Biological Research Center of the Hungarian Academy of Sciences, P.O. Box 521, H-6701 Szeged, Hungary. sbotond@gmail.com', 'Hungary|Hungary|Hungary|Hungary', 3, 'Algorithms|Base Sequence|Biological Evolution|Chromosome Mapping|DNA Mutational Analysis|Evolution, Molecular|Molecular Sequence Data|Multigene Family|Pattern Recognition, Automated|Phylogeny|Repetitive Sequences, Nucleic Acid|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-9-27', '18205906', 'The models developed to characterize the evolution of multigene families (such as the birth-and-death and the concerted models) have also been applied on the level of sequence repeats inside a gene/protein. Phylogenetic reconstruction is the method of choice to study the evolution of gene families and also sequence repeats in the light of these models. The characterization of the gene family evolution in view of the evolutionary models is done by the evaluation of the clustering of the sequences with the originating loci in mind. As the locus represents positional information, it is straightforward that in the case of the repeats the exact position in the sequence should be used, as the simple numbering according to repeat order can be misleading.'),
(91903, 2008, 'bmc', 'The XBabelPhish MAGE-ML and XML translator', 'Maier, Don|Wymore, Farrell|Sherlock, Gavin|Ball, Catherine A', 'Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. dMaier@genome.stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. dMaier@genome.stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. dMaier@genome.stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. dMaier@genome.stanford.edu', 'United States|United States|United States|United States', 0, 'Animals|Database Management Systems|Gene Expression Profiling|Humans|Hypermedia|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Systems Integration|User-Computer Interface|Work Simplification', 'Journal Article', '10.1186/1471-2105-9-28', '18205924', 'MAGE-ML has been promoted as a standard format for describing microarray experiments and the data they produce. Two characteristics of the MAGE-ML format compromise its use as a universal standard: First, MAGE-ML files are exceptionally large - too large to be easily read by most people, and often too large to be read by most software programs. Second, the MAGE-ML standard permits many ways of representing the same information. As a result, different producers of MAGE-ML create different documents describing the same experiment and its data. Recognizing all the variants is an unwieldy software engineering task, resulting in software packages that can read and process MAGE-ML from some, but not all producers. This Tower of MAGE-ML Babel bars the unencumbered exchange of microarray experiment descriptions couched in MAGE-ML.'),
(91904, 2008, 'bmc', 'A nonparametric model for quality control of database search results in shotgun proteomics', 'Zhang, Jiyang|Li, Jianqi|Liu, Xin|Xie, Hongwei|Zhu, Yunping|He, Fuchu', 'College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Changsha, 410073, China. zhangjy@hupo.org.cn|College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Changsha, 410073, China. zhangjy@hupo.org.cn|College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Changsha, 410073, China. zhangjy@hupo.org.cn|College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Changsha, 410073, China. zhangjy@hupo.org.cn|College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Changsha, 410073, China. zhangjy@hupo.org.cn|College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Changsha, 410073, China. zhangjy@hupo.org.cn', 'China|China|China|China|China|China', 13, 'Algorithms|Amino Acid Sequence|Database Management Systems|Databases, Protein|Discriminant Analysis|Information Storage and Retrieval|Molecular Sequence Data|Multivariate Analysis|Peptide Mapping|Proteomics|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein', 'Evaluation Studies', '10.1186/1471-2105-9-29', '18205957', 'Analysis of complex samples with tandem mass spectrometry (MS/MS) has become routine in proteomic research. However, validation of database search results creates a bottleneck in MS/MS data processing. Recently, methods based on a randomized database have become popular for quality control of database search results. However, a consequent problem is the ignorance of how to combine different database search scores to improve the sensitivity of randomized database methods.'),
(91905, 2008, 'bmc', 'SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data', 'Diaz-Uriarte, Ramon', 'Statistical Computing Team, Structural Biology and Biocomputing Programme, Spanish National Cancer Center (CNIO), Melchor Fernández Almagro 3, Madrid, 28029, Spain. rdiaz02@gmail.com', 'Spain', 9, 'Algorithms|Biomarkers|Diagnosis, Computer-Assisted|Gene Expression Profiling|Genetic Predisposition to Disease|Humans|Internet|Mortality|Software|Survival Analysis|Survival Rate', 'Journal Article', '10.1186/1471-2105-9-30', '18208605', 'Censored data are increasingly common in many microarray studies that attempt to relate gene expression to patient survival. Several new methods have been proposed in the last two years. Most of these methods, however, are not available to biomedical researchers, leading to many re-implementations from scratch of ad-hoc, and suboptimal, approaches with survival data.'),
(91906, 2008, 'bmc', 'The comparative analysis of statistics, based on the likelihood ratio criterion, in the automated annotation problem', 'Leontovich, Andrey M|Tokmachev, Konstantin Y|van Houwelingen, Hans C', 'Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow 119899, Russia. aml@genebee.msu.su|Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow 119899, Russia. aml@genebee.msu.su|Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow 119899, Russia. aml@genebee.msu.su', '-|-|-', 4, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Databases, Genetic|Likelihood Functions|Models, Genetic|Models, Statistical|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis', 'Journal Article', '10.1186/1471-2105-9-31', '18211675', 'This paper discusses the problem of automated annotation. It is a continuation of the previous work on the A4-algorithm (Adaptive algorithm of automated annotation) developed by Leontovich and others.'),
(91907, 2008, 'bmc', 'Prioritization of gene regulatory interactions from large-scale modules in yeast', 'Lee, Ho-Joon|Manke, Thomas|Bringas, Ricardo|Vingron, Martin', 'Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. lee@molgen.mpg.de|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. lee@molgen.mpg.de|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. lee@molgen.mpg.de|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. lee@molgen.mpg.de', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Fungal|Models, Biological|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Transcription Factors', 'Journal Article', '10.1186/1471-2105-9-32', '18211684', 'The identification of groups of co-regulated genes and their transcription factors, called transcriptional modules, has been a focus of many studies about biological systems. While methods have been developed to derive numerous modules from genome-wide data, individual links between regulatory proteins and target genes still need experimental verification. In this work, we aim to prioritize regulator-target links within transcriptional modules based on three types of large-scale data sources.'),
(91908, 2008, 'bmc', 'A fast structural multiple alignment method for long RNA sequences', 'Tabei, Yasuo|Kiryu, Hisanori|Kin, Taishin|Asai, Kiyoshi', 'Graduate School of Frontier Science, University of Tokyo, CB04 Kiban-tou 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan. tabei@cb.k.u-tokyo.ac.jp|Graduate School of Frontier Science, University of Tokyo, CB04 Kiban-tou 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan. tabei@cb.k.u-tokyo.ac.jp|Graduate School of Frontier Science, University of Tokyo, CB04 Kiban-tou 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan. tabei@cb.k.u-tokyo.ac.jp|Graduate School of Frontier Science, University of Tokyo, CB04 Kiban-tou 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan. tabei@cb.k.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan', 71, 'Algorithms|Base Sequence|Chromosome Mapping|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-9-33', '18215258', 'Aligning multiple RNA sequences is essential for analyzing non-coding RNAs. Although many alignment methods for non-coding RNAs, including Sankoffs algorithm for strict structural alignments, have been proposed, they are either inaccurate or computationally too expensive. Faster methods with reasonable accuracies are required for genome-scale analyses.'),
(91909, 2008, 'bmc', 'A statistical toolbox for metagenomics: assessing functional diversity in microbial communities', 'Schloss, Patrick D|Handelsman, Jo', 'Department of Microbiology, University of Massachusetts - Amherst, Amherst, MA 01003, USA. pschloss@microbio.umass.edu|Department of Microbiology, University of Massachusetts - Amherst, Amherst, MA 01003, USA. pschloss@microbio.umass.edu', 'United States|United States', 82, 'Animals|Bacteria|Bone and Bones|Computational Biology|Data Interpretation, Statistical|Genetic Variation|Genomics|Models, Genetic|Peptide Fragments|RNA, Ribosomal, 16S|Soil Microbiology|Water Microbiology|Whales', 'Journal Article', '10.1186/1471-2105-9-34', '18215273', 'The 99% of bacteria in the environment that are recalcitrant to culturing have spurred the development of metagenomics, a culture-independent approach to sample and characterize microbial genomes. Massive datasets of metagenomic sequences have been accumulated, but analysis of these sequences has focused primarily on the descriptive comparison of the relative abundance of proteins that belong to specific functional categories. More robust statistical methods are needed to make inferences from metagenomic data. In this study, we developed and applied a suite of tools to describe and compare the richness, membership, and structure of microbial communities using peptide fragment sequences extracted from metagenomic sequence data.'),
(91910, 2008, 'bmc', 'Enhancing the prediction of protein pairings between interacting families using orthology information', 'Izarzugaza, Jose M G|Juan, David|Pons, Carles|Pazos, Florencio|Valencia, Alfonso', 'Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO), C/Melchor Fernández Almagro, 3. 28029, Madrid,Spain. jmgonzalez@cnio.es|Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO), C/Melchor Fernández Almagro, 3. 28029, Madrid,Spain. jmgonzalez@cnio.es|Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO), C/Melchor Fernández Almagro, 3. 28029, Madrid,Spain. jmgonzalez@cnio.es|Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO), C/Melchor Fernández Almagro, 3. 28029, Madrid,Spain. jmgonzalez@cnio.es|Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO), C/Melchor Fernández Almagro, 3. 28029, Madrid,Spain. jmgonzalez@cnio.es', 'Spain|Spain|Spain|Spain|Spain', 12, 'Databases, Protein|Forecasting|Information Systems|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Alignment|Yeasts', 'Comparative Study', '10.1186/1471-2105-9-35', '18215279', 'It has repeatedly been shown that interacting protein families tend to have similar phylogenetic trees. These similarities can be used to predicting the mapping between two families of interacting proteins (i.e. which proteins from one family interact with which members of the other). The correct mapping will be that which maximizes the similarity between the trees. The two families may eventually comprise orthologs and paralogs, if members of the two families are present in more than one organism. This fact can be exploited to restrict the possible mappings, simply by impeding links between proteins of different organisms. We present here an algorithm to predict the mapping between families of interacting proteins which is able to incorporate information regarding orthologues, or any other assignment of proteins to classes that may restrict possible mappings.'),
(91911, 2008, 'bmc', 'Universal seeds for cDNA-to-genome comparison', 'Zhou, Leming|Stanton, Jonathan|Florea, Liliana', 'Department of Computer Science, George Washington University, Washington DC, 20052, USA. lmzhou@gwu.edu|Department of Computer Science, George Washington University, Washington DC, 20052, USA. lmzhou@gwu.edu|Department of Computer Science, George Washington University, Washington DC, 20052, USA. lmzhou@gwu.edu', 'United States|United States|United States', 0, 'Algorithms|Base Sequence|Chromosome Mapping|DNA, Complementary|Genome|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-9-36', '18215286', 'To meet the needs of gene annotation for newly sequenced organisms, optimized spaced seeds can be implemented into cross-species sequence alignment programs to accurately align gene sequences to the genome of a related species. So far, seed performance has been tested for comparisons between closely related species, such as human and mouse, or on simulated data. As the number and variety of genomes increases, it becomes desirable to identify a small set of universal seeds that perform optimally or near-optimally on a large range of comparisons.'),
(91912, 2008, 'bmc', 'Evaluation of phylogenetic footprint discovery for predicting bacterial cis-regulatory elements and revealing their evolution', 'Janky, Rekins|van Helden, Jacques', 'Laboratoire de Bioinformatique des Génomes et des Réseaux, Université Libre de Bruxelles (ULB), Campus Plaine, CP 263, Boulevard du Triomphe, 1050 Bruxelles, Belgium. rekins@scmbb.ulb.ac.be|Laboratoire de Bioinformatique des Génomes et des Réseaux, Université Libre de Bruxelles (ULB), Campus Plaine, CP 263, Boulevard du Triomphe, 1050 Bruxelles, Belgium. rekins@scmbb.ulb.ac.be', 'Belgium|Belgium', 29, 'Actinobacteria|Algorithms|Amino Acid Motifs|Bacterial Proteins|Conserved Sequence|DNA Footprinting|Escherichia coli K12|Evolution, Molecular|Genome, Bacterial|Gram-Positive Endospore-Forming Bacteria|Phylogeny|Promoter Regions, Genetic|Sequence Homology, Nucleic Acid|Serine Endopeptidases|Software', 'Journal Article', '10.1186/1471-2105-9-37', '18215291', 'The detection of conserved motifs in promoters of orthologous genes (phylogenetic footprints) has become a common strategy to predict cis-acting regulatory elements. Several software tools are routinely used to raise hypotheses about regulation. However, these tools are generally used as black boxes, with default parameters. A systematic evaluation of optimal parameters for a footprint discovery strategy can bring a sizeable improvement to the predictions.'),
(91913, 2008, 'bmc', 'A semiparametric modeling framework for potential biomarker discovery and the development of metabonomic profiles', 'Ghosh, Samiran|Grant, David F|Dey, Dipak K|Hill, Dennis W', 'Department of Mathematical Sciences, Indiana University Purdue University, Indianapolis, Indiana, USA. samiran@math.iupui.edu|Department of Mathematical Sciences, Indiana University Purdue University, Indianapolis, Indiana, USA. samiran@math.iupui.edu|Department of Mathematical Sciences, Indiana University Purdue University, Indianapolis, Indiana, USA. samiran@math.iupui.edu|Department of Mathematical Sciences, Indiana University Purdue University, Indianapolis, Indiana, USA. samiran@math.iupui.edu', 'India|India|India|India', 0, 'Algorithms|Artificial Intelligence|Biomarkers|Computer Simulation|Diagnosis, Computer-Assisted|Humans|Models, Biological|Pattern Recognition, Automated|Proteome|Wounds and Injuries', 'Evaluation Studies', '10.1186/1471-2105-9-38', '18215299', 'The discovery of biomarkers is an important step towards the development of criteria for early diagnosis of disease status. Recently electrospray ionization (ESI) and matrix assisted laser desorption (MALDI) time-of-flight (TOF) mass spectrometry have been used to identify biomarkers both in proteomics and metabonomics studies. Data sets generated from such studies are generally very large in size and thus require the use of sophisticated statistical techniques to glean useful information. Most recent attempts to process these types of data model each compounds intensity either discretely by positional (mass to charge ratio) clustering or through each compounds own intensity distribution. Traditionally data processing steps such as noise removal, background elimination and m/z alignment, are generally carried out separately resulting in unsatisfactory propagation of signals in the final model.'),
(91914, 2008, 'bmc', 'miRNAminer: a tool for homologous microRNA gene search', 'Artzi, Shay|Kiezun, Adam|Shomron, Noam', 'Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA. artzi@mit.edu|Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA. artzi@mit.edu|Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA. artzi@mit.edu', 'United States|United States|United States', 55, 'Animals|Base Sequence|Cattle|Databases, Genetic|Dogs|Humans|Internet|Mice|MicroRNAs|Molecular Sequence Data|Opossums|Pan troglodytes|Rats|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1186/1471-2105-9-39', '18215311', 'MicroRNAs (miRNAs), present in most metazoans, are small non-coding RNAs that control gene expression by negatively regulating translation through binding to the 3UTR of mRNA transcripts. Previously, experimental and computational methods were used to construct miRNA gene repositories agreeing with careful submission guidelines.'),
(91915, 2008, 'bmc', 'I-TASSER server for protein 3D structure prediction', 'Zhang, Yang', 'Center for Bioinformatics and Department of Molecular Bioscience, University of Kansas, 2030 Becker Dr, Lawrence, KS 66047, USA. yzhang@ku.edu', 'United States', 3116, 'Amino Acid Sequence|Computer Simulation|Internet|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-9-40', '18215316', 'Prediction of 3-dimensional protein structures from amino acid sequences represents one of the most important problems in computational structural biology. The community-wide Critical Assessment of Structure Prediction (CASP) experiments have been designed to obtain an objective assessment of the state-of-the-art of the field, where I-TASSER was ranked as the best method in the server section of the recent 7th CASP experiment. Our laboratory has since then received numerous requests about the public availability of the I-TASSER algorithm and the usage of the I-TASSER predictions.'),
(91916, 2008, 'bmc', 'Predicting the interactome of Xanthomonas oryzae pathovar oryzae for target selection and DB service', 'Kim, Jeong-Gu|Park, Daeui|Kim, Byoung-Chul|Cho, Seong-Woong|Kim, Yeong Tae|Park, Young-Jin|Cho, Hee Jung|Park, Hyunseok|Kim, Ki-Bong|Yoon, Kyong-Oh|Park, Soo-Jun|Lee, Byoung-Moo|Bhak, Jong', 'Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com|Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com|Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com|Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com|Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com|Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com|Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com|Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com|Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com|Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com|Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com|Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com|Microbial Genetics Division, National Institute of Agricultural Biotechnology (NIAB), Rural Development Administration (RDA), Suwon 441-707, Korea. jkim5aug@yahoo.com', '-|-|-|-|-|-|-|-|-|-|-|-|-', 28, 'Bacterial Proteins|Database Management Systems|Databases, Protein|Drug Delivery Systems|Protein Interaction Mapping|Proteome|Signal Transduction|User-Computer Interface|Xanthomonas', 'Journal Article', '10.1186/1471-2105-9-41', '18215330', 'Protein-protein interactions (PPIs) play key roles in various cellular functions. In addition, some critical inter-species interactions such as host-pathogen interactions and pathogenicity occur through PPIs. Phytopathogenic bacteria infect hosts through attachment to host tissue, enzyme secretion, exopolysaccharides production, toxins release, iron acquisition, and effector proteins secretion. Many such mechanisms involve some kind of protein-protein interaction in hosts. Our first aim was to predict the whole protein interaction pairs (interactome) of Xanthomonas oryzae pathovar oryzae (Xoo) that is an important pathogenic bacterium that causes bacterial blight (BB) in rice. We developed a detection protocol to find possibly interacting proteins in its host using whole genome PPI prediction algorithms. The second aim was to build a DB server and a bioinformatic procedure for finding target proteins in Xoo for developing pesticides that block host-pathogen protein interactions within critical biochemical pathways.'),
(91917, 2008, 'bmc', 'New resampling method for evaluating stability of clusters', 'Gana Dresen, Irina M|Boes, Tanja|Huesing, Johannes|Neuhaeuser, Markus|Joeckel, Karl-Heinz', 'Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitaetsklinikum Essen, Germany. irina.gana-dresen@uk-essen.de|Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitaetsklinikum Essen, Germany. irina.gana-dresen@uk-essen.de|Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitaetsklinikum Essen, Germany. irina.gana-dresen@uk-essen.de|Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitaetsklinikum Essen, Germany. irina.gana-dresen@uk-essen.de|Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitaetsklinikum Essen, Germany. irina.gana-dresen@uk-essen.de', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Multigene Family|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-9-42', '18218074', 'Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in clustering procedures. Statistical methods are required to distinguish between real and random clusters. Several methods for assessing cluster stability have been published, including resampling methods such as the bootstrap. We propose a new resampling method based on continuous weights to assess the stability of clusters in hierarchical clustering. While in bootstrapping approximately one third of the original items is lost, continuous weights avoid zero elements and instead allow non integer diagonal elements, which leads to retention of the full dimensionality of space, i.e. each variable of the original data set is represented in the resampling sample.'),
(91918, 2008, 'bmc', 'Predicting biological system objectives de novo from internal state measurements', 'Gianchandani, Erwin P|Oberhardt, Matthew A|Burgard, Anthony P|Maranas, Costas D|Papin, Jason A', 'Department of Biomedical Engineering University of Virginia Box 800759, Health System Charlottesville, VA 22908 USA. erwin@virginia.edu|Department of Biomedical Engineering University of Virginia Box 800759, Health System Charlottesville, VA 22908 USA. erwin@virginia.edu|Department of Biomedical Engineering University of Virginia Box 800759, Health System Charlottesville, VA 22908 USA. erwin@virginia.edu|Department of Biomedical Engineering University of Virginia Box 800759, Health System Charlottesville, VA 22908 USA. erwin@virginia.edu|Department of Biomedical Engineering University of Virginia Box 800759, Health System Charlottesville, VA 22908 USA. erwin@virginia.edu', 'United States|United States|United States|United States|United States', 68, 'Computational Biology|Forecasting|Metabolic Networks and Pathways|Saccharomyces cerevisiae|Systems Biology', 'Comparative Study', '10.1186/1471-2105-9-43', '18218092', 'Optimization theory has been applied to complex biological systems to interrogate network properties and develop and refine metabolic engineering strategies. For example, methods are emerging to engineer cells to optimally produce byproducts of commercial value, such as bioethanol, as well as molecular compounds for disease therapy. Flux balance analysis (FBA) is an optimization framework that aids in this interrogation by generating predictions of optimal flux distributions in cellular networks. Critical features of FBA are the definition of a biologically relevant objective function (e.g., maximizing the rate of synthesis of biomass, a unit of measurement of cellular growth) and the subsequent application of linear programming (LP) to identify fluxes through a reaction network. Despite the success of FBA, a central remaining challenge is the definition of a network objective with biological meaning.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91919, 2008, 'bmc', 'Generating samples for association studies based on HapMap data', 'Li, Jing|Chen, Yixuan', 'Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH 44106, USA. jingli@case.edu|Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH 44106, USA. jingli@case.edu', 'United States|United States', 37, 'Computer Simulation|Databases, Genetic|Genetic Variation|Haplotypes|Information Storage and Retrieval|Models, Genetic|Models, Statistical|Polymorphism, Single Nucleotide|Sample Size', 'Journal Article', '10.1186/1471-2105-9-44', '18218094', 'With the completion of the HapMap project, a variety of computational algorithms and tools have been proposed for haplotype inference, tag SNP selection and genome-wide association studies. Simulated data are commonly used in evaluating these new developed approaches. In addition to simulations based on population models, empirical data generated by perturbing real data, has also been used because it may inherit specific properties from real data. However, there is no tool that is publicly available to generate large scale simulated variation data by taking into account knowledge from the HapMap project.'),
(91920, 2008, 'bmc', 'A genetic approach for building different alphabets for peptide and protein classification', 'Nanni, Loris|Lumini, Alessandra', 'DEIS, Università di Bologna, Via Venezia 52, 47023 Cesena (FC), Italy. loris.nanni@unibo.it|DEIS, Università di Bologna, Via Venezia 52, 47023 Cesena (FC), Italy. loris.nanni@unibo.it', 'Italy|Italy', 34, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Computer Simulation|Models, Chemical|Molecular Sequence Data|Pattern Recognition, Automated|Peptides|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1186/1471-2105-9-45', '18218100', 'In this paper, it is proposed an optimization approach for producing reduced alphabets for peptide classification, using a Genetic Algorithm. The classification task is performed by a multi-classifier system where each classifier (Linear or Radial Basis function Support Vector Machines) is trained using features extracted by different reduced alphabets. Each alphabet is constructed by a Genetic Algorithm whose objective function is the maximization of the area under the ROC-curve obtained in several classification problems.'),
(91921, 2008, 'bmc', 'EzArray: a web-based highly automated Affymetrix expression array data management and analysis system', 'Zhu, Yuerong|Zhu, Yuelin|Xu, Wei', 'Research and Development, BioInfoRx, Inc,, Middleton, WI 53562, USA. ron@bioinforx.com|Research and Development, BioInfoRx, Inc,, Middleton, WI 53562, USA. ron@bioinforx.com|Research and Development, BioInfoRx, Inc,, Middleton, WI 53562, USA. ron@bioinforx.com', 'United States|United States|United States', 16, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-46', '18218103', 'Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand.'),
(91922, 2008, 'bmc', 'Discrimination of outer membrane proteins with improved performance', 'Yan, Changhui|Hu, Jing|Wang, Yingfeng', 'Department of Computer Science, Utah State University, Logan, UT 84322, USA. charles.yan@usu.edu|Department of Computer Science, Utah State University, Logan, UT 84322, USA. charles.yan@usu.edu|Department of Computer Science, Utah State University, Logan, UT 84322, USA. charles.yan@usu.edu', 'United States|United States|United States', 0, 'Bacterial Outer Membrane Proteins|Cell Membrane|Discriminant Analysis', 'Comparative Study', '10.1186/1471-2105-9-47', '18218108', 'Outer membrane proteins (OMPs) perform diverse functional roles in Gram-negative bacteria. Identification of outer membrane proteins is an important task.'),
(91923, 2008, 'bmc', 'The average mutual information profile as a genomic signature', 'Bauer, Mark|Schuster, Sheldon M|Sayood, Khalid', 'Department of Electrical Engineering, University of Nebraska, Lincoln, NE USA. mark@engr.unl.edu|Department of Electrical Engineering, University of Nebraska, Lincoln, NE USA. mark@engr.unl.edu|Department of Electrical Engineering, University of Nebraska, Lincoln, NE USA. mark@engr.unl.edu', 'United States|United States|United States', 0, 'Biological Evolution|Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Evolution, Molecular|Genetic Variation|Genomics|Information Theory|Models, Genetic|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-9-48', '18218139', 'Occult organizational structures in DNA sequences may hold the key to understanding functional and evolutionary aspects of the DNA molecule. Such structures can also provide the means for identifying and discriminating organisms using genomic data. Species specific genomic signatures are useful in a variety of contexts such as evolutionary analysis, assembly and classification of genomic sequences from large uncultivated microbial communities and a rapid identification system in health hazard situations.'),
(91924, 2008, 'bmc', 'A dynamic Bayesian network approach to protein secondary structure prediction', 'Yao, Xin-Qiu|Zhu, Huaiqiu|She, Zhen-Su', 'State Key Laboratory for Turbulence and Complex Systems and Department of Biomedical Engineering, Peking University, Beijing 100871, China. yxq@ctb.pku.edu.cn|State Key Laboratory for Turbulence and Complex Systems and Department of Biomedical Engineering, Peking University, Beijing 100871, China. yxq@ctb.pku.edu.cn|State Key Laboratory for Turbulence and Complex Systems and Department of Biomedical Engineering, Peking University, Beijing 100871, China. yxq@ctb.pku.edu.cn', 'China|China|China', 51, 'Algorithms|Amino Acid Sequence|Bayes Theorem|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Structure, Secondary|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-9-49', '18218144', 'Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful information relevant to sequence-structure relationship. However, at present, the prediction accuracy of pure HMM-type methods is much lower than that of machine learning-based methods such as neural networks (NN) or support vector machines (SVM).'),
(91925, 2008, 'bmc', 'Defining functional distances over gene ontology', 'del Pozo, Angela|Pazos, Florencio|Valencia, Alfonso', 'Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernandez Almagro, 3, E-28029 Madrid, Spain. adelpozo@cnio.es|Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernandez Almagro, 3, E-28029 Madrid, Spain. adelpozo@cnio.es|Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernandez Almagro, 3, E-28029 Madrid, Spain. adelpozo@cnio.es', 'Spain|Spain|Spain', 0, 'Algorithms|Amino Acid Sequence|Molecular Sequence Data|Multigene Family|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-9-50', '18221506', 'A fundamental problem when trying to define the functional relationships between proteins is the difficulty in quantifying functional similarities, even when well-structured ontologies exist regarding the activity of proteins (i.e. gene ontology -GO-). However, functional metrics can overcome the problems in the comparing and evaluating functional assignments and predictions. As a reference of proximity, previous approaches to compare GO terms considered linkage in terms of ontology weighted by a probability distribution that balances the non-uniform richness of different parts of the Direct Acyclic Graph. Here, we have followed a different approach to quantify functional similarities between GO terms.'),
(91926, 2008, 'bmc', 'The contrasting properties of conservation and correlated phylogeny in protein functional residue prediction', 'Manning, Jonathan R|Jefferson, Emily R|Barton, Geoffrey J', 'School of Life Sciences Research, University of Dundee, UK. jrm@compbio.dundee.ac.uk|School of Life Sciences Research, University of Dundee, UK. jrm@compbio.dundee.ac.uk|School of Life Sciences Research, University of Dundee, UK. jrm@compbio.dundee.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Conserved Sequence|Models, Chemical|Molecular Sequence Data|Phylogeny|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Statistics as Topic', 'Journal Article', '10.1186/1471-2105-9-51', '18221517', 'Amino acids responsible for structure, core function or specificity may be inferred from multiple protein sequence alignments where a limited set of residue types are tolerated. The rise in available protein sequences continues to increase the power of techniques based on this principle.'),
(91927, 2008, 'bmc', 'The development of PIPA: an integrated and automated pipeline for genome-wide protein function annotation', 'Yu, Chenggang|Zavaljevski, Nela|Desai, Valmik|Johnson, Seth|Stevens, Fred J|Reifman, Jaques', 'Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, Ft. Detrick, MD, USA. cyu@bioanalysis.org|Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, Ft. Detrick, MD, USA. cyu@bioanalysis.org|Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, Ft. Detrick, MD, USA. cyu@bioanalysis.org|Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, Ft. Detrick, MD, USA. cyu@bioanalysis.org|Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, Ft. Detrick, MD, USA. cyu@bioanalysis.org|Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, Ft. Detrick, MD, USA. cyu@bioanalysis.org', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Computational Biology|Databases, Protein|Pattern Recognition, Automated|Proteins|Proteomics|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-9-52', '18221520', 'Automated protein function prediction methods are needed to keep pace with high-throughput sequencing. With the existence of many programs and databases for inferring different protein functions, a pipeline that properly integrates these resources will benefit from the advantages of each method. However, integrated systems usually do not provide mechanisms to generate customized databases to predict particular protein functions. Here, we describe a tool termed PIPA (Pipeline for Protein Annotation) that has these capabilities.'),
(91928, 2008, 'bmc', 'TOBFAC: the database of tobacco transcription factors', 'Rushton, Paul J|Bokowiec, Marta T|Laudeman, Thomas W|Brannock, Jennifer F|Chen, Xianfeng|Timko, Michael P', 'Department of Biology, University of Virginia, Charlottesville, VA 22904, USA. pr8y@virginia.edu|Department of Biology, University of Virginia, Charlottesville, VA 22904, USA. pr8y@virginia.edu|Department of Biology, University of Virginia, Charlottesville, VA 22904, USA. pr8y@virginia.edu|Department of Biology, University of Virginia, Charlottesville, VA 22904, USA. pr8y@virginia.edu|Department of Biology, University of Virginia, Charlottesville, VA 22904, USA. pr8y@virginia.edu|Department of Biology, University of Virginia, Charlottesville, VA 22904, USA. pr8y@virginia.edu', 'United States|United States|United States|United States|United States|United States', 56, 'Chromosome Mapping|Database Management Systems|Databases, Genetic|Internet|Multigene Family|Plant Proteins|Sequence Analysis, DNA|Tobacco|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-53', '18221524', 'Regulation of gene expression at the level of transcription is a major control point in many biological processes. Transcription factors (TFs) can activate and/or repress the transcriptional rate of target genes and vascular plant genomes devote approximately 7% of their coding capacity to TFs. Global analysis of TFs has only been performed for three complete higher plant genomes - Arabidopsis (Arabidopsis thaliana), poplar (Populus trichocarpa) and rice (Oryza sativa). Presently, no large-scale analysis of TFs has been made from a member of the Solanaceae, one of the most important families of vascular plants. To fill this void, we have analysed tobacco (Nicotiana tabacum) TFs using a dataset of 1,159,022 gene-space sequence reads (GSRs) obtained by methylation filtering of the tobacco genome. An analytical pipeline was developed to isolate TF sequences from the GSR data set. This involved multiple (typically 10-15) independent searches with different versions of the TF family-defining domain(s) (normally the DNA-binding domain) followed by assembly into contigs and verification. Our analysis revealed that tobacco contains a minimum of 2,513 TFs representing all of the 64 well-characterised plant TF families. The number of TFs in tobacco is higher than previously reported for Arabidopsis and rice.'),
(91929, 2008, 'bmc', 'Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sample sizes', 'Frömke, Cornelia|Hothorn, Ludwig A|Kropf, Siegfried', 'Department of Biometry, Hannover Medical School, Carl-Neuberg-Str, 1, D-30625 Hannover, Germany. froemke.cornelia@mh-hannover.de|Department of Biometry, Hannover Medical School, Carl-Neuberg-Str, 1, D-30625 Hannover, Germany. froemke.cornelia@mh-hannover.de|Department of Biometry, Hannover Medical School, Carl-Neuberg-Str, 1, D-30625 Hannover, Germany. froemke.cornelia@mh-hannover.de', 'Germany|Germany|Germany', 0, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Models, Biological|Models, Statistical|Multivariate Analysis|Oligonucleotide Array Sequence Analysis|Sample Size|Signal Processing, Computer-Assisted', 'Journal Article', '10.1186/1471-2105-9-54', '18221560', 'In many research areas it is necessary to find differences between treatment groups with several variables. For example, studies of microarray data seek to find a significant difference in location parameters from zero or one for ratios thereof for each variable. However, in some studies a significant deviation of the difference in locations from zero (or 1 in terms of the ratio) is biologically meaningless. A relevant difference or ratio is sought in such cases.'),
(91930, 2008, 'bmc', 'Designing multiple degenerate primers via consecutive pairwise alignments', 'Najafabadi, Hamed Shateri|Torabi, Noorossadat|Chamankhah, Mahmood', 'Nanobiotechnology Research Center, Avesina Research Institute, Shahid Beheshti University, Evin Ave., Tehran, Iran. hamed.shaterinajafabadi@mail.mcgill.ca|Nanobiotechnology Research Center, Avesina Research Institute, Shahid Beheshti University, Evin Ave., Tehran, Iran. hamed.shaterinajafabadi@mail.mcgill.ca|Nanobiotechnology Research Center, Avesina Research Institute, Shahid Beheshti University, Evin Ave., Tehran, Iran. hamed.shaterinajafabadi@mail.mcgill.ca', '-|-|-', 0, 'Algorithms|Base Sequence|DNA Primers|Molecular Sequence Data|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-9-55', '18221562', 'Different algorithms have been proposed to solve various versions of degenerate primer design problem. For one of the most general cases, multiple degenerate primer design problem, very few algorithms exist, none of them satisfying the criterion of designing low number of primers that cover high number of sequences. Besides, the present algorithms require high computation capacity and running time.'),
(91931, 2008, 'bmc', 'A phase synchronization clustering algorithm for identifying interesting groups of genes from cell cycle expression data', 'Kim, Chang Sik|Bae, Cheol Soo|Tcha, Hong Joon', 'Institute of Animal Resources Research, Kangwon National University, Chuncheon, Republic of Korea. cskim@kangwon.ac.kr|Institute of Animal Resources Research, Kangwon National University, Chuncheon, Republic of Korea. cskim@kangwon.ac.kr|Institute of Animal Resources Research, Kangwon National University, Chuncheon, Republic of Korea. cskim@kangwon.ac.kr', '-|-|-', 16, 'Algorithms|Biological Clocks|Cell Cycle|Cell Cycle Proteins|Cluster Analysis|Computer Simulation|Gene Expression|Gene Expression Profiling|Models, Biological|Multigene Family|Signal Transduction', 'Journal Article', '10.1186/1471-2105-9-56', '18221564', 'The previous studies of genome-wide expression patterns show that a certain percentage of genes are cell cycle regulated. The expression data has been analyzed in a number of different ways to identify cell cycle dependent genes. In this study, we pose the hypothesis that cell cycle dependent genes are considered as oscillating systems with a rhythm, i.e. systems producing response signals with period and frequency. Therefore, we are motivated to apply the theory of multivariate phase synchronization for clustering cell cycle specific genome-wide expression data.'),
(91932, 2008, 'bmc', 'Gene function prediction using labeled and unlabeled data', 'Zhao, Xing-Ming|Wang, Yong|Chen, Luonan|Aihara, Kazuyuki', 'ERATO Aihara Complexity Modelling Project, JST, 4-6-1 Komaba, Meguro, Tokyo, Japan. xmzhao@aihara.jst.go.jp|ERATO Aihara Complexity Modelling Project, JST, 4-6-1 Komaba, Meguro, Tokyo, Japan. xmzhao@aihara.jst.go.jp|ERATO Aihara Complexity Modelling Project, JST, 4-6-1 Komaba, Meguro, Tokyo, Japan. xmzhao@aihara.jst.go.jp|ERATO Aihara Complexity Modelling Project, JST, 4-6-1 Komaba, Meguro, Tokyo, Japan. xmzhao@aihara.jst.go.jp', 'Japan|Japan|Japan|Japan', 0, 'Algorithms|Computer Simulation|Gene Expression Profiling|Models, Biological|Multigene Family|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Journal Article', '10.1186/1471-2105-9-57', '18221567', 'In general, gene function prediction can be formalized as a classification problem based on machine learning technique. Usually, both labeled positive and negative samples are needed to train the classifier. For the problem of gene function prediction, however, the available information is only about positive samples. In other words, we know which genes have the function of interested, while it is generally unclear which genes do not have the function, i.e. the negative samples. If all the genes outside of the target functional family are seen as negative samples, the imbalanced problem will arise because there are only a relatively small number of genes annotated in each family. Furthermore, the classifier may be degraded by the false negatives in the heuristically generated negative samples.'),
(91933, 2008, 'bmc', 'Signature Evaluation Tool (SET): a Java-based tool to evaluate and visualize the sample discrimination abilities of gene expression signatures', 'Jen, Chih-Hung|Yang, Tsun-Po|Tung, Chien-Yi|Su, Shu-Han|Lin, Chi-Hung|Hsu, Ming-Ta|Wang, Hsei-Wei', 'Microarray & Gene Expression Analysis Core Facility, VGH National Yang-Ming University Genome Research Center, Taipei, Taiwan. chjen2@ym.edu.tw|Microarray & Gene Expression Analysis Core Facility, VGH National Yang-Ming University Genome Research Center, Taipei, Taiwan. chjen2@ym.edu.tw|Microarray & Gene Expression Analysis Core Facility, VGH National Yang-Ming University Genome Research Center, Taipei, Taiwan. chjen2@ym.edu.tw|Microarray & Gene Expression Analysis Core Facility, VGH National Yang-Ming University Genome Research Center, Taipei, Taiwan. chjen2@ym.edu.tw|Microarray & Gene Expression Analysis Core Facility, VGH National Yang-Ming University Genome Research Center, Taipei, Taiwan. chjen2@ym.edu.tw|Microarray & Gene Expression Analysis Core Facility, VGH National Yang-Ming University Genome Research Center, Taipei, Taiwan. chjen2@ym.edu.tw|Microarray & Gene Expression Analysis Core Facility, VGH National Yang-Ming University Genome Research Center, Taipei, Taiwan. chjen2@ym.edu.tw', '-|-|-|-|-|-|-', 0, 'Artificial Intelligence|Biomarkers, Tumor|Cluster Analysis|Diagnosis, Computer-Assisted|Feasibility Studies|Gene Expression|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Internet|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Predictive Value of Tests|Principal Component Analysis|Selection Bias|Software', 'Journal Article', '10.1186/1471-2105-9-58', '18221568', 'The identification of specific gene expression signature for distinguishing sample groups is a dominant field in cancer research. Although a number of tools have been developed to identify optimal gene expression signatures, the number of signature genes obtained is often overly large to be applied clinically. Furthermore, experimental verification is sometimes limited by the availability of wet-lab materials such as antibodies and reagents. A tool to evaluate the discrimination power of candidate genes is therefore in high demand by clinical researchers.'),
(91934, 2008, 'bmc', 'Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification', 'Kouskoumvekaki, Irene|Yang, Zhiyong|Jónsdóttir, Svava O|Olsson, Lisbeth|Panagiotou, Gianni', 'Center for Microbial Biotechnology, BioCentrum-DTU, Building 223, Technical University of Denmark, DK-2800 Kgs Lyngby, Denmark. irene@cbs.dtu.dk|Center for Microbial Biotechnology, BioCentrum-DTU, Building 223, Technical University of Denmark, DK-2800 Kgs Lyngby, Denmark. irene@cbs.dtu.dk|Center for Microbial Biotechnology, BioCentrum-DTU, Building 223, Technical University of Denmark, DK-2800 Kgs Lyngby, Denmark. irene@cbs.dtu.dk|Center for Microbial Biotechnology, BioCentrum-DTU, Building 223, Technical University of Denmark, DK-2800 Kgs Lyngby, Denmark. irene@cbs.dtu.dk|Center for Microbial Biotechnology, BioCentrum-DTU, Building 223, Technical University of Denmark, DK-2800 Kgs Lyngby, Denmark. irene@cbs.dtu.dk', 'Denmark|Denmark|Denmark|Denmark|Denmark', 13, 'Artificial Intelligence|Aspergillus nidulans|Biomarkers|Cluster Analysis|Gene Expression Profiling|Genetic Enhancement|Genotype|Metabolism|Pattern Recognition, Automated|Protein Engineering|Proteomics|Salicylates', 'Journal Article', '10.1186/1471-2105-9-59', '18226195', 'In the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinant Aspergillus nidulans (mutants that produce the 6- methyl salicylic acid polyketide molecule) for application in metabolic engineering.'),
(91935, 2008, 'bmc', 'Inferring gene expression dynamics via functional regression analysis', 'Müller, Hans-Georg|Chiou, Jeng-Min|Leng, Xiaoyan', 'Department of Statistics, University of California, One Shields Avenue, Davis, CA 95616, USA. mueller@wald.ucdavis.edu|Department of Statistics, University of California, One Shields Avenue, Davis, CA 95616, USA. mueller@wald.ucdavis.edu|Department of Statistics, University of California, One Shields Avenue, Davis, CA 95616, USA. mueller@wald.ucdavis.edu', 'United States|United States|United States', 0, 'Aging|Algorithms|Animals|Computer Simulation|Data Interpretation, Statistical|Drosophila Proteins|Drosophila melanogaster|Gene Expression Profiling|Gene Expression Regulation, Developmental|Models, Biological|Morphogenesis|Oligonucleotide Array Sequence Analysis|Regression Analysis|Signal Transduction', 'Journal Article', '10.1186/1471-2105-9-60', '18226220', 'Temporal gene expression profiles characterize the time-dynamics of expression of specific genes and are increasingly collected in current gene expression experiments. In the analysis of experiments where gene expression is obtained over the life cycle, it is of interest to relate temporal patterns of gene expression associated with different developmental stages to each other to study patterns of long-term developmental gene regulation. We use tools from functional data analysis to study dynamic changes by relating temporal gene expression profiles of different developmental stages to each other.'),
(91936, 2008, 'bmc', 'Searching for evolutionary distant RNA homologs within genomic sequences using partition function posterior probabilities', 'Roshan, Usman|Chikkagoudar, Satish|Livesay, Dennis R', 'Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, USA. usman@cs.njit.edu|Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, USA. usman@cs.njit.edu|Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, USA. usman@cs.njit.edu', 'Jersey|Jersey|Jersey', 0, 'Base Sequence|Computational Biology|Databases, Genetic|Genome|Molecular Sequence Data|Nucleic Acid Conformation|Probability|RNA|Reference Standards|Reproducibility of Results|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Software Design', 'Journal Article', '10.1186/1471-2105-9-61', '18226231', 'Identification of RNA homologs within genomic stretches is difficult when pairwise sequence identity is low or unalignable flanking residues are present. In both cases structure-sequence or profile/family-sequence alignment programs become difficult to apply because of unreliable RNA structures or family alignments. As such, local sequence-sequence alignment programs are frequently used instead. We have recently demonstrated that maximal expected accuracy alignments using partition function match probabilities (implemented in Probalign) are significantly better than contemporary methods on heterogeneous length protein sequence datasets, thus suggesting an affinity for local alignment.'),
(91937, 2008, 'bmc', 'VirulentPred: a SVM based prediction method for virulent proteins in bacterial pathogens', 'Garg, Aarti|Gupta, Dinesh', 'Structural and Computational Biology Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), Aruna Asaf Ali Marg, New Delhi 110067, India. aarti@icgeb.res.in|Structural and Computational Biology Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), Aruna Asaf Ali Marg, New Delhi 110067, India. aarti@icgeb.res.in', 'India|India', 0, 'Bacterial Infections|Bacterial Proteins|Databases, Protein|Information Storage and Retrieval|Predictive Value of Tests|Proteome|Sequence Analysis, Protein|Software|Virulence', 'Comparative Study', '10.1186/1471-2105-9-62', '18226234', 'Prediction of bacterial virulent protein sequences has implications for identification and characterization of novel virulence-associated factors, finding novel drug/vaccine targets against proteins indispensable to pathogenicity, and understanding the complex virulence mechanism in pathogens.'),
(91938, 2008, 'bmc', 'Meta-analysis of breast cancer microarray studies in conjunction with conserved cis-elements suggest patterns for coordinate regulation', 'Smith, David D|Saetrom, Pål|Snøve, Ola|Lundberg, Cathryn|Rivas, Guillermo E|Glackin, Carlotta|Larson, Garrett P', 'Division of Molecular Medicine, City of Hope and Beckman Research Institute, Duarte, CA 91010, USA. dsmith02@coh.org|Division of Molecular Medicine, City of Hope and Beckman Research Institute, Duarte, CA 91010, USA. dsmith02@coh.org|Division of Molecular Medicine, City of Hope and Beckman Research Institute, Duarte, CA 91010, USA. dsmith02@coh.org|Division of Molecular Medicine, City of Hope and Beckman Research Institute, Duarte, CA 91010, USA. dsmith02@coh.org|Division of Molecular Medicine, City of Hope and Beckman Research Institute, Duarte, CA 91010, USA. dsmith02@coh.org|Division of Molecular Medicine, City of Hope and Beckman Research Institute, Duarte, CA 91010, USA. dsmith02@coh.org|Division of Molecular Medicine, City of Hope and Beckman Research Institute, Duarte, CA 91010, USA. dsmith02@coh.org', 'United States|United States|United States|United States|United States|United States|United States', 41, 'Algorithms|Biomarkers, Tumor|Breast Neoplasms|Conserved Sequence|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Meta-Analysis as Topic|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Regulatory Elements, Transcriptional|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-9-63', '18226260', 'Gene expression measurements from breast cancer (BrCa) tumors are established clinical predictive tools to identify tumor subtypes, identify patients showing poor/good prognosis, and identify patients likely to have disease recurrence. However, diverse breast cancer datasets in conjunction with diagnostic clinical arrays show little overlap in the sets of genes identified. One approach to identify a set of consistently dysregulated candidate genes in these tumors is to employ meta-analysis of multiple independent microarray datasets. This allows one to compare expression data from a diverse collection of breast tumor array datasets generated on either cDNA or oligonucleotide arrays.'),
(91939, 2008, 'bmc', 'CASCADE: a novel quasi all paths-based network analysis algorithm for clustering biological interactions', 'Hwang, Woochang|Cho, Young-Rae|Zhang, Aidong|Ramanathan, Murali', 'Department of Computer Science and Engineering, State University of New York, Buffalo, NY 14260, USA. whwang2@cse.buffalo.edu|Department of Computer Science and Engineering, State University of New York, Buffalo, NY 14260, USA. whwang2@cse.buffalo.edu|Department of Computer Science and Engineering, State University of New York, Buffalo, NY 14260, USA. whwang2@cse.buffalo.edu|Department of Computer Science and Engineering, State University of New York, Buffalo, NY 14260, USA. whwang2@cse.buffalo.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|Models, Biological|Multigene Family|Pattern Recognition, Automated|Protein Interaction Mapping|Proteome|Signal Transduction', 'Journal Article', '10.1186/1471-2105-9-64', '18230159', 'Quantitative characterization of the topological characteristics of protein-protein interaction (PPI) networks can enable the elucidation of biological functional modules. Here, we present a novel clustering methodology for PPI networks wherein the biological and topological influence of each protein on other proteins is modeled using the probability distribution that the series of interactions necessary to link a pair of distant proteins in the network occur within a time constant (the occurrence probability).'),
(91940, 2008, 'bmc', 'E-CAI: a novel server to estimate an expected value of Codon Adaptation Index (eCAI)', 'Puigbò, Pere|Bravo, Ignacio G|Garcia-Vallvé, Santiago', 'Evolutionary Genomics Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), Campus Sescelades, c/Marcelli Domingo s/n, 43007 Tarragona, Spain. ppuigbo@urv.cat|Evolutionary Genomics Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), Campus Sescelades, c/Marcelli Domingo s/n, 43007 Tarragona, Spain. ppuigbo@urv.cat|Evolutionary Genomics Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), Campus Sescelades, c/Marcelli Domingo s/n, 43007 Tarragona, Spain. ppuigbo@urv.cat', 'Spain|Spain|Spain', 0, 'Adaptation, Physiological|Algorithms|Base Sequence|Codon|Computer Simulation|Data Interpretation, Statistical|Genetic Variation|Internet|Models, Genetic|Models, Statistical|Molecular Sequence Data|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-9-65', '18230160', 'The Codon Adaptation Index (CAI) is a measure of the synonymous codon usage bias for a DNA or RNA sequence. It quantifies the similarity between the synonymous codon usage of a gene and the synonymous codon frequency of a reference set. Extreme values in the nucleotide or in the amino acid composition have a large impact on differential preference for synonymous codons. It is thence essential to define the limits for the expected value of CAI on the basis of sequence composition in order to properly interpret the CAI and provide statistical support to CAI analyses. Though several freely available programs calculate the CAI for a given DNA sequence, none of them corrects for compositional biases or provides confidence intervals for CAI values.'),
(91941, 2008, 'bmc', 'Validation of protein models by a neural network approach', 'Mereghetti, Paolo|Ganadu, Maria Luisa|Papaleo, Elena|Fantucci, Piercarlo|De Gioia, Luca', 'Department of Chemistry, University of Sassari, Via Vienna 2, 07100, Sassari, Italy. mereghetti@uniss.it|Department of Chemistry, University of Sassari, Via Vienna 2, 07100, Sassari, Italy. mereghetti@uniss.it|Department of Chemistry, University of Sassari, Via Vienna 2, 07100, Sassari, Italy. mereghetti@uniss.it|Department of Chemistry, University of Sassari, Via Vienna 2, 07100, Sassari, Italy. mereghetti@uniss.it|Department of Chemistry, University of Sassari, Via Vienna 2, 07100, Sassari, Italy. mereghetti@uniss.it', 'Italy|Italy|Italy|Italy|Italy', 23, 'Algorithms|Computer Simulation|Models, Chemical|Models, Molecular|Neural Networks (Computer)|Pattern Recognition, Automated|Protein Conformation|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein', 'Evaluation Studies', '10.1186/1471-2105-9-66', '18230168', 'The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure refinement, which has been recently identified as one of the bottlenecks limiting the quality and usefulness of protein structure prediction.'),
(91942, 2008, 'bmc', 'VennMaster: area-proportional Euler diagrams for functional GO analysis of microarrays', 'Kestler, Hans A|Müller, André|Kraus, Johann M|Buchholz, Malte|Gress, Thomas M|Liu, Hongfang|Kane, David W|Zeeberg, Barry R|Weinstein, John N', 'Neural Information Processing, University of Ulm, Germany. hans.kestler@uni-ulm.de|Neural Information Processing, University of Ulm, Germany. hans.kestler@uni-ulm.de|Neural Information Processing, University of Ulm, Germany. hans.kestler@uni-ulm.de|Neural Information Processing, University of Ulm, Germany. hans.kestler@uni-ulm.de|Neural Information Processing, University of Ulm, Germany. hans.kestler@uni-ulm.de|Neural Information Processing, University of Ulm, Germany. hans.kestler@uni-ulm.de|Neural Information Processing, University of Ulm, Germany. hans.kestler@uni-ulm.de|Neural Information Processing, University of Ulm, Germany. hans.kestler@uni-ulm.de|Neural Information Processing, University of Ulm, Germany. hans.kestler@uni-ulm.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 76, 'Algorithms|Computer Graphics|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Logistic Models|Models, Genetic|Oligonucleotide Array Sequence Analysis|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-67', '18230172', 'Microarray experiments generate vast amounts of data. The functional context of differentially expressed genes can be assessed by querying the Gene Ontology (GO) database via GoMiner. Directed acyclic graph representations, which are used to depict GO categories enriched with differentially expressed genes, are difficult to interpret and, depending on the particular analysis, may not be well suited for formulating new hypotheses. Additional graphical methods are therefore needed to augment the GO graphical representation.'),
(91943, 2008, 'bmc', 'Evaluation of two methods for computational HLA haplotypes inference using a real dataset', 'Bettencourt, Bruno F|Santos, Margarida R|Fialho, Raquel N|Couto, Ana R|Peixoto, Maria J|Pinheiro, João P|Spínola, Hélder|Mora, Marian G|Santos, Cristina|Brehm, António|Bruges-Armas, Jácome', 'Hospital Santo Espírito de Angra do Heroísmo, SEEBMO, Angra do Heroísmo, Azores, Portugal. bfbettencourt@seebmo.org|Hospital Santo Espírito de Angra do Heroísmo, SEEBMO, Angra do Heroísmo, Azores, Portugal. bfbettencourt@seebmo.org|Hospital Santo Espírito de Angra do Heroísmo, SEEBMO, Angra do Heroísmo, Azores, Portugal. bfbettencourt@seebmo.org|Hospital Santo Espírito de Angra do Heroísmo, SEEBMO, Angra do Heroísmo, Azores, Portugal. bfbettencourt@seebmo.org|Hospital Santo Espírito de Angra do Heroísmo, SEEBMO, Angra do Heroísmo, Azores, Portugal. bfbettencourt@seebmo.org|Hospital Santo Espírito de Angra do Heroísmo, SEEBMO, Angra do Heroísmo, Azores, Portugal. bfbettencourt@seebmo.org|Hospital Santo Espírito de Angra do Heroísmo, SEEBMO, Angra do Heroísmo, Azores, Portugal. bfbettencourt@seebmo.org|Hospital Santo Espírito de Angra do Heroísmo, SEEBMO, Angra do Heroísmo, Azores, Portugal. bfbettencourt@seebmo.org|Hospital Santo Espírito de Angra do Heroísmo, SEEBMO, Angra do Heroísmo, Azores, Portugal. bfbettencourt@seebmo.org|Hospital Santo Espírito de Angra do Heroísmo, SEEBMO, Angra do Heroísmo, Azores, Portugal. bfbettencourt@seebmo.org|Hospital Santo Espírito de Angra do Heroísmo, SEEBMO, Angra do Heroísmo, Azores, Portugal. bfbettencourt@seebmo.org', 'Portugal|Portugal|Portugal|Portugal|Portugal|Portugal|Portugal|Portugal|Portugal|Portugal|Portugal', 0, 'Algorithms|DNA Mutational Analysis|HLA Antigens|Haplotypes|Humans|Polymorphism, Single Nucleotide|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1186/1471-2105-9-68', '18230173', 'HLA haplotype analysis has been used in population genetics and in the investigation of disease-susceptibility locus, due to its high polymorphism. Several methods for inferring haplotype genotypic data have been proposed, but it is unclear how accurate each of the methods is or which method is superior. The accuracy of two of the leading methods of computational haplotype inference--Expectation-Maximization algorithm based (implemented in Arlequin V3.0) and Bayesian algorithm based (implemented in PHASE V2.1.1)--was compared using a set of 122 HLA haplotypes (A-B-Cw-DQB1-DRB1) determined through direct counting. The accuracy was measured with the Mean Squared Error (MSE), Similarity Index (IF) and Haplotype Identification Index (IH).'),
(91944, 2008, 'bmc', 'The strength of co-authorship in gene name disambiguation', 'Farkas, Richárd', 'Hungarian Academy of Science, Research Group on Artificial Intelligence, Aradi vertanuk tere, Szeged, Hungary. rfarkas@inf.u-szeged.hu', 'Hungary', 9, 'Authorship|Classification|Databases, Genetic|Decision Trees|Genes|MEDLINE|Natural Language Processing|Semantics', 'Journal Article', '10.1186/1471-2105-9-69', '18230174', 'A biomedical entity mention in articles and other free texts is often ambiguous. For example, 13% of the gene names (aliases) might refer to more than one gene. The task of Gene Symbol Disambiguation (GSD) - a special case of Word Sense Disambiguation (WSD) - is to assign a unique gene identifier for all identified gene name aliases in biology-related articles. Supervised and unsupervised machine learning WSD techniques have been applied in the biomedical field with promising results. We examine here the utilisation potential of the fact - one of the special features of biological articles - that the authors of the documents are known through graph-based semi-supervised methods for the GSD task.'),
(91945, 2008, 'bmc', 'GraphCrunch: a tool for large network analyses', 'Milenkovixc4x87, Tijana|Lai, Jason|Przulj, Natasa', 'Department of Computer Science, University of California, Irvine, CA 92697-3435, USA. tmilenko@ics.uci.edu|Department of Computer Science, University of California, Irvine, CA 92697-3435, USA. tmilenko@ics.uci.edu|Department of Computer Science, University of California, Irvine, CA 92697-3435, USA. tmilenko@ics.uci.edu', 'United States|United States|United States', 84, 'Algorithms|Computer Graphics|Computer Simulation|Models, Biological|Proteome|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-70', '18230190', 'The recent explosion in biological and other real-world network data has created the need for improved tools for large network analyses. In addition to well established global network properties, several new mathematical techniques for analyzing local structural properties of large networks have been developed. Small over-represented subgraphs, called network motifs, have been introduced to identify simple building blocks of complex networks. Small induced subgraphs, called graphlets, have been used to develop network signatures that summarize network topologies. Based on these network signatures, two new highly sensitive measures of network local structural similarities were designed: the relative graphlet frequency distance (RGF-distance) and the graphlet degree distribution agreement (GDD-agreement). Finding adequate null-models for biological networks is important in many research domains. Network properties are used to assess the fit of network models to the data. Various network models have been proposed. To date, there does not exist a software tool that measures the above mentioned local network properties. Moreover, none of the existing tools compare real-world networks against a series of network models with respect to these local as well as a multitude of global network properties.'),
(91946, 2008, 'bmc', 'PEPOP: computational design of immunogenic peptides', 'Moreau, Violaine|Fleury, Cécile|Piquer, Dominique|Nguyen, Christophe|Novali, Nicolas|Villard, Sylvie|Laune, Daniel|Granier, Claude|Molina, Franck', 'CNRS FRE 3009, SysDiag, CAP DELTA, 1682 Rue de la Valsière, CS 61003, 34184 Montpellier Cedex 4, France. violaine.moreau@sysdiag.cnrs.fr|CNRS FRE 3009, SysDiag, CAP DELTA, 1682 Rue de la Valsière, CS 61003, 34184 Montpellier Cedex 4, France. violaine.moreau@sysdiag.cnrs.fr|CNRS FRE 3009, SysDiag, CAP DELTA, 1682 Rue de la Valsière, CS 61003, 34184 Montpellier Cedex 4, France. violaine.moreau@sysdiag.cnrs.fr|CNRS FRE 3009, SysDiag, CAP DELTA, 1682 Rue de la Valsière, CS 61003, 34184 Montpellier Cedex 4, France. violaine.moreau@sysdiag.cnrs.fr|CNRS FRE 3009, SysDiag, CAP DELTA, 1682 Rue de la Valsière, CS 61003, 34184 Montpellier Cedex 4, France. violaine.moreau@sysdiag.cnrs.fr|CNRS FRE 3009, SysDiag, CAP DELTA, 1682 Rue de la Valsière, CS 61003, 34184 Montpellier Cedex 4, France. violaine.moreau@sysdiag.cnrs.fr|CNRS FRE 3009, SysDiag, CAP DELTA, 1682 Rue de la Valsière, CS 61003, 34184 Montpellier Cedex 4, France. violaine.moreau@sysdiag.cnrs.fr|CNRS FRE 3009, SysDiag, CAP DELTA, 1682 Rue de la Valsière, CS 61003, 34184 Montpellier Cedex 4, France. violaine.moreau@sysdiag.cnrs.fr|CNRS FRE 3009, SysDiag, CAP DELTA, 1682 Rue de la Valsière, CS 61003, 34184 Montpellier Cedex 4, France. violaine.moreau@sysdiag.cnrs.fr', 'France|France|France|France|France|France|France|France|France', 52, 'Algorithms|Antibodies|Computational Biology|Epitopes|Peptides|Protein Engineering|Protein Structure, Quaternary|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-9-71', '18234071', 'Most methods available to predict protein epitopes are sequence based. There is a need for methods using 3D information for prediction of discontinuous epitopes and derived immunogenic peptides.'),
(91947, 2008, 'bmc', 'Subfamily specific conservation profiles for proteins based on n-gram patterns', 'Vries, John K|Liu, Xiong', 'Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA. vries@ccbb.pitt.edu|Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA. vries@ccbb.pitt.edu', 'United States|United States', 11, 'Algorithms|Amino Acid Sequence|Conserved Sequence|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-9-72', '18234090', 'A new algorithm has been developed for generating conservation profiles that reflect the evolutionary history of the subfamily associated with a query sequence. It is based on n-gram patterns (NP{n,m}) which are sets of n residues and m wildcards in windows of size n+m. The generation of conservation profiles is treated as a signal-to-noise problem where the signal is the count of n-gram patterns in target sequences that are similar to the query sequence and the noise is the count over all target sequences. The signal is differentiated from the noise by applying singular value decomposition to sets of target sequences rank ordered by similarity with respect to the query.'),
(91948, 2008, 'bmc', 'SIGffRid: a tool to search for sigma factor binding sites in bacterial genomes using comparative approach and biologically driven statistics', 'Touzain, Fabrice|Schbath, Sophie|Debled-Rennesson, Isabelle|Aigle, Bertrand|Kucherov, Gregory|Leblond, Pierre', 'Laboratoire Lorrain de Recherche en Informatique et ses Applications, Campus Scientifique, B,P, 239, UMR CNRS-INPL-INRIA-Nancy 2-UHP 7503, 54506 Vandoeuvre-lès-Nancy, France. touzain@loria.fr|Laboratoire Lorrain de Recherche en Informatique et ses Applications, Campus Scientifique, B,P, 239, UMR CNRS-INPL-INRIA-Nancy 2-UHP 7503, 54506 Vandoeuvre-lès-Nancy, France. touzain@loria.fr|Laboratoire Lorrain de Recherche en Informatique et ses Applications, Campus Scientifique, B,P, 239, UMR CNRS-INPL-INRIA-Nancy 2-UHP 7503, 54506 Vandoeuvre-lès-Nancy, France. touzain@loria.fr|Laboratoire Lorrain de Recherche en Informatique et ses Applications, Campus Scientifique, B,P, 239, UMR CNRS-INPL-INRIA-Nancy 2-UHP 7503, 54506 Vandoeuvre-lès-Nancy, France. touzain@loria.fr|Laboratoire Lorrain de Recherche en Informatique et ses Applications, Campus Scientifique, B,P, 239, UMR CNRS-INPL-INRIA-Nancy 2-UHP 7503, 54506 Vandoeuvre-lès-Nancy, France. touzain@loria.fr|Laboratoire Lorrain de Recherche en Informatique et ses Applications, Campus Scientifique, B,P, 239, UMR CNRS-INPL-INRIA-Nancy 2-UHP 7503, 54506 Vandoeuvre-lès-Nancy, France. touzain@loria.fr', 'France|France|France|France|France|France', 11, 'Algorithms|Binding Sites|Chromosome Mapping|Genome, Bacterial|Pattern Recognition, Automated|Protein Binding|Sequence Analysis, DNA|Sigma Factor|Software', 'Journal Article', '10.1186/1471-2105-9-73', '18237374', 'Many programs have been developed to identify transcription factor binding sites. However, most of them are not able to infer two-word motifs with variable spacer lengths. This case is encountered for RNA polymerase Sigma (sigma) Factor Binding Sites (SFBSs) usually composed of two boxes, called -35 and -10 in reference to the transcription initiation point. Our goal is to design an algorithm detecting SFBS by using combinational and statistical constraints deduced from biological observations.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91949, 2008, 'bmc', 'Towards an automatic classification of protein structural domains based on structural similarity', 'Sam, Vichetra|Tai, Chin-Hsien|Garnier, Jean|Gibrat, Jean-Francois|Lee, Byungkook|Munson, Peter J', 'Mathematical and Statistical Computing Laboratory, DCB, CIT, NIH, DHHS, Bethesda, MD, USA. vsam@mail.nih.gov|Mathematical and Statistical Computing Laboratory, DCB, CIT, NIH, DHHS, Bethesda, MD, USA. vsam@mail.nih.gov|Mathematical and Statistical Computing Laboratory, DCB, CIT, NIH, DHHS, Bethesda, MD, USA. vsam@mail.nih.gov|Mathematical and Statistical Computing Laboratory, DCB, CIT, NIH, DHHS, Bethesda, MD, USA. vsam@mail.nih.gov|Mathematical and Statistical Computing Laboratory, DCB, CIT, NIH, DHHS, Bethesda, MD, USA. vsam@mail.nih.gov|Mathematical and Statistical Computing Laboratory, DCB, CIT, NIH, DHHS, Bethesda, MD, USA. vsam@mail.nih.gov', 'United States|United States|United States|United States|United States|United States', 16, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Cluster Analysis|Molecular Sequence Data|Pattern Recognition, Automated|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-9-74', '18237410', 'Formal classification of a large collection of protein structures aids the understanding of evolutionary relationships among them. Classifications involving manual steps, such as SCOP and CATH, face the challenge of increasing volume of available structures. Automatic methods such as FSSP or Dali Domain Dictionary, yield divergent classifications, for reasons not yet fully investigated. One possible reason is that the pairwise similarity scores used in automatic classification do not adequately reflect the judgments made in manual classification. Another possibility is the difference between manual and automatic classification procedures. We explore the degree to which these two factors might affect the final classification.'),
(91950, 2008, 'bmc', 'Rank-based edge reconstruction for scale-free genetic regulatory networks', 'Chen, Guanrao|Larsen, Peter|Almasri, Eyad|Dai, Yang', 'Department of Computer Science (MC152), University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL 60607, USA. gchen4@uic.edu|Department of Computer Science (MC152), University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL 60607, USA. gchen4@uic.edu|Department of Computer Science (MC152), University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL 60607, USA. gchen4@uic.edu|Department of Computer Science (MC152), University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL 60607, USA. gchen4@uic.edu', 'United States|United States|United States|United States', 17, 'Algorithms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Oligonucleotide Array Sequence Analysis|Proteome|Signal Transduction', 'Journal Article', '10.1186/1471-2105-9-75', '18237422', 'The reconstruction of genetic regulatory networks from microarray gene expression data has been a challenging task in bioinformatics. Various approaches to this problem have been proposed, however, they do not take into account the topological characteristics of the targeted networks while reconstructing them.'),
(91951, 2008, 'bmc', 'Response projected clustering for direct association with physiological and clinical response data', 'Yi, Sung-Gon|Park, Taesung|Lee, Jae K', 'Department of Statistics, Seoul National University, Silim-dong, Kwanak-gu, Seoul, 151-747, Korea. skon@bibs.snu.ac.kr|Department of Statistics, Seoul National University, Silim-dong, Kwanak-gu, Seoul, 151-747, Korea. skon@bibs.snu.ac.kr|Department of Statistics, Seoul National University, Silim-dong, Kwanak-gu, Seoul, 151-747, Korea. skon@bibs.snu.ac.kr', '-|-|-', 4, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Cluster Analysis|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Meta-Analysis as Topic|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Statistics as Topic', 'Evaluation Studies', '10.1186/1471-2105-9-76', '18237428', 'Microarray gene expression data are often analyzed together with corresponding physiological response and clinical metadata of biological subjects, e.g. patients residual tumor sizes after chemotherapy or glucose levels at various stages of diabetic patients. Current clustering analysis cannot directly incorporate such quantitative metadata into the clustering heatmap of gene expression. It will be quite useful if these clinical response data can be effectively summarized in the high-dimensional clustering display so that important groups of genes can be intuitively discovered with different degrees of relevance to target disease phenotypes.'),
(91952, 2008, 'bmc', 'AWclust: point-and-click software for non-parametric population structure analysis', 'Gao, Xiaoyi|Starmer, Joshua D', 'Miami Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136, USA. xgao@med.miami.edu|Miami Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136, USA. xgao@med.miami.edu', 'United States|United States', 53, 'Algorithms|Biological Evolution|Chromosome Mapping|Genetics, Population|Linkage Disequilibrium|Multigene Family|Phylogeny|Polymorphism, Single Nucleotide|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-77', '18237431', 'Population structure analysis is important to genetic association studies and evolutionary investigations. Parametric approaches, e.g. STRUCTURE and L-POP, usually assume Hardy-Weinberg equilibrium (HWE) and linkage equilibrium among loci in sample population individuals. However, the assumptions may not hold and allele frequency estimation may not be accurate in some data sets. The improved version of STRUCTURE (version 2.1) can incorporate linkage information among loci but is still sensitive to high background linkage disequilibrium. Nowadays, large-scale single nucleotide polymorphisms (SNPs) are becoming popular in genetic studies. Therefore, it is imperative to have software that makes full use of these genetic data to generate inference even when model assumptions do not hold or allele frequency estimation suffers from high variation.'),
(91953, 2008, 'bmc', 'OpenDMAP: an open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression', 'Hunter, Lawrence|Lu, Zhiyong|Firby, James|Baumgartner, William A|Johnson, Helen L|Ogren, Philip V|Cohen, K Bretonnel', 'Center for Computational Pharmacology, University of Colorado School of Medicine, Aurora, CO 80045, USA. Larry.Hunter@uchsc.edu|Center for Computational Pharmacology, University of Colorado School of Medicine, Aurora, CO 80045, USA. Larry.Hunter@uchsc.edu|Center for Computational Pharmacology, University of Colorado School of Medicine, Aurora, CO 80045, USA. Larry.Hunter@uchsc.edu|Center for Computational Pharmacology, University of Colorado School of Medicine, Aurora, CO 80045, USA. Larry.Hunter@uchsc.edu|Center for Computational Pharmacology, University of Colorado School of Medicine, Aurora, CO 80045, USA. Larry.Hunter@uchsc.edu|Center for Computational Pharmacology, University of Colorado School of Medicine, Aurora, CO 80045, USA. Larry.Hunter@uchsc.edu|Center for Computational Pharmacology, University of Colorado School of Medicine, Aurora, CO 80045, USA. Larry.Hunter@uchsc.edu', 'United States|United States|United States|United States|United States|United States|United States', 97, 'Algorithms|Cell Physiological Phenomena|Gene Expression|Health Knowledge, Attitudes, Practice|Information Storage and Retrieval|Models, Biological|Natural Language Processing|Periodicals as Topic|Protein Interaction Mapping|Protein Transport|Software', 'Journal Article', '10.1186/1471-2105-9-78', '18237434', 'Information extraction (IE) efforts are widely acknowledged to be important in harnessing the rapid advance of biomedical knowledge, particularly in areas where important factual information is published in a diverse literature. Here we report on the design, implementation and several evaluations of OpenDMAP, an ontology-driven, integrated concept analysis system. It significantly advances the state of the art in information extraction by leveraging knowledge in ontological resources, integrating diverse text processing applications, and using an expanded pattern language that allows the mixing of syntactic and semantic elements and variable ordering.'),
(91954, 2008, 'bmc', 'Ori-Finder: a web-based system for finding oriCs in unannotated bacterial genomes', 'Gao, Feng|Zhang, Chun-Ting', 'Department of Physics, Tianjin University, Tianjin 300072, China. fgao@tju.edu.cn|Department of Physics, Tianjin University, Tianjin 300072, China. fgao@tju.edu.cn', 'China|China', 190, 'Algorithms|Base Sequence|Chromosome Mapping|Genome, Bacterial|Information Storage and Retrieval|Information Systems|Internet|Molecular Sequence Data|Replication Origin|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-79', '18237442', 'Chromosomal replication is the central event in the bacterial cell cycle. Identification of replication origins (oriCs) is necessary for almost all newly sequenced bacterial genomes. Given the increasing pace of genome sequencing, the current available software for predicting oriCs, however, still leaves much to be desired. Therefore, the increasing availability of genome sequences calls for improved software to identify oriCs in newly sequenced and unannotated bacterial genomes.'),
(91955, 2008, 'bmc', 'ProLoc-GO: utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization', 'Huang, Wen-Lin|Tung, Chun-Wei|Ho, Shih-Wen|Hwang, Shiow-Fen|Ho, Shinn-Ying', 'Institute of Bioinformatics, National Chiao Tung University, Hsinchu, Taiwan. wenlinhuang2001@yahoo.com.tw|Institute of Bioinformatics, National Chiao Tung University, Hsinchu, Taiwan. wenlinhuang2001@yahoo.com.tw|Institute of Bioinformatics, National Chiao Tung University, Hsinchu, Taiwan. wenlinhuang2001@yahoo.com.tw|Institute of Bioinformatics, National Chiao Tung University, Hsinchu, Taiwan. wenlinhuang2001@yahoo.com.tw|Institute of Bioinformatics, National Chiao Tung University, Hsinchu, Taiwan. wenlinhuang2001@yahoo.com.tw', '-|-|-|-|-', 97, 'Algorithms|Cells|Computational Biology|Databases, Protein|Pattern Recognition, Automated|Proteins|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-9-80', '18241343', 'Gene Ontology (GO) annotation, which describes the function of genes and gene products across species, has recently been used to predict protein subcellular and subnuclear localization. Existing GO-based prediction methods for protein subcellular localization use the known accession numbers of query proteins to obtain their annotated GO terms. An accurate prediction method for predicting subcellular localization of novel proteins without known accession numbers, using only the input sequence, is worth developing.'),
(91956, 2008, 'bmc', 'Visualizing and clustering high throughput sub-cellular localization imaging', 'Hamilton, Nicholas A|Teasdale, Rohan D', 'ARC Centre of Excellence in Bioinformatics, The University of Queensland, Brisbane, Queensland 4072, Australia. n.hamilton@imb.uq.edu.au|ARC Centre of Excellence in Bioinformatics, The University of Queensland, Brisbane, Queensland 4072, Australia. n.hamilton@imb.uq.edu.au', 'Australia|Australia', 14, 'Artificial Intelligence|Cluster Analysis|Computer Graphics|Fluorescent Dyes|HeLa Cells|Humans|Image Processing, Computer-Assisted|Imaging, Three-Dimensional|Microscopy, Fluorescence|Organelles|Pattern Recognition, Automated|Reference Values|Reproducibility of Results|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-81', '18241353', 'The expansion of automatic imaging technologies has created a need to be able to efficiently compare and review large sets of image data. To enable comparisons of image data between samples we need to define the normal variation within distinct images of the same sample. Even with tightly controlled experimental conditions, protein expression can vary widely between cells, and because of the difficulty in viewing and comparing large image sets this might not be observed. Here we introduce a novel methodology, iCluster, for visualizing, clustering and comparing large sub-cellular localization image sets. For each member of an image set, iCluster generates statistics that have been found to be useful in distinguishing sub-cellular localization. The statistics are mapped into two or three dimensions such as to preserve distances between the statistics vectors. The complete image set is then visualized in two or three dimensions using the coordinates so determined. The result is images that are statistically similar are spatially close in the visualization allowing for easy comparison of images that are similar and distinguishment of dissimilar images into distinct clusters.'),
(91957, 2008, 'bmc', 'A comparison of common programming languages used in bioinformatics', 'Fourment, Mathieu|Gillings, Michael R', 'Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia. m.fourment@gmail.com|Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia. m.fourment@gmail.com', 'Australia|Australia', 46, 'Computational Biology|Programming Languages|Software|Software Validation', 'Comparative Study', '10.1186/1471-2105-9-82', '18251993', 'The performance of different programming languages has previously been benchmarked using abstract mathematical algorithms, but not using standard bioinformatics algorithms. We compared the memory usage and speed of execution for three standard bioinformatics methods, implemented in programs using one of six different programming languages. Programs for the Sellers algorithm, the Neighbor-Joining tree construction algorithm and an algorithm for parsing BLAST file outputs were implemented in C, C++, C#, Java, Perl and Python.'),
(91958, 2008, 'bmc', 'The VirusBanker database uses a Java program to allow flexible searching through Bunyaviridae sequences', 'Fourment, Mathieu|Gibbs, Mark J', 'Department of Biological Sciences, Macquarie University, Sydney NSW 2109, Australia. m.fourment@gmail.com|Department of Biological Sciences, Macquarie University, Sydney NSW 2109, Australia. m.fourment@gmail.com', 'Australia|Australia', 3, 'Base Sequence|Bunyaviridae|Database Management Systems|Databases, Genetic|Information Systems|Molecular Sequence Data|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1186/1471-2105-9-83', '18251994', 'Viruses of the Bunyaviridae have segmented negative-stranded RNA genomes and several of them cause significant disease. Many partial sequences have been obtained from the segments so that GenBank searches give complex results. Sequence databases usually use HTML pages to mediate remote sorting, but this approach can be limiting and may discourage a user from exploring a database.'),
(91959, 2008, 'bmc', 'OSIRISv12: a named entity recognition system for sequence variants of genes in biomedical literature', 'Furlong, Laura I|Dach, Holger|Hofmann-Apitius, Martin|Sanz, Ferran', 'Research Unit on Biomedical Informatics (GRIB), IMIM, UPF, PRBB, c/Dr, Aiguader 88, E-08003 Barcelona, Spain. lfurlong@imim.es|Research Unit on Biomedical Informatics (GRIB), IMIM, UPF, PRBB, c/Dr, Aiguader 88, E-08003 Barcelona, Spain. lfurlong@imim.es|Research Unit on Biomedical Informatics (GRIB), IMIM, UPF, PRBB, c/Dr, Aiguader 88, E-08003 Barcelona, Spain. lfurlong@imim.es|Research Unit on Biomedical Informatics (GRIB), IMIM, UPF, PRBB, c/Dr, Aiguader 88, E-08003 Barcelona, Spain. lfurlong@imim.es', 'Spain|Spain|Spain|Spain', 27, 'Artificial Intelligence|Information Storage and Retrieval|MEDLINE|Medical Subject Headings|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Polymorphism, Single Nucleotide|United States', 'Journal Article', '10.1186/1471-2105-9-84', '18251998', 'Single Nucleotide Polymorphisms, among other type of sequence variants, constitute key elements in genetic epidemiology and pharmacogenomics. While sequence data about genetic variation is found at databases such as dbSNP, clues about the functional and phenotypic consequences of the variations are generally found in biomedical literature. The identification of the relevant documents and the extraction of the information from them are hampered by the large size of literature databases and the lack of widely accepted standard notation for biomedical entities. Thus, automatic systems for the identification of citations of allelic variants of genes in biomedical texts are required.'),
(91960, 2008, 'bmc', 'Statistical issues in the analysis of Illumina data', 'Dunning, Mark J|Barbosa-Morais, Nuno L|Lynch, Andy G|Tavaré, Simon|Ritchie, Matthew E', 'Department of Oncology, University of Cambridge, CRUK Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK. md392@cam.ac.uk|Department of Oncology, University of Cambridge, CRUK Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK. md392@cam.ac.uk|Department of Oncology, University of Cambridge, CRUK Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK. md392@cam.ac.uk|Department of Oncology, University of Cambridge, CRUK Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK. md392@cam.ac.uk|Department of Oncology, University of Cambridge, CRUK Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK. md392@cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 82, 'Algorithms|Artifacts|Data Interpretation, Statistical|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-9-85', '18254947', 'Illumina bead-based arrays are becoming increasingly popular due to their high degree of replication and reported high data quality. However, little attention has been paid to the pre-processing of Illumina data. In this paper, we present our experience of analysing the raw data from an Illumina spike-in experiment and offer guidelines for those wishing to analyse expression data or develop new methodologies for this technology.'),
(91961, 2008, 'bmc', 'The Annotation, Mapping, Expression and Network (AMEN) suite of tools for molecular systems biology', 'Chalmel, Frédéric|Primig, Michael', 'Institut National de la Santé et de la Recherche Médicale Unité 625, Groupe dEtude de la Reproduction chez lHomme et les Mammifères, Institut Fédératif de Recherche 140, F-35042 Rennes, France. frederic.chalmel@rennes.inserm.fr|Institut National de la Santé et de la Recherche Médicale Unité 625, Groupe dEtude de la Reproduction chez lHomme et les Mammifères, Institut Fédératif de Recherche 140, F-35042 Rennes, France. frederic.chalmel@rennes.inserm.fr', 'France|France', 50, 'Algorithms|Chromosome Mapping|Computer Graphics|Gene Expression Profiling|Molecular Biology|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Proteome|Signal Transduction|Software|Systems Biology|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-86', '18254954', 'High-throughput genome biological experiments yield large and multifaceted datasets that require flexible and user-friendly analysis tools to facilitate their interpretation by life scientists. Many solutions currently exist, but they are often limited to specific steps in the complex process of data management and analysis and some require extensive informatics skills to be installed and run efficiently.'),
(91962, 2008, 'bmc', 'Building pathway clusters from Random Forests classification using class votes', 'Pang, Herbert|Zhao, Hongyu', 'Division of Biostatistics, Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520, USA. herbert.pang@yale.edu|Division of Biostatistics, Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520, USA. herbert.pang@yale.edu', 'United States|United States', 29, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Models, Biological|Models, Statistical|Multigene Family|Oligonucleotide Array Sequence Analysis|Proteome|Signal Transduction', 'Journal Article', '10.1186/1471-2105-9-87', '18254968', 'Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bring biological insights into microarray studies. A variety of methods have been proposed to construct networks using gene expression data. Because individual pathways do not act in isolation, it is important to understand how different pathways coordinate to perform cellular functions. However, there are no published methods describing how to build pathway clusters that are closely related to traits of interest.'),
(91963, 2008, 'bmc', 'Comparison of normalisation methods for surface-enhanced laser desorption and ionisation (SELDI) time-of-flight (TOF) mass spectrometry data', 'Meuleman, Wouter|Engwegen, Judith Ymn|Gast, Marie-Christine W|Beijnen, Jos H|Reinders, Marcel Jt|Wessels, Lodewyk Fa', 'Bioinformatics and Statistics, Department of Molecular Biology, The Netherlands Cancer Institute, Amsterdam, The Netherlands. w.meuleman@tudelft.nl|Bioinformatics and Statistics, Department of Molecular Biology, The Netherlands Cancer Institute, Amsterdam, The Netherlands. w.meuleman@tudelft.nl|Bioinformatics and Statistics, Department of Molecular Biology, The Netherlands Cancer Institute, Amsterdam, The Netherlands. w.meuleman@tudelft.nl|Bioinformatics and Statistics, Department of Molecular Biology, The Netherlands Cancer Institute, Amsterdam, The Netherlands. w.meuleman@tudelft.nl|Bioinformatics and Statistics, Department of Molecular Biology, The Netherlands Cancer Institute, Amsterdam, The Netherlands. w.meuleman@tudelft.nl|Bioinformatics and Statistics, Department of Molecular Biology, The Netherlands Cancer Institute, Amsterdam, The Netherlands. w.meuleman@tudelft.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 38, 'Reference Values|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Comparative Study', '10.1186/1471-2105-9-88', '18257918', 'Mass spectrometry for biological data analysis is an active field of research, providing an efficient way of high-throughput proteome screening. A popular variant of mass spectrometry is SELDI, which is often used to measure sample populations with the goal of developing (clinical) classifiers. Unfortunately, not only is the data resulting from such measurements quite noisy, variance between replicate measurements of the same sample can be high as well. Normalisation of spectra can greatly reduce the effect of this technical variance and further improve the quality and interpretability of the data. However, it is unclear which normalisation method yields the most informative result.'),
(91964, 2008, 'bmc', 'An analysis of the positional distribution of DNA motifs in promoter regions and its biological relevance', 'Casimiro, Ana C|Vinga, Susana|Freitas, Ana T|Oliveira, Arlindo L', 'INESC-ID/IST, Rua Alves Redol, 9 1000-029 Lisboa, Portugal. ana.casimiro@gmail.com|INESC-ID/IST, Rua Alves Redol, 9 1000-029 Lisboa, Portugal. ana.casimiro@gmail.com|INESC-ID/IST, Rua Alves Redol, 9 1000-029 Lisboa, Portugal. ana.casimiro@gmail.com|INESC-ID/IST, Rua Alves Redol, 9 1000-029 Lisboa, Portugal. ana.casimiro@gmail.com', 'Portugal|Portugal|Portugal|Portugal', 13, 'Algorithms|Base Sequence|Computer Simulation|DNA|Models, Genetic|Models, Statistical|Molecular Sequence Data|Promoter Regions, Genetic|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Statistical Distributions', 'Journal Article', '10.1186/1471-2105-9-89', '18257925', 'Motif finding algorithms have developed in their ability to use computationally efficient methods to detect patterns in biological sequences. However the posterior classification of the output still suffers from some limitations, which makes it difficult to assess the biological significance of the motifs found. Previous work has highlighted the existence of positional bias of motifs in the DNA sequences, which might indicate not only that the pattern is important, but also provide hints of the positions where these patterns occur preferentially.'),
(91965, 2008, 'bmc', 'Modularization of biochemical networks based on classification of Petri net t-invariants', 'Grafahrend-Belau, Eva|Schreiber, Falk|Heiner, Monika|Sackmann, Andrea|Junker, Björn H|Grunwald, Stefanie|Speer, Astrid|Winder, Katja|Koch, Ina', 'Technical University of Applied Sciences Berlin, FB VI/FB V, Bioinformatics/Biotechnology, Seestr, 64, 13347 Berlin, Germany. grafahr@ipk-gatersleben.de|Technical University of Applied Sciences Berlin, FB VI/FB V, Bioinformatics/Biotechnology, Seestr, 64, 13347 Berlin, Germany. grafahr@ipk-gatersleben.de|Technical University of Applied Sciences Berlin, FB VI/FB V, Bioinformatics/Biotechnology, Seestr, 64, 13347 Berlin, Germany. grafahr@ipk-gatersleben.de|Technical University of Applied Sciences Berlin, FB VI/FB V, Bioinformatics/Biotechnology, Seestr, 64, 13347 Berlin, Germany. grafahr@ipk-gatersleben.de|Technical University of Applied Sciences Berlin, FB VI/FB V, Bioinformatics/Biotechnology, Seestr, 64, 13347 Berlin, Germany. grafahr@ipk-gatersleben.de|Technical University of Applied Sciences Berlin, FB VI/FB V, Bioinformatics/Biotechnology, Seestr, 64, 13347 Berlin, Germany. grafahr@ipk-gatersleben.de|Technical University of Applied Sciences Berlin, FB VI/FB V, Bioinformatics/Biotechnology, Seestr, 64, 13347 Berlin, Germany. grafahr@ipk-gatersleben.de|Technical University of Applied Sciences Berlin, FB VI/FB V, Bioinformatics/Biotechnology, Seestr, 64, 13347 Berlin, Germany. grafahr@ipk-gatersleben.de|Technical University of Applied Sciences Berlin, FB VI/FB V, Bioinformatics/Biotechnology, Seestr, 64, 13347 Berlin, Germany. grafahr@ipk-gatersleben.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 62, 'Algorithms|Computer Simulation|Models, Biological|Multigene Family|Proteome|Signal Transduction', 'Journal Article', '10.1186/1471-2105-9-90', '18257938', 'Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the systems invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system.'),
(91966, 2008, 'bmc', 'Evolutionary approaches for the reverse-engineering of gene regulatory networks: a study on a biologically realistic dataset', 'Auliac, Cédric|Frouin, Vincent|Gidrol, Xavier|dAlché-Buc, Florence', 'Laboratoire Informatique, Biologie Intégrative et Systèmes Complexes (IBISC), Université dEvry-Val dEssonne, Evry, France. cauliac@ibisc.univ-evry.fr|Laboratoire Informatique, Biologie Intégrative et Systèmes Complexes (IBISC), Université dEvry-Val dEssonne, Evry, France. cauliac@ibisc.univ-evry.fr|Laboratoire Informatique, Biologie Intégrative et Systèmes Complexes (IBISC), Université dEvry-Val dEssonne, Evry, France. cauliac@ibisc.univ-evry.fr|Laboratoire Informatique, Biologie Intégrative et Systèmes Complexes (IBISC), Université dEvry-Val dEssonne, Evry, France. cauliac@ibisc.univ-evry.fr', 'France|France|France|France', 25, 'Biological Evolution|Computer Simulation|Evolution, Molecular|Gene Expression Regulation|Genetic Variation|Models, Genetic|Signal Transduction|Transcription Factors', 'Journal Article', '10.1186/1471-2105-9-91', '18261218', 'Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interactions may be modelled by a Bayesian Network (BN) that represents the presence of direct interactions from regulators to regulees by conditional probability distributions. We used enhanced evolutionary algorithms to stochastically evolve a set of candidate BN structures and found the model that best fits data without prior knowledge.'),
(91967, 2008, 'bmc', 'Microarray data mining using landmark gene-guided clustering', 'Chopra, Pankaj|Kang, Jaewoo|Yang, Jiong|Cho, HyungJun|Kim, Heenam Stanley|Lee, Min-Goo', 'Dept. of Computer Science and Engineering, Korea University, Seoul, Korea. pchopra@ncsu.edu|Dept. of Computer Science and Engineering, Korea University, Seoul, Korea. pchopra@ncsu.edu|Dept. of Computer Science and Engineering, Korea University, Seoul, Korea. pchopra@ncsu.edu|Dept. of Computer Science and Engineering, Korea University, Seoul, Korea. pchopra@ncsu.edu|Dept. of Computer Science and Engineering, Korea University, Seoul, Korea. pchopra@ncsu.edu|Dept. of Computer Science and Engineering, Korea University, Seoul, Korea. pchopra@ncsu.edu', '-|-|-|-|-|-', 21, 'Algorithms|Computational Biology|Databases, Genetic|Gene Expression Profiling|Models, Genetic|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-9-92', '18267003', 'Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms, however, generate only one set of clusters independent of the biological context of the analysis. This is often inadequate to explore data from different biological perspectives and gain new insights. We propose a new clustering model that can generate multiple versions of different clusters from a single dataset, each of which highlights a different aspect of the given dataset.'),
(91968, 2008, 'bmc', 'Supervised Lowess normalization of comparative genome hybridization data--application to lactococcal strain comparisons', 'van Hijum, Sacha A  F T|Baerends, Richard J S|Zomer, Aldert L|Karsens, Harma A|Martin-Requena, Victoria|Trelles, Oswaldo|Kok, Jan|Kuipers, Oscar P', 'Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN Haren, The Netherlands. s.a.f.t.van.hijum@rug.nl|Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN Haren, The Netherlands. s.a.f.t.van.hijum@rug.nl|Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN Haren, The Netherlands. s.a.f.t.van.hijum@rug.nl|Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN Haren, The Netherlands. s.a.f.t.van.hijum@rug.nl|Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN Haren, The Netherlands. s.a.f.t.van.hijum@rug.nl|Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN Haren, The Netherlands. s.a.f.t.van.hijum@rug.nl|Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN Haren, The Netherlands. s.a.f.t.van.hijum@rug.nl|Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, 9751 NN Haren, The Netherlands. s.a.f.t.van.hijum@rug.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 22, 'Chromosome Mapping|Databases, Genetic|Genetic Variation|Genome, Bacterial|In Situ Hybridization|Lactococcus|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1186/1471-2105-9-93', '18267014', 'Array-based comparative genome hybridization (aCGH) is commonly used to determine the genomic content of bacterial strains. Since prokaryotes in general have less conserved genome sequences than eukaryotes, sequence divergences between the genes in the genomes used for an aCGH experiment obstruct determination of genome variations (e.g. deletions). Current normalization methods do not take into consideration sequence divergence between target and microarray features and therefore cannot distinguish a difference in signal due to systematic errors in the data or due to sequence divergence.'),
(91969, 2008, 'bmc', 'Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction', 'Tan, Ching-Wai|Jones, David T', 'Department of Computer Science, University College London, London, UK. chingwai@ntu.edu.sg|Department of Computer Science, University College London, London, UK. chingwai@ntu.edu.sg', 'United Kingdom|United Kingdom', 13, 'Amino Acid Sequence|Discriminant Analysis|Evolution, Molecular|Molecular Sequence Data|Neural Networks (Computer)|Pattern Recognition, Automated|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-9-94', '18267018', 'We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represented as a machine learning problem, where neural networks are used to learn the native-like features of protein structures using a set of positive and negative training examples. A set of native protein structures provides the positive training examples, while negative training examples are simulated decoy structures obtained by reversing the sequences of native structures. Various features are extracted from the training dataset of positive and negative examples and used as inputs to the neural networks.'),
(91970, 2008, 'bmc', 'Simultaneous fitting of real-time PCR data with efficiency of amplification modeled as Gaussian function of target fluorescence', 'Batsch, Anke|Noetel, Andrea|Fork, Christian|Urban, Anita|Lazic, Daliborka|Lucas, Tina|Pietsch, Julia|Lazar, Andreas|Schömig, Edgar|Gründemann, Dirk', 'Department of Pharmacology, University of Cologne, Gleueler Strasse 24, 50931 Cologne, Germany. gabatsch@gmx.de|Department of Pharmacology, University of Cologne, Gleueler Strasse 24, 50931 Cologne, Germany. gabatsch@gmx.de|Department of Pharmacology, University of Cologne, Gleueler Strasse 24, 50931 Cologne, Germany. gabatsch@gmx.de|Department of Pharmacology, University of Cologne, Gleueler Strasse 24, 50931 Cologne, Germany. gabatsch@gmx.de|Department of Pharmacology, University of Cologne, Gleueler Strasse 24, 50931 Cologne, Germany. gabatsch@gmx.de|Department of Pharmacology, University of Cologne, Gleueler Strasse 24, 50931 Cologne, Germany. gabatsch@gmx.de|Department of Pharmacology, University of Cologne, Gleueler Strasse 24, 50931 Cologne, Germany. gabatsch@gmx.de|Department of Pharmacology, University of Cologne, Gleueler Strasse 24, 50931 Cologne, Germany. gabatsch@gmx.de|Department of Pharmacology, University of Cologne, Gleueler Strasse 24, 50931 Cologne, Germany. gabatsch@gmx.de|Department of Pharmacology, University of Cologne, Gleueler Strasse 24, 50931 Cologne, Germany. gabatsch@gmx.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 15, 'Algorithms|DNA|Data Interpretation, Statistical|Gene Targeting|Normal Distribution|Reproducibility of Results|Reverse Transcriptase Polymerase Chain Reaction|Sensitivity and Specificity|Spectrometry, Fluorescence', 'Evaluation Studies', '10.1186/1471-2105-9-95', '18267040', 'In real-time PCR, it is necessary to consider the efficiency of amplification (EA) of amplicons in order to determine initial target levels properly. EAs can be deduced from standard curves, but these involve extra effort and cost and may yield invalid EAs. Alternatively, EA can be extracted from individual fluorescence curves. Unfortunately, this is not reliable enough.'),
(91971, 2007, 'bmc', 'Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees', 'Chen, Xiaoyu|Blanchette, Mathieu', 'McGill Centre for Bioinformatics, 3775 University Street, room 332, Montreal, Quebec, Canada, H3A 2B4. xchen@cs.washington.edu|McGill Centre for Bioinformatics, 3775 University Street, room 332, Montreal, Quebec, Canada, H3A 2B4. xchen@cs.washington.edu', 'Canada|Canada', 36, 'Bayes Theorem|Forecasting|Gene Expression Regulation|Gene Regulatory Networks|Genes, Regulator|Humans|Regression Analysis|Tissue Distribution|Transcription Factors', 'Comparative Study', '10.1186/1471-2105-8-S10-S2', '18269696', 'In vertebrates, a large part of gene transcriptional regulation is operated by cis-regulatory modules. These modules are believed to be regulating much of the tissue-specificity of gene expression.'),
(91972, 2007, 'bmc', 'Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data', 'Costa, Ivan G|Krause, Roland|Opitz, Lennart|Schliep, Alexander', 'Department Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. ivan.filho@molgen.mpg.de|Department Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. ivan.filho@molgen.mpg.de|Department Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. ivan.filho@molgen.mpg.de|Department Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. ivan.filho@molgen.mpg.de', 'Germany|Germany|Germany|Germany', 17, 'Animals|Cluster Analysis|Drosophila melanogaster|Gene Expression Profiling|Gene Expression Regulation, Developmental|In Situ Hybridization|Learning|Oligonucleotide Array Sequence Analysis', 'Comparative Study', '10.1186/1471-2105-8-S10-S3', '18269697', 'Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. Complimentary large data sets of in situ RNA hybridization images for different stages of the fly embryo elucidate the spatial expression patterns.'),
(91973, 2007, 'bmc', 'Time-series alignment by non-negative multiple generalized canonical correlation analysis', 'Fischer, Bernd|Roth, Volker|Buhmann, Joachim M', 'Institute of Computational Science, ETH Zurich, Switzerland. bernd.fischer@inf.ethz.ch|Institute of Computational Science, ETH Zurich, Switzerland. bernd.fischer@inf.ethz.ch|Institute of Computational Science, ETH Zurich, Switzerland. bernd.fischer@inf.ethz.ch', 'Switzerland|Switzerland|Switzerland', 18, 'Biomarkers|Chromatography, Liquid|Mass Spectrometry|Multivariate Analysis|Proteomics|Sequence Analysis, Protein|Statistics as Topic|Time Factors', 'Comparative Study', '10.1186/1471-2105-8-S10-S4', '18269698', 'Quantitative analysis of differential protein expressions requires to align temporal elution measurements from liquid chromatography coupled to mass spectrometry (LC/MS). We propose multiple Canonical Correlation Analysis (mCCA) as a method to align the non-linearly distorted time scales of repeated LC/MS experiments in a robust way.'),
(91974, 2007, 'bmc', 'Analyzing in situ gene expression in the mouse brain with image registration, feature extraction and block clustering', 'Jagalur, Manjunatha|Pal, Chris|Learned-Miller, Erik|Zoeller, R Thomas|Kulp, David', 'Department of Computer Science, University of Massachusetts Amherst, Amherst, MA-01003, USA. manju@cs.umass.edu|Department of Computer Science, University of Massachusetts Amherst, Amherst, MA-01003, USA. manju@cs.umass.edu|Department of Computer Science, University of Massachusetts Amherst, Amherst, MA-01003, USA. manju@cs.umass.edu|Department of Computer Science, University of Massachusetts Amherst, Amherst, MA-01003, USA. manju@cs.umass.edu|Department of Computer Science, University of Massachusetts Amherst, Amherst, MA-01003, USA. manju@cs.umass.edu', 'United States|United States|United States|United States|United States', 0, 'Animals|Brain Chemistry|Brain Mapping|Cluster Analysis|Drosophila melanogaster|Gene Expression Regulation|In Situ Hybridization|Mice', 'Comparative Study', '10.1186/1471-2105-8-S10-S5', '18269699', 'Many important high throughput projects use in situ hybridization and may require the analysis of images of spatial cross sections of organisms taken with cellular level resolution. Projects creating gene expression atlases at unprecedented scales for the embryonic fruit fly as well as the embryonic and adult mouse already involve the analysis of hundreds of thousands of high resolution experimental images mapping mRNA expression patterns. Challenges include accurate registration of highly deformed tissues, associating cells with known anatomical regions, and identifying groups of genes whose expression is coordinately regulated with respect to both concentration and spatial location. Solutions to these and other challenges will lead to a richer understanding of the complex system aspects of gene regulation in heterogeneous tissue.'),
(91975, 2007, 'bmc', 'A mixture of feature experts approach for protein-protein interaction prediction', 'Qi, Yanjun|Klein-Seetharaman, Judith|Bar-Joseph, Ziv', 'School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. qyj@cs.cmu.edu|School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. qyj@cs.cmu.edu|School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. qyj@cs.cmu.edu', 'United States|United States|United States', 0, 'Amino Acid Sequence|Databases, Protein|Humans|Predictive Value of Tests|Protein Interaction Mapping|Saccharomyces cerevisiae', 'Comparative Study', '10.1186/1471-2105-8-S10-S6', '18269700', 'High-throughput methods can directly detect the set of interacting proteins in model species but the results are often incomplete and exhibit high false positive and false negative rates. A number of researchers have recently presented methods for integrating direct and indirect data for predicting interactions. These methods utilize a common classifier for all pairs. However, due to missing data and high redundancy among the features used, different protein pairs may benefit from different features based on the set of attributes available. In addition, in many cases it is hard to directly determine which of the data sources contributed to a prediction. This information is important for biologists using these predications in the design of new experiments.'),
(91976, 2007, 'bmc', 'Accurate splice site prediction using support vector machines', 'Sonnenburg, Sören|Schweikert, Gabriele|Philips, Petra|Behr, Jonas|Rätsch, Gunnar', 'Fraunhofer Institute FIRST, Kekuléstr, 7, 12489 Berlin, Germany. Soeren.Sonnenburg@first.fraunhofer.de|Fraunhofer Institute FIRST, Kekuléstr, 7, 12489 Berlin, Germany. Soeren.Sonnenburg@first.fraunhofer.de|Fraunhofer Institute FIRST, Kekuléstr, 7, 12489 Berlin, Germany. Soeren.Sonnenburg@first.fraunhofer.de|Fraunhofer Institute FIRST, Kekuléstr, 7, 12489 Berlin, Germany. Soeren.Sonnenburg@first.fraunhofer.de|Fraunhofer Institute FIRST, Kekuléstr, 7, 12489 Berlin, Germany. Soeren.Sonnenburg@first.fraunhofer.de', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Animals|Arabidopsis|Brassicaceae|Caenorhabditis elegans|Drosophila melanogaster|Forecasting|Genomics|Humans|Markov Chains|RNA Splice Sites|Zebrafish', 'Comparative Study', '10.1186/1471-2105-8-S10-S7', '18269701', 'For splice site recognition, one has to solve two classification problems: discriminating true from decoy splice sites for both acceptor and donor sites. Gene finding systems typically rely on Markov Chains to solve these tasks.'),
(91977, 2007, 'bmc', 'A new pairwise kernel for biological network inference with support vector machines', 'Vert, Jean-Philippe|Qiu, Jian|Noble, William S', 'Centre for Computational Biology, Ecole des Mines de Paris, 35 rue Saint-Honoré, 77300 Fontainebleau, France. Jean-Philippe.Vert@ensmp.fr|Centre for Computational Biology, Ecole des Mines de Paris, 35 rue Saint-Honoré, 77300 Fontainebleau, France. Jean-Philippe.Vert@ensmp.fr|Centre for Computational Biology, Ecole des Mines de Paris, 35 rue Saint-Honoré, 77300 Fontainebleau, France. Jean-Philippe.Vert@ensmp.fr', 'France|France|France', 0, 'Algorithms|Gene Expression Profiling|Metabolic Networks and Pathways|Models, Statistical|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Systems Biology', 'Comparative Study', '10.1186/1471-2105-8-S10-S8', '18269702', 'Much recent work in bioinformatics has focused on the inference of various types of biological networks, representing gene regulation, metabolic processes, protein-protein interactions, etc. A common setting involves inferring network edges in a supervised fashion from a set of high-confidence edges, possibly characterized by multiple, heterogeneous data sets (protein sequence, gene expression, etc.).'),
(91978, 2008, 'bmc', 'High-throughput bioinformatics with the Cyrille2 pipeline system', 'Fiers, Mark W E J|van der Burgt, Ate|Datema, Erwin|de Groot, Joost C W|van Ham, Roeland C H J', 'Applied Bioinformatics, Plant Research International, PO Box 16, 6700AA Wageningen, The Netherlands. Mark.Fiers@wur.nl|Applied Bioinformatics, Plant Research International, PO Box 16, 6700AA Wageningen, The Netherlands. Mark.Fiers@wur.nl|Applied Bioinformatics, Plant Research International, PO Box 16, 6700AA Wageningen, The Netherlands. Mark.Fiers@wur.nl|Applied Bioinformatics, Plant Research International, PO Box 16, 6700AA Wageningen, The Netherlands. Mark.Fiers@wur.nl|Applied Bioinformatics, Plant Research International, PO Box 16, 6700AA Wageningen, The Netherlands. Mark.Fiers@wur.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Computational Biology|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-96', '18269742', 'Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses are often interdependent and chained together to form complex workflows or pipelines. Given the volume of the data used and the multitude of computational resources available, specialized pipeline software is required to make high-throughput analysis of large-scale omics datasets feasible.'),
(91979, 2008, 'bmc', 'Using a logical model to predict the growth of yeast', 'Whelan, K E|King, R D', 'Department of Computer Science, Aberystwyth University, Aberystwyth, Wales, UK. knw@aber.ac.uk|Department of Computer Science, Aberystwyth University, Aberystwyth, Wales, UK. knw@aber.ac.uk', 'United Kingdom|United Kingdom', 15, 'Cell Proliferation|Computer Simulation|Logistic Models|Models, Biological|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Journal Article', '10.1186/1471-2105-9-97', '18269749', 'A logical model of the known metabolic processes in S. cerevisiae was constructed from iFF708, an existing Flux Balance Analysis (FBA) model, and augmented with information from the KEGG online pathway database. The use of predicate logic as the knowledge representation for modelling enables an explicit representation of the structure of the metabolic network, and enables logical inference techniques to be used for model identification/improvement.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91980, 2008, 'bmc', 'Statistical methodology for the analysis of dye-switch microarray experiments', 'Mary-Huard, Tristan|Aubert, Julie|Mansouri-Attia, Nadera|Sandra, Olivier|Daudin, Jean-Jacques', 'UMR AgroParisTech/INRA 518, 16, rue Claude Bernard 75231 Paris CEDEX 05, France. maryhuar@agroparistech.fr|UMR AgroParisTech/INRA 518, 16, rue Claude Bernard 75231 Paris CEDEX 05, France. maryhuar@agroparistech.fr|UMR AgroParisTech/INRA 518, 16, rue Claude Bernard 75231 Paris CEDEX 05, France. maryhuar@agroparistech.fr|UMR AgroParisTech/INRA 518, 16, rue Claude Bernard 75231 Paris CEDEX 05, France. maryhuar@agroparistech.fr|UMR AgroParisTech/INRA 518, 16, rue Claude Bernard 75231 Paris CEDEX 05, France. maryhuar@agroparistech.fr', 'France|France|France|France|France', 4, 'Algorithms|Data Interpretation, Statistical|Fluorescent Dyes|Gene Expression Profiling|In Situ Hybridization, Fluorescence|Microscopy, Fluorescence, Multiphoton|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-9-98', '18271965', 'In individually dye-balanced microarray designs, each biological sample is hybridized on two different slides, once with Cy3 and once with Cy5. While this strategy ensures an automatic correction of the gene-specific labelling bias, it also induces dependencies between log-ratio measurements that must be taken into account in the statistical analysis.'),
(91981, 2008, 'bmc', 'A perspective for biomedical data integration: design of databases for flow cytometry', 'Drakos, John|Karakantza, Marina|Zoumbos, Nicholas C|Lakoumentas, John|Nikiforidis, George C|Sakellaropoulos, George C', 'Department of Medical Physics, School of Medicine, University of Patras, GR-26504 Rion, Greece. drakos@upatras.gr|Department of Medical Physics, School of Medicine, University of Patras, GR-26504 Rion, Greece. drakos@upatras.gr|Department of Medical Physics, School of Medicine, University of Patras, GR-26504 Rion, Greece. drakos@upatras.gr|Department of Medical Physics, School of Medicine, University of Patras, GR-26504 Rion, Greece. drakos@upatras.gr|Department of Medical Physics, School of Medicine, University of Patras, GR-26504 Rion, Greece. drakos@upatras.gr|Department of Medical Physics, School of Medicine, University of Patras, GR-26504 Rion, Greece. drakos@upatras.gr', 'Greece|Greece|Greece|Greece|Greece|Greece', 5, 'Algorithms|Database Management Systems|Databases, Factual|Flow Cytometry|Information Storage and Retrieval|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-99', '18275602', 'The integration of biomedical information is essential for tackling medical problems. We describe a data model in the domain of flow cytometry (FC) allowing for massive management, analysis and integration with other laboratory and clinical information. The paper is concerned with the proper translation of the Flow Cytometry Standard (FCS) into a relational database schema, in a way that facilitates end users at either doing research on FC or studying specific cases of patients undergone FC analysis'),
(91982, 2008, 'bmc', 'Analyzing M-CSF dependent monocyte/macrophage differentiation: expression modes and meta-modes derived from an independent component analysis', 'Lutter, Dominik|Ugocsai, Peter|Grandl, Margot|Orso, Evelyn|Theis, Fabian|Lang, Elmar W|Schmitz, Gerd', 'Institute for Clinical Chemistry and Laboratory Medicine, University of Regensburg, D-93042 Regensburg, Germany. dominik.lutter@klinik.uni-regensburg.de|Institute for Clinical Chemistry and Laboratory Medicine, University of Regensburg, D-93042 Regensburg, Germany. dominik.lutter@klinik.uni-regensburg.de|Institute for Clinical Chemistry and Laboratory Medicine, University of Regensburg, D-93042 Regensburg, Germany. dominik.lutter@klinik.uni-regensburg.de|Institute for Clinical Chemistry and Laboratory Medicine, University of Regensburg, D-93042 Regensburg, Germany. dominik.lutter@klinik.uni-regensburg.de|Institute for Clinical Chemistry and Laboratory Medicine, University of Regensburg, D-93042 Regensburg, Germany. dominik.lutter@klinik.uni-regensburg.de|Institute for Clinical Chemistry and Laboratory Medicine, University of Regensburg, D-93042 Regensburg, Germany. dominik.lutter@klinik.uni-regensburg.de|Institute for Clinical Chemistry and Laboratory Medicine, University of Regensburg, D-93042 Regensburg, Germany. dominik.lutter@klinik.uni-regensburg.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 19, 'Cell Differentiation|Cytokines|Gene Expression Profiling|Macrophage Colony-Stimulating Factor|Macrophages|Meta-Analysis as Topic|Monocytes|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Signal Transduction', 'Journal Article', '10.1186/1471-2105-9-100', '18279525', 'The analysis of high-throughput gene expression data sets derived from microarray experiments still is a field of extensive investigation. Although new approaches and algorithms are published continuously, mostly conventional methods like hierarchical clustering algorithms or variance analysis tools are used. Here we take a closer look at independent component analysis (ICA) which is already discussed widely as a new analysis approach. However, deep exploration of its applicability and relevance to concrete biological problems is still missing. In this study, we investigate the relevance of ICA in gaining new insights into well characterized regulatory mechanisms of M-CSF dependent macrophage differentiation.'),
(91983, 2008, 'bmc', 'Prediction of mucin-type O-glycosylation sites in mammalian proteins using the composition of k-spaced amino acid pairs', 'Chen, Yong-Zi|Tang, Yu-Rong|Sheng, Zhi-Ya|Zhang, Ziding', 'Bioinformatics Center, College of Biological Sciences, China Agricultural University, 100094 Beijing, China. chenyongzi77@yahoo.com.cn|Bioinformatics Center, College of Biological Sciences, China Agricultural University, 100094 Beijing, China. chenyongzi77@yahoo.com.cn|Bioinformatics Center, College of Biological Sciences, China Agricultural University, 100094 Beijing, China. chenyongzi77@yahoo.com.cn|Bioinformatics Center, College of Biological Sciences, China Agricultural University, 100094 Beijing, China. chenyongzi77@yahoo.com.cn', 'China|China|China|China', 108, 'Amino Acid Motifs|Amino Acid Sequence|Animals|Artificial Intelligence|Binding Sites|Glycosylation|Humans|Mammals|Molecular Sequence Data|Mucins|Pattern Recognition, Automated|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-9-101', '18282281', 'As one of the most common protein post-translational modifications, glycosylation is involved in a variety of important biological processes. Computational identification of glycosylation sites in protein sequences becomes increasingly important in the post-genomic era. A new encoding scheme was employed to improve the prediction of mucin-type O-glycosylation sites in mammalian proteins.'),
(91984, 2008, 'bmc', 'Clustering exact matches of pairwise sequence alignments by weighted linear regression', 'González, Alvaro J|Liao, Li', 'Laboratory of Bioinformatics, Computer and Information Sciences Department, University of Delaware, 421 Smith Hall, Newark, DE 19716, USA. alvaro@cis.udel.edu|Laboratory of Bioinformatics, Computer and Information Sciences Department, University of Delaware, 421 Smith Hall, Newark, DE 19716, USA. alvaro@cis.udel.edu', 'United States|United States', 2, 'Algorithms|Cluster Analysis|Linear Models|Sequence Alignment|Software', 'Comparative Study', '10.1186/1471-2105-9-102', '18282291', 'At intermediate stages of genome assembly projects, when a number of contigs have been generated and their validity needs to be verified, it is desirable to align these contigs to a reference genome when it is available. The interest is not to analyze a detailed alignment between a contig and the reference genome at the base level, but rather to have a rough estimate of where the contig aligns to the reference genome, specifically, by identifying the starting and ending positions of such a region. This information is very useful in ordering the contigs, facilitating post-assembly analysis such as gap closure and resolving repeats. There exist programs, such as BLAST and MUMmer, that can quickly align and identify high similarity segments between two sequences, which, when seen in a dot plot, tend to agglomerate along a diagonal but can also be disrupted by gaps or shifted away from the main diagonal due to mismatches between the contig and the reference. It is a tedious and practically impossible task to visually inspect the dot plot to identify the regions covered by a large number of contigs from sequence assembly projects. A forced global alignment between a contig and the reference is not only time consuming but often meaningless.'),
(91985, 2008, 'bmc', 'Automated simultaneous analysis phylogenetics (ASAP): an enabling tool for phlyogenomics', 'Sarkar, Indra Neil|Egan, Mary G|Coruzzi, Gloria|Lee, Ernest K|DeSalle, Rob', 'MBLWHOI Library, Marine Biological Laboratory, Woods Hole, MA, USA. sarkar@mbl.edu|MBLWHOI Library, Marine Biological Laboratory, Woods Hole, MA, USA. sarkar@mbl.edu|MBLWHOI Library, Marine Biological Laboratory, Woods Hole, MA, USA. sarkar@mbl.edu|MBLWHOI Library, Marine Biological Laboratory, Woods Hole, MA, USA. sarkar@mbl.edu|MBLWHOI Library, Marine Biological Laboratory, Woods Hole, MA, USA. sarkar@mbl.edu', 'United States|United States|United States|United States|United States', 20, 'Algorithms|Base Sequence|Chromosome Mapping|Evolution, Molecular|Molecular Sequence Data|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-9-103', '18282301', 'The availability of sequences from whole genomes to reconstruct the tree of life has the potential to enable the development of phylogenomic hypotheses in ways that have not been before possible. A significant bottleneck in the analysis of genomic-scale views of the tree of life is the time required for manual curation of genomic data into multi-gene phylogenetic matrices.'),
(91986, 2008, 'bmc', 'PDTD: a web-accessible protein database for drug target identification', 'Gao, Zhenting|Li, Honglin|Zhang, Hailei|Liu, Xiaofeng|Kang, Ling|Luo, Xiaomin|Zhu, Weiliang|Chen, Kaixian|Wang, Xicheng|Jiang, Hualiang', 'Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China. zhentg@mail.shcnc.ac.cn|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China. zhentg@mail.shcnc.ac.cn|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China. zhentg@mail.shcnc.ac.cn|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China. zhentg@mail.shcnc.ac.cn|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China. zhentg@mail.shcnc.ac.cn|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China. zhentg@mail.shcnc.ac.cn|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China. zhentg@mail.shcnc.ac.cn|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China. zhentg@mail.shcnc.ac.cn|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China. zhentg@mail.shcnc.ac.cn|Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China. zhentg@mail.shcnc.ac.cn', 'China|China|China|China|China|China|China|China|China|China', 228, 'Binding Sites|Database Management Systems|Databases, Protein|Drug Delivery Systems|Drug Design|Information Storage and Retrieval|Internet|Protein Binding|Protein Conformation|Proteins|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-9-104', '18282303', 'Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D) structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (Target Fishing Docking) http://www.dddc.ac.cn/tarfisdock, which has been used widely by others. Recently, we have constructed a protein target database, Potential Drug Target Database (PDTD), and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation.'),
(91987, 2008, 'bmc', 'Piecewise multivariate modelling of sequential metabolic profiling data', 'Rantalainen, Mattias|Cloarec, Olivier|Ebbels, Timothy M D|Lundstedt, Torbjörn|Nicholson, Jeremy K|Holmes, Elaine|Trygg, Johan', 'Research Group for Chemometrics, Institute of Chemistry, Umeå University, Umeå, S-901 87, Sweden. mattias.rantalainen@imperial.ac.uk|Research Group for Chemometrics, Institute of Chemistry, Umeå University, Umeå, S-901 87, Sweden. mattias.rantalainen@imperial.ac.uk|Research Group for Chemometrics, Institute of Chemistry, Umeå University, Umeå, S-901 87, Sweden. mattias.rantalainen@imperial.ac.uk|Research Group for Chemometrics, Institute of Chemistry, Umeå University, Umeå, S-901 87, Sweden. mattias.rantalainen@imperial.ac.uk|Research Group for Chemometrics, Institute of Chemistry, Umeå University, Umeå, S-901 87, Sweden. mattias.rantalainen@imperial.ac.uk|Research Group for Chemometrics, Institute of Chemistry, Umeå University, Umeå, S-901 87, Sweden. mattias.rantalainen@imperial.ac.uk|Research Group for Chemometrics, Institute of Chemistry, Umeå University, Umeå, S-901 87, Sweden. mattias.rantalainen@imperial.ac.uk', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 22, 'Animals|Computational Biology|Computer Simulation|Data Interpretation, Statistical|Kidney Tubules, Proximal|Kinetics|Mercuric Chloride|Metabolism|Models, Biological|Models, Statistical|Multivariate Analysis|Predictive Value of Tests|Rats|Reference Values|Systems Biology|Time Factors', 'Comparative Study', '10.1186/1471-2105-9-105', '18284665', 'Modelling the time-related behaviour of biological systems is essential for understanding their dynamic responses to perturbations. In metabolic profiling studies, the sampling rate and number of sampling points are often restricted due to experimental and biological constraints.'),
(91988, 2008, 'bmc', 'K-OPLS package: kernel-based orthogonal projections to latent structures for prediction and interpretation in feature space', 'Bylesjö, Max|Rantalainen, Mattias|Nicholson, Jeremy K|Holmes, Elaine|Trygg, Johan', 'Research Group for Chemometrics, Department of Chemistry, Umeå University, Umeå, SE-901 87, Sweden. max.bylesjo@chem.umu.se|Research Group for Chemometrics, Department of Chemistry, Umeå University, Umeå, SE-901 87, Sweden. max.bylesjo@chem.umu.se|Research Group for Chemometrics, Department of Chemistry, Umeå University, Umeå, SE-901 87, Sweden. max.bylesjo@chem.umu.se|Research Group for Chemometrics, Department of Chemistry, Umeå University, Umeå, SE-901 87, Sweden. max.bylesjo@chem.umu.se|Research Group for Chemometrics, Department of Chemistry, Umeå University, Umeå, SE-901 87, Sweden. max.bylesjo@chem.umu.se', 'Sweden|Sweden|Sweden|Sweden|Sweden', 63, 'Algorithms|Computer Simulation|Models, Biological|Proteome|Signal Transduction|Software', 'Journal Article', '10.1186/1471-2105-9-106', '18284666', 'Kernel-based classification and regression methods have been successfully applied to modelling a wide variety of biological data. The Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method offers unique properties facilitating separate modelling of predictive variation and structured noise in the feature space. While providing prediction results similar to other kernel-based methods, K-OPLS features enhanced interpretational capabilities, allowing detection of unanticipated systematic variation in the data such as instrumental drift, batch variability or unexpected biological variation.'),
(91989, 2008, 'bmc', 'Fuzzy association rules for biological data analysis: a case study on yeast', 'Lopez, Francisco J|Blanco, Armando|Garcia, Fernando|Cano, Carlos|Marin, Antonio', 'Department of Computer Science and AI, University of Granada, 18071, Granada, Spain. fjavier@decsai.ugr.es|Department of Computer Science and AI, University of Granada, 18071, Granada, Spain. fjavier@decsai.ugr.es|Department of Computer Science and AI, University of Granada, 18071, Granada, Spain. fjavier@decsai.ugr.es|Department of Computer Science and AI, University of Granada, 18071, Granada, Spain. fjavier@decsai.ugr.es|Department of Computer Science and AI, University of Granada, 18071, Granada, Spain. fjavier@decsai.ugr.es', 'Spain|Spain|Spain|Spain|Spain', 30, 'Algorithms|Base Sequence|Chromosome Mapping|Databases, Genetic|Fuzzy Logic|Genome, Fungal|Molecular Sequence Data|Pattern Recognition, Automated|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-9-107', '18284669', 'Last years mapping of diverse genomes has generated huge amounts of biological data which are currently dispersed through many databases. Integration of the information available in the various databases is required to unveil possible associations relating already known data. Biological data are often imprecise and noisy. Fuzzy set theory is specially suitable to model imprecise data while association rules are very appropriate to integrate heterogeneous data.'),
(91990, 2008, 'bmc', 'MScanner: a classifier for retrieving Medline citations', 'Poulter, Graham L|Rubin, Daniel L|Altman, Russ B|Seoighe, Cathal', 'UCT NBN Node, Department of Molecular and Cell Biology, University of Cape Town, Cape Town, South Africa. graham.poulter@gmail.com|UCT NBN Node, Department of Molecular and Cell Biology, University of Cape Town, Cape Town, South Africa. graham.poulter@gmail.com|UCT NBN Node, Department of Molecular and Cell Biology, University of Cape Town, Cape Town, South Africa. graham.poulter@gmail.com|UCT NBN Node, Department of Molecular and Cell Biology, University of Cape Town, Cape Town, South Africa. graham.poulter@gmail.com', 'South Africa|South Africa|South Africa|South Africa', 43, 'Database Management Systems|Databases, Factual|Information Storage and Retrieval|Internet|MEDLINE|Medical Subject Headings|Software', 'Comparative Study', '10.1186/1471-2105-9-108', '18284683', 'Keyword searching through PubMed and other systems is the standard means of retrieving information from Medline. However, ad-hoc retrieval systems do not meet all of the needs of databases that curate information from literature, or of text miners developing a corpus on a topic that has many terms indicative of relevance. Several databases have developed supervised learning methods that operate on a filtered subset of Medline, to classify Medline records so that fewer articles have to be manually reviewed for relevance. A few studies have considered generalisation of Medline classification to operate on the entire Medline database in a non-domain-specific manner, but existing applications lack speed, available implementations, or a means to measure performance in new domains.'),
(91991, 2008, 'bmc', 'Evolutionary Pareto-optimization of stably folding peptides', 'Gronwald, Wolfram|Hohm, Tim|Hoffmann, Daniel', 'Institute for Functional Genomics, University of Regensburg, Josef-Engert-Strasse 9, 93053 Regensburg, Germany. wolfram.gronwald@klinik.uni-regensburg.de|Institute for Functional Genomics, University of Regensburg, Josef-Engert-Strasse 9, 93053 Regensburg, Germany. wolfram.gronwald@klinik.uni-regensburg.de|Institute for Functional Genomics, University of Regensburg, Josef-Engert-Strasse 9, 93053 Regensburg, Germany. wolfram.gronwald@klinik.uni-regensburg.de', 'Germany|Germany|Germany', 20, 'Amino Acid Sequence|Evolution, Molecular|Molecular Sequence Data|Neurofilament Proteins|Peptide Fragments|Peptides|Protein Folding|Protein Structure, Tertiary|Sequence Homology, Amino Acid', 'Comparative Study', '10.1186/1471-2105-9-109', '18284690', 'As a rule, peptides are more flexible and unstructured than proteins with their substantial stabilizing hydrophobic cores. Nevertheless, a few stably folding peptides have been discovered. This raises the question whether there may be more such peptides that are unknown as yet. These molecules could be helpful in basic research and medicine.'),
(91992, 2008, 'bmc', 'SPIKE--a database, visualization and analysis tool of cellular signaling pathways', 'Elkon, Ran|Vesterman, Rita|Amit, Nira|Ulitsky, Igor|Zohar, Idan|Weisz, Mali|Mass, Gilad|Orlev, Nir|Sternberg, Giora|Blekhman, Ran|Assa, Jackie|Shiloh, Yosef|Shamir, Ron', 'The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il|The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il|The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il|The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il|The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il|The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il|The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il|The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il|The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il|The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il|The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il|The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il|The David and Inez Myers Laboratory for Genetic Research, Department of Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel. ranel@post.tau.ac.il', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 47, 'Cell Physiological Phenomena|Database Management Systems|Databases, Genetic|Metabolic Networks and Pathways|Signal Transduction|Software', 'Comparative Study', '10.1186/1471-2105-9-110', '18289391', 'Biological signaling pathways that govern cellular physiology form an intricate web of tightly regulated interlocking processes. Data on these regulatory networks are accumulating at an unprecedented pace. The assimilation, visualization and interpretation of these data have become a major challenge in biological research, and once met, will greatly boost our ability to understand cell functioning on a systems level.'),
(91993, 2008, 'bmc', 'Simple integrative preprocessing preserves what is shared in data sources', 'Tripathi, Abhishek|Klami, Arto|Kaski, Samuel', 'Department of Computer Science, P,O, Box 68, FI-00014, University of Helsinki, Finland. abhishek@cs.helsinki.fi|Department of Computer Science, P,O, Box 68, FI-00014, University of Helsinki, Finland. abhishek@cs.helsinki.fi|Department of Computer Science, P,O, Box 68, FI-00014, University of Helsinki, Finland. abhishek@cs.helsinki.fi', 'Finland|Finland|Finland', 0, 'Computer Simulation|Database Management Systems|Databases, Factual|Gene Expression Profiling|Information Storage and Retrieval|Models, Biological|Systems Integration', 'Journal Article', '10.1186/1471-2105-9-111', '18291027', 'Bioinformatics data analysis toolbox needs general-purpose, fast and easily interpretable preprocessing tools that perform data integration during exploratory data analysis. Our focus is on vector-valued data sources, each consisting of measurements of the same entity but on different variables, and on tasks where source-specific variation is considered noisy or not interesting. Principal components analysis of all sources combined together is an obvious choice if it is not important to distinguish between data source-specific and shared variation. Canonical Correlation Analysis (CCA) focuses on mutual dependencies and discards source-specific noise but it produces a separate set of components for each source.'),
(91994, 2008, 'bmc', 'ReAlignerV: web-based genomic alignment tool with high specificity and robustness estimated by species-specific insertion sequences', 'Iwama, Hisakazu|Hori, Yukio|Matsumoto, Kensuke|Murao, Koji|Ishida, Toshihiko', 'Life Science Research Center, Kagawa University, Ikenobe 1750-1, Miki-cho, Kita-gun, Kagawa, 761-0793, Japan. iwama@med.kagawa-u.ac.jp|Life Science Research Center, Kagawa University, Ikenobe 1750-1, Miki-cho, Kita-gun, Kagawa, 761-0793, Japan. iwama@med.kagawa-u.ac.jp|Life Science Research Center, Kagawa University, Ikenobe 1750-1, Miki-cho, Kita-gun, Kagawa, 761-0793, Japan. iwama@med.kagawa-u.ac.jp|Life Science Research Center, Kagawa University, Ikenobe 1750-1, Miki-cho, Kita-gun, Kagawa, 761-0793, Japan. iwama@med.kagawa-u.ac.jp|Life Science Research Center, Kagawa University, Ikenobe 1750-1, Miki-cho, Kita-gun, Kagawa, 761-0793, Japan. iwama@med.kagawa-u.ac.jp', 'Japan|Japan|Japan|Japan|Japan', 0, 'Algorithms|Base Sequence|Chromosome Mapping|DNA Transposable Elements|Internet|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-9-112', '18294369', 'Detecting conserved noncoding sequences (CNSs) across species highlights the functional elements. Alignment procedures combined with computational prediction of transcription factor binding sites (TFBSs) can narrow down key regulatory elements. Repeat masking processes are often performed before alignment to mask insertion sequences such as transposable elements (TEs). However, recently such TEs have been reported to influence the gene regulatory network evolution. Therefore, an alignment approach that is robust to TE insertions is meaningful for finding novel conserved TFBSs in TEs.'),
(91995, 2008, 'bmc', 'Human Pol II promoter recognition based on primary sequences and free energy of dinucleotides', 'Yang, Jian-Yi|Zhou, Yu|Yu, Zu-Guo|Anh, Vo|Zhou, Li-Qian', 'School of Mathematics and Computational Science, Xiangtan University, Hunan 411105, China. yangjianyiapple@163.com|School of Mathematics and Computational Science, Xiangtan University, Hunan 411105, China. yangjianyiapple@163.com|School of Mathematics and Computational Science, Xiangtan University, Hunan 411105, China. yangjianyiapple@163.com|School of Mathematics and Computational Science, Xiangtan University, Hunan 411105, China. yangjianyiapple@163.com|School of Mathematics and Computational Science, Xiangtan University, Hunan 411105, China. yangjianyiapple@163.com', 'China|China|China|China|China', 0, 'Algorithms|Base Sequence|DNA Polymerase II|Entropy|Humans|Molecular Sequence Data|Pattern Recognition, Automated|Promoter Regions, Genetic|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-9-113', '18294399', 'Promoter region plays an important role in determining where the transcription of a particular gene should be initiated. Computational prediction of eukaryotic Pol II promoter sequences is one of the most significant problems in sequence analysis. Existing promoter prediction methods are still far from being satisfactory.'),
(91996, 2008, 'bmc', 'Effects of dependence in high-dimensional multiple testing problems', 'Kim, Kyung In|van de Wiel, Mark A', 'Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands. k.i.kim@tue.nl|Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands. k.i.kim@tue.nl', 'Netherlands|Netherlands', 0, 'Algorithms|Artifacts|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Statistics as Topic', 'Comparative Study', '10.1186/1471-2105-9-114', '18298808', 'We consider effects of dependence among variables of high-dimensional data in multiple hypothesis testing problems, in particular the False Discovery Rate (FDR) control procedures. Recent simulation studies consider only simple correlation structures among variables, which is hardly inspired by real data features. Our aim is to systematically study effects of several network features like sparsity and correlation strength by imposing dependence structures among variables using random correlation matrices.'),
(91997, 2008, 'bmc', 'Novel methodology for construction and pruning of quasi-median networks', 'Ayling, Sarah C|Brown, Terence A', 'Manchester Interdisciplinary Biocentre, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK. sarah.ayling@manchester.ac.uk|Manchester Interdisciplinary Biocentre, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK. sarah.ayling@manchester.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Evolution, Molecular|Humans|Molecular Sequence Data|RNA, Ribosomal, 5S|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-9-115', '18298812', 'Visualising the evolutionary history of a set of sequences is a challenge for molecular phylogenetics. One approach is to use undirected graphs, such as median networks, to visualise phylogenies where reticulate relationships such as recombination or homoplasy are displayed as cycles. Median networks contain binary representations of sequences as nodes, with edges connecting those sequences differing at one character, hypothetical ancestral nodes are invoked to generate a connected network which contains all most parsimonious trees. Quasi-median networks are a generalisation of median networks which are not restricted to binary data, although phylogenetic information contained within the multistate positions can be lost during the preprocessing of data. Where the history of a set of samples contain frequent homoplasies or recombination events quasi-median networks will have a complex topology. Graph reduction or pruning methods have been used to reduce network complexity but some of these methods are inapplicable to datasets in which recombination has occurred and others are procedurally complex and/or result in disconnected networks.'),
(91998, 2008, 'bmc', 'CWRML: representing crop wild relative conservation and use data in XML', 'Moore, Jonathan D|Kell, Shelagh P|Iriondo, Jose M|Ford-Lloyd, Brian V|Maxted, Nigel', 'Warwick HRI, University of Warwick, Wellesbourne, Warwickshire, CV35 9EF, UK. jonathan.moore@warwick.ac.uk|Warwick HRI, University of Warwick, Wellesbourne, Warwickshire, CV35 9EF, UK. jonathan.moore@warwick.ac.uk|Warwick HRI, University of Warwick, Wellesbourne, Warwickshire, CV35 9EF, UK. jonathan.moore@warwick.ac.uk|Warwick HRI, University of Warwick, Wellesbourne, Warwickshire, CV35 9EF, UK. jonathan.moore@warwick.ac.uk|Warwick HRI, University of Warwick, Wellesbourne, Warwickshire, CV35 9EF, UK. jonathan.moore@warwick.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Crops, Agricultural|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Programming Languages|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-9-116', '18298814', 'Crop wild relatives are wild species that are closely related to crops. They are valuable as potential gene donors for crop improvement and may help to ensure food security for the future. However, they are becoming increasingly threatened in the wild and are inadequately conserved, both in situ and ex situ. Information about the conservation status and utilisation potential of crop wild relatives is diverse and dispersed, and no single agreed standard exists for representing such information, yet, this information is vital to ensure these species are effectively conserved and utilised. The European Community-funded project, European Crop Wild Relative Diversity Assessment and Conservation Forum, determined the minimum information requirements for the conservation and utilisation of crop wild relatives and created the Crop Wild Relative Information System, incorporating an eXtensible Markup Language (XML) schema to aid data sharing and exchange.'),
(91999, 2008, 'bmc', 'A mixture model approach to sample size estimation in two-sample comparative microarray experiments', 'Jørstad, Tommy S|Midelfart, Herman|Bones, Atle M', 'Department of Biology, Norwegian University of Science and Technology, Høgskoleringen 5, NO-7491 Trondheim, Norway. Tommy.Jorstad@bio.ntnu.no|Department of Biology, Norwegian University of Science and Technology, Høgskoleringen 5, NO-7491 Trondheim, Norway. Tommy.Jorstad@bio.ntnu.no|Department of Biology, Norwegian University of Science and Technology, Høgskoleringen 5, NO-7491 Trondheim, Norway. Tommy.Jorstad@bio.ntnu.no', 'Norway|Norway|Norway', 0, 'Algorithms|Computer Simulation|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sample Size|Statistical Distributions', 'Comparative Study', '10.1186/1471-2105-9-117', '18298817', 'Choosing the appropriate sample size is an important step in the design of a microarray experiment, and recently methods have been proposed that estimate sample sizes for control of the False Discovery Rate (FDR). Many of these methods require knowledge of the distribution of effect sizes among the differentially expressed genes. If this distribution can be determined then accurate sample size requirements can be calculated.'),
(92000, 2008, 'bmc', 'Exon level integration of proteomics and microarray data', 'Bitton, Danny A|Okoniewski, Michaxc5x82 J|Connolly, Yvonne|Miller, Crispin J', 'Cancer Research UK, Applied Computational Biology and Bioinformatics Group, Paterson Institute for Cancer Research, The University of Manchester, Christie Hospital Site, Wilmslow Road, Manchester, M20 4BX, UK. dbitton@picr.man.ac.uk|Cancer Research UK, Applied Computational Biology and Bioinformatics Group, Paterson Institute for Cancer Research, The University of Manchester, Christie Hospital Site, Wilmslow Road, Manchester, M20 4BX, UK. dbitton@picr.man.ac.uk|Cancer Research UK, Applied Computational Biology and Bioinformatics Group, Paterson Institute for Cancer Research, The University of Manchester, Christie Hospital Site, Wilmslow Road, Manchester, M20 4BX, UK. dbitton@picr.man.ac.uk|Cancer Research UK, Applied Computational Biology and Bioinformatics Group, Paterson Institute for Cancer Research, The University of Manchester, Christie Hospital Site, Wilmslow Road, Manchester, M20 4BX, UK. dbitton@picr.man.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 26, 'Algorithms|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Peptide Mapping|Proteome|Proteomics|RNA Splice Sites|Reproducibility of Results|Sensitivity and Specificity|Systems Integration', 'Evaluation Studies', '10.1186/1471-2105-9-118', '18298841', 'Previous studies comparing quantitative proteomics and microarray data have generally found poor correspondence between the two. We hypothesised that this might in part be because the different assays were targeting different parts of the expressed genome and might therefore be subjected to confounding effects from processes such as alternative splicing.'),
(92001, 2008, 'bmc', 'High-precision high-coverage functional inference from integrated data sources', 'Linghu, Bolan|Snitkin, Evan S|Holloway, Dustin T|Gustafson, Adam M|Xia, Yu|DeLisi, Charles', 'Bioinformatics Graduate Program, Boston University, Boston, MA, 02215, USA. blinghu@bu.edu|Bioinformatics Graduate Program, Boston University, Boston, MA, 02215, USA. blinghu@bu.edu|Bioinformatics Graduate Program, Boston University, Boston, MA, 02215, USA. blinghu@bu.edu|Bioinformatics Graduate Program, Boston University, Boston, MA, 02215, USA. blinghu@bu.edu|Bioinformatics Graduate Program, Boston University, Boston, MA, 02215, USA. blinghu@bu.edu|Bioinformatics Graduate Program, Boston University, Boston, MA, 02215, USA. blinghu@bu.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Database Management Systems|Databases, Protein|Pattern Recognition, Automated|Reproducibility of Results|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sensitivity and Specificity|Systems Integration', 'Journal Article', '10.1186/1471-2105-9-119', '18298847', 'Information obtained from diverse data sources can be combined in a principled manner using various machine learning methods to increase the reliability and range of knowledge about protein function. The result is a weighted functional linkage network (FLN) in which linked neighbors share at least one function with high probability. Precision is, however, low. Aiming to provide precise functional annotation for as many proteins as possible, we explore and propose a two-step framework for functional annotation (1) construction of a high-coverage and reliable FLN via machine learning techniques (2) development of a decision rule for the constructed FLN to optimize functional annotation.'),
(92002, 2008, 'bmc', 'A Bayesian method for calculating real-time quantitative PCR calibration curves using absolute plasmid DNA standards', 'Sivaganesan, Mano|Seifring, Shawn|Varma, Manju|Haugland, Richard A|Shanks, Orin C', 'U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 26 West Martin Luther King Drive, Cincinnati, OH 45268, USA. sivaganesan.mano@epa.gov|U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 26 West Martin Luther King Drive, Cincinnati, OH 45268, USA. sivaganesan.mano@epa.gov|U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 26 West Martin Luther King Drive, Cincinnati, OH 45268, USA. sivaganesan.mano@epa.gov|U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 26 West Martin Luther King Drive, Cincinnati, OH 45268, USA. sivaganesan.mano@epa.gov|U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 26 West Martin Luther King Drive, Cincinnati, OH 45268, USA. sivaganesan.mano@epa.gov', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Base Sequence|Bayes Theorem|Calibration|Molecular Sequence Data|Pattern Recognition, Automated|Plasmids|Reverse Transcriptase Polymerase Chain Reaction|Sequence Analysis, DNA|United States', 'Journal Article', '10.1186/1471-2105-9-120', '18298858', 'In real-time quantitative PCR studies using absolute plasmid DNA standards, a calibration curve is developed to estimate an unknown DNA concentration. However, potential differences in the amplification performance of plasmid DNA compared to genomic DNA standards are often ignored in calibration calculations and in some cases impossible to characterize. A flexible statistical method that can account for uncertainty between plasmid and genomic DNA targets, replicate testing, and experiment-to-experiment variability is needed to estimate calibration curve parameters such as intercept and slope. Here we report the use of a Bayesian approach to generate calibration curves for the enumeration of target DNA from genomic DNA samples using absolute plasmid DNA standards.'),
(92003, 2008, 'bmc', 'SciDBMaker: new software for computer-aided design of specialized biological databases', 'Hammami, Riadh|Zouhir, Abdelmajid|Naghmouchi, Karim|Ben Hamida, Jeannette|Fliss, Ismail', 'Unité de Protéomie Fonctionnelle & Biopréservation Alimentaire, Institut Supérieur des Sciences Biologiques Appliquées de Tunis, Université El Manar, Tunisie. Riadh.hammami@fst.rnu.tn|Unité de Protéomie Fonctionnelle & Biopréservation Alimentaire, Institut Supérieur des Sciences Biologiques Appliquées de Tunis, Université El Manar, Tunisie. Riadh.hammami@fst.rnu.tn|Unité de Protéomie Fonctionnelle & Biopréservation Alimentaire, Institut Supérieur des Sciences Biologiques Appliquées de Tunis, Université El Manar, Tunisie. Riadh.hammami@fst.rnu.tn|Unité de Protéomie Fonctionnelle & Biopréservation Alimentaire, Institut Supérieur des Sciences Biologiques Appliquées de Tunis, Université El Manar, Tunisie. Riadh.hammami@fst.rnu.tn|Unité de Protéomie Fonctionnelle & Biopréservation Alimentaire, Institut Supérieur des Sciences Biologiques Appliquées de Tunis, Université El Manar, Tunisie. Riadh.hammami@fst.rnu.tn', '-|-|-|-|-', 15, 'Algorithms|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Molecular Biology|Software|Software Design', 'Journal Article', '10.1186/1471-2105-9-121', '18298861', 'The exponential growth of research in molecular biology has brought concomitant proliferation of databases for stocking its findings. A variety of protein sequence databases exist. While all of these strive for completeness, the range of user interests is often beyond their scope. Large databases covering a broad range of domains tend to offer less detailed information than smaller, more specialized resources, often creating a need to combine data from many sources in order to obtain a complete picture. Scientific researchers are continually developing new specific databases to enhance their understanding of biological processes.'),
(92004, 2008, 'bmc', 'Strategies for measuring evolutionary conservation of RNA secondary structures', 'Gruber, Andreas R|Bernhart, Stephan H|Hofacker, Ivo L|Washietl, Stefan', 'Institute for Theoretical Chemistry, University of Vienna, Währingerstrasse 17, 1090 Wien, Austria. agruber@tbi.univie.ac.at|Institute for Theoretical Chemistry, University of Vienna, Währingerstrasse 17, 1090 Wien, Austria. agruber@tbi.univie.ac.at|Institute for Theoretical Chemistry, University of Vienna, Währingerstrasse 17, 1090 Wien, Austria. agruber@tbi.univie.ac.at|Institute for Theoretical Chemistry, University of Vienna, Währingerstrasse 17, 1090 Wien, Austria. agruber@tbi.univie.ac.at', 'Austria|Austria|Austria|Austria', 0, 'Algorithms|Base Pair Mismatch|Base Sequence|Conserved Sequence|Evolution, Molecular|Molecular Sequence Data|RNA|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1186/1471-2105-9-122', '18302738', 'Evolutionary conservation of RNA secondary structure is a typical feature of many functional non-coding RNAs. Since almost all of the available methods used for prediction and annotation of non-coding RNA genes rely on this evolutionary signature, accurate measures for structural conservation are essential.'),
(92005, 2008, 'bmc', 'Assessment of composite motif discovery methods', 'Klepper, Kjetil|Sandve, Geir K|Abul, Osman|Johansen, Jostein|Drablos, Finn', 'Department of Cancer Reasearch and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. kjetil.klepper@ntnu.no|Department of Cancer Reasearch and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. kjetil.klepper@ntnu.no|Department of Cancer Reasearch and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. kjetil.klepper@ntnu.no|Department of Cancer Reasearch and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. kjetil.klepper@ntnu.no|Department of Cancer Reasearch and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. kjetil.klepper@ntnu.no', 'Norway|Norway|Norway|Norway|Norway', 40, 'Algorithms|Amino Acid Motifs|Base Sequence|Binding Sites|DNA|Molecular Sequence Data|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1186/1471-2105-9-123', '18302777', 'Computational discovery of regulatory elements is an important area of bioinformatics research and more than a hundred motif discovery methods have been published. Traditionally, most of these methods have addressed the problem of single motif discovery - discovering binding motifs for individual transcription factors. In higher organisms, however, transcription factors usually act in combination with nearby bound factors to induce specific regulatory behaviours. Hence, recent focus has shifted from single motifs to the discovery of sets of motifs bound by multiple cooperating transcription factors, so called composite motifs or cis-regulatory modules. Given the large number and diversity of methods available, independent assessment of methods becomes important. Although there have been several benchmark studies of single motif discovery, no similar studies have previously been conducted concerning composite motif discovery.'),
(92006, 2008, 'bmc', 'A gene pattern mining algorithm using interchangeable gene sets for prokaryotes', 'Hu, Meng|Choi, Kwangmin|Su, Wei|Kim, Sun|Yang, Jiong', 'EECS, Case Western Reserve University, Cleveland, OH 44106 USA. meng.hu@case.edu|EECS, Case Western Reserve University, Cleveland, OH 44106 USA. meng.hu@case.edu|EECS, Case Western Reserve University, Cleveland, OH 44106 USA. meng.hu@case.edu|EECS, Case Western Reserve University, Cleveland, OH 44106 USA. meng.hu@case.edu|EECS, Case Western Reserve University, Cleveland, OH 44106 USA. meng.hu@case.edu', 'United States|United States|United States|United States|United States', 2, 'Algorithms|Base Sequence|Chromosome Mapping|Databases, Genetic|Information Storage and Retrieval|Molecular Sequence Data|Multigene Family|Pattern Recognition, Automated|Prokaryotic Cells|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-9-124', '18302784', 'Mining gene patterns that are common to multiple genomes is an important biological problem, which can lead us to novel biological insights. When family classification of genes is available, this problem is similar to the pattern mining problem in the data mining community. However, when family classification information is not available, mining gene patterns is a challenging problem. There are several well developed algorithms for predicting gene patterns in a pair of genomes, such as FISH and DAGchainer. These algorithms use the optimization problem formulation which is solved using the dynamic programming technique. Unfortunately, extending these algorithms to multiple genome cases is not trivial due to the rapid increase in time and space complexity.');
