INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71550, 2004, 'bio', 'Exploiting conserved structure for faster annotation of non-coding RNAs without loss of accuracy', 'Weinberg, Zasha|Ruzzo, Walter L', 'Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA. zasha@cs.washington.edu|Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA. zasha@cs.washington.edu', 'United States|United States', 25, 'Algorithms|Chromosome Mapping|Conserved Sequence|Markov Chains|Pattern Recognition, Automated|RNA, Untranslated|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1093/bioinformatics/bth925', '15262817', 'Non-coding RNAs (ncRNAs)-functional RNA molecules not coding for proteins-are grouped into hundreds of families of homologs. To find new members of an ncRNA gene family in a large genome database, covariance models (CMs) are a useful statistical tool, as they use both sequence and RNA secondary structure information. Unfortunately, CM searches are slow. Previously, we introduced rigorous filters, which provably sacrifice none of CMs accuracy, although often scanning much faster. A rigorous filter, using a profile hidden Markov model (HMM), is built based on the CM, and filters the genome database, eliminating sequences that provably could not be annotated as homologs. The CM is run only on the remainder. Some biologically important ncRNA families could not be scanned efficiently with this technique, largely due to the significance of conserved secondary structure relative to primary sequence in identifying these families. Current heuristic filters are also expected to perform poorly on such families.'),
(71551, 2004, 'bio', 'Filtering erroneous protein annotation', 'Wieser, D|Kretschmann, E|Apweiler, R', 'Sequence Database Group, European Bioinformatics Institute, Cambridge, UK.|Sequence Database Group, European Bioinformatics Institute, Cambridge, UK.|Sequence Database Group, European Bioinformatics Institute, Cambridge, UK.', 'United Kingdom|United Kingdom|United Kingdom', 10, 'Algorithms|Amino Acid Sequence|Databases, Protein|Documentation|Information Storage and Retrieval|Molecular Sequence Data|Proteins|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth938', '15262818', 'Automatically generated annotation on protein data of UniProt (Universal Protein Resource) is planned to be publicly available on the UniProt web pages in April 2004. It is expected that the data content of over 500,000 protein entries in the TrEMBL section will be enhanced by the output of an automated annotation pipeline. However, a part of the automatically added data will be erroneous, as are parts of the information coming from other sources. We present a post-processing system called Xanthippe that is based on a simple exclusion mechanism and a decision tree approach using the C4.5 data-mining algorithm.'),
(71552, 2004, 'bio', 'Reconstructing phylogeny by quadratically approximated maximum likelihood', 'Woodhams, M D|Hendy, M D', 'Allan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North, New Zealand. m.d.woodhams@massey.ac.nz|Allan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North, New Zealand. m.d.woodhams@massey.ac.nz', 'New Zealand|New Zealand', 4, 'Algorithms|Chromosome Mapping|Computer Simulation|Evolution, Molecular|Likelihood Functions|Models, Genetic|Models, Statistical|Phylogeny|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bth926', '15262819', 'Maximum likelihood (ML) for phylogenetic inference from sequence data remains a method of choice, but has computational limitations. In particular, it cannot be applied for a global search through all potential trees when the number of taxa is large, and hence a heuristic restriction in the search space is required. In this paper, we derive a quadratic approximation, QAML, to the likelihood function whose maximum is easily determined for a given tree. The derivation depends on Hadamard conjugation, and hence is limited to the simple symmetric models of Kimura and of Jukes and Cantor. Preliminary testing has demonstrated the accuracy of QAML is close to that of ML.'),
(71553, 2004, 'bio', 'Using MoBIoS scalable genome join to find conserved primer pair candidates between two genomes', 'Xu, Weijia|Briggs, Willard J|Padolina, Joanna|Timme, Ruth E|Liu, Wenguo|Linder, C Randal|Miranker, Daniel P', 'Department of Computer Sciences, University of Texas at Austin, Austin, TX 78741, USA.|Department of Computer Sciences, University of Texas at Austin, Austin, TX 78741, USA.|Department of Computer Sciences, University of Texas at Austin, Austin, TX 78741, USA.|Department of Computer Sciences, University of Texas at Austin, Austin, TX 78741, USA.|Department of Computer Sciences, University of Texas at Austin, Austin, TX 78741, USA.|Department of Computer Sciences, University of Texas at Austin, Austin, TX 78741, USA.|Department of Computer Sciences, University of Texas at Austin, Austin, TX 78741, USA.', 'United States|United States|United States|United States|United States|United States|United States', 13, 'Arabidopsis|Chromosome Mapping|Conserved Sequence|DNA Primers|Genome, Plant|Oryza|Polymerase Chain Reaction|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth929', '15262820', 'For the purpose of identifying evolutionary reticulation events in flowering plants, we determine a large number of paired, conserved DNA oligomers that may be used as primers to amplify orthologous DNA regions using the polymerase chain reaction (PCR).'),
(71554, 2004, 'bio', 'Protein network inference from multiple genomic data: a supervised approach', 'Yamanishi, Y|Vert, J-P|Kanehisa, M', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan. yoshi@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan. yoshi@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan. yoshi@kuicr.kyoto-u.ac.jp', 'Japan|Japan|Japan', 140, 'Artificial Intelligence|Chromosome Mapping|Databases, Genetic|Gene Expression Profiling|Models, Biological|Protein Interaction Mapping|Proteome|Saccharomyces cerevisiae Proteins|Signal Transduction|Systems Integration', 'Evaluation Studies', '10.1093/bioinformatics/bth910', '15262821', 'An increasing number of observations support the hypothesis that most biological functions involve the interactions between many proteins, and that the complexity of living systems arises as a result of such interactions. In this context, the problem of inferring a global protein network for a given organism, using all available genomic data about the organism, is quickly becoming one of the main challenges in current computational biology.'),
(71555, 2004, 'bio', 'A two-stage classifier for identification of protein-protein interface residues', 'Yan, Changhui|Dobbs, Drena|Honavar, Vasant', 'Artificial Intelligence Research Laboratory, Iowa State University, Ames, IA, 50010, USA. chhyan@iastate.edu|Artificial Intelligence Research Laboratory, Iowa State University, Ames, IA, 50010, USA. chhyan@iastate.edu|Artificial Intelligence Research Laboratory, Iowa State University, Ames, IA, 50010, USA. chhyan@iastate.edu', 'United States|United States|United States', 33, 'Amino Acid Sequence|Amino Acids|Binding Sites|Computer Simulation|Models, Chemical|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth920', '15262822', 'The ability to identify protein-protein interaction sites and to detect specific amino acid residues that contribute to the specificity and affinity of protein interactions has important implications for problems ranging from rational drug design to analysis of metabolic and signal transduction networks.'),
(71556, 2004, 'bio', 'IMGT/JunctionAnalysis: the first tool for the analysis of the immunoglobulin and T cell receptor complex V-J and V-D-J JUNCTIONs', 'Yousfi Monod, Mehdi|Giudicelli, Véronique|Chaume, Denys|Lefranc, Marie-Paule', 'Laboratoire dImmunoGénétique Moléculaire LIGM, Université Montpellier II, UPR CNRS 1142, Institut de Génétique Humaine IGH, Montpellier Cedex 5, France.|Laboratoire dImmunoGénétique Moléculaire LIGM, Université Montpellier II, UPR CNRS 1142, Institut de Génétique Humaine IGH, Montpellier Cedex 5, France.|Laboratoire dImmunoGénétique Moléculaire LIGM, Université Montpellier II, UPR CNRS 1142, Institut de Génétique Humaine IGH, Montpellier Cedex 5, France.|Laboratoire dImmunoGénétique Moléculaire LIGM, Université Montpellier II, UPR CNRS 1142, Institut de Génétique Humaine IGH, Montpellier Cedex 5, France.', 'France|France|France|France', 227, 'Algorithms|Base Sequence|Gene Rearrangement, T-Lymphocyte|Genes, Immunoglobulin|Genetic Variation|Immunoglobulin Joining Region|Immunoglobulins|Molecular Sequence Data|Receptors, Antigen, T-Cell|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth945', '15262823', 'To create the enormous diversity of 10(12) immunoglobulins (IG) and T cell receptors (TR) per individual, very complex mechanisms occur at the DNA level: the combinatorial diversity results from the junction of the variable (V), diversity (D) and joining (J) genes, the N-diversity represents the addition at random of nucleotides not encoded in the genome, and somatic hypermutations occur in IG rearranged sequences. The accurate annotation of the junction between V, D, J genes in rearranged IG and TR sequences represents therefore a huge challenge by its uniqueness and complexity. We developed IMGT/JunctionAnalysis to analyse automatically in detail the IG and TR junctions, according to the IMGT Scientific chart rules, based on the IMGT-ONTOLOGY concepts.'),
(71557, 2004, 'bio', 'Predicting protein folding pathways', 'Zaki, Mohammed J|Nadimpally, Vinay|Bardhan, Deb|Bystroff, Chris', 'Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. zaki@cs.rpi.edu|Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. zaki@cs.rpi.edu|Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. zaki@cs.rpi.edu|Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. zaki@cs.rpi.edu', 'United States|United States|United States|United States', 18, 'Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Conformation|Protein Conformation|Protein Folding|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth935', '15262824', 'A structured folding pathway, which is a time ordered sequence of folding events, plays an important role in the protein folding process and hence, in the conformational search. Pathway prediction, thus gives more insight into the folding process and is a valuable guiding tool to search the conformation space. In this paper, we propose a novel unfolding approach to predict the folding pathway. We apply graph-based methods on a weighted secondary structure graph of a protein to predict the sequence of unfolding events. When viewed in reverse this yields the folding pathway. We demonstrate the success of our approach on several proteins whose pathway is partially known.'),
(71558, 2004, 'bio', 'EC_oligos: automated and whole-genome primer design for exons within one or between two genomes', 'Liu, Shaolin|Tinker, Nicholas A|Molnar, Stephen J|Mather, Diane E', 'Department of Plant Science, McGill University, Ste-Anne-de-Bellevue, Montreal, QC, Canada.|Department of Plant Science, McGill University, Ste-Anne-de-Bellevue, Montreal, QC, Canada.|Department of Plant Science, McGill University, Ste-Anne-de-Bellevue, Montreal, QC, Canada.|Department of Plant Science, McGill University, Ste-Anne-de-Bellevue, Montreal, QC, Canada.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Chromosome Mapping|Conserved Sequence|DNA Primers|Exons|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/bth413', '15271776', 'EC_oligos designs oligonucleotides (oligos) from exons of annotated genomic sequence information. It can automatically and rapidly select oligos that are conserved between two sets of sequence data, and can pair up oligos for use as PCR primers. It can do this on a whole-genome scale and according to user-defined criteria.'),
(71559, 2004, 'bio', 'SelSim: a program to simulate population genetic data with natural selection and recombination', 'Spencer, Chris C A|Coop, Graham', 'Department of Statistics, 1 South Parks Road, Oxford OX1 3TG, UK. spencer@stats.ox.ac.uk <spencer@stats.ox.ac.uk>|Department of Statistics, 1 South Parks Road, Oxford OX1 3TG, UK. spencer@stats.ox.ac.uk <spencer@stats.ox.ac.uk>', 'United Kingdom|United Kingdom', 93, 'Animals|Biological Evolution|Computer Simulation|Genetic Variation|Genetics, Population|Humans|Models, Genetic|Models, Statistical|Recombination, Genetic|Selection, Genetic|Software', 'Journal Article', '10.1093/bioinformatics/bth417', '15271777', 'SelSim is a program for Monte Carlo simulation of DNA polymorphism data for a recombining region within which a single bi-allelic site has experienced natural selection. SelSim allows simulation from either a fully stochastic model of, or deterministic approximations to, natural selection within a coalescent framework. A number of different mutation models are available for simulating surrounding neutral variation. The package enables a detailed exploration of the effects of different models and strengths of selection on patterns of diversity. This provides a tool for the statistical analysis of both empirical data and methods designed to detect natural selection.'),
(71560, 2004, 'bio', 'Microarray Data Analysis Toolbox (MDAT): for normalization, adjustment and analysis of gene expression data', 'Knowlton, Nicholas|Dozmorov, Igor M|Centola, Michael', 'Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, 825 NE 13 Street, RP Rm 461 MS: 58, Oklahoma City, OK 73104, USA. knowltonn@omrf.ouhsc.edu <knowltonn@omrf.ouhsc.edu>|Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, 825 NE 13 Street, RP Rm 461 MS: 58, Oklahoma City, OK 73104, USA. knowltonn@omrf.ouhsc.edu <knowltonn@omrf.ouhsc.edu>|Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, 825 NE 13 Street, RP Rm 461 MS: 58, Oklahoma City, OK 73104, USA. knowltonn@omrf.ouhsc.edu <knowltonn@omrf.ouhsc.edu>', 'United States|United States|United States', 23, 'Algorithms|Data Interpretation, Statistical|Gene Expression Profiling|Internet|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth424', '15271778', 'We introduce a novel Matlab toolbox for microarray data analysis. This toolbox uses normalization based upon a normally distributed background and differential gene expression based on five statistical measures. The objects in this toolbox are open source and can be implemented to suit your application.'),
(71561, 2004, 'bio', 'Data exploration tools for the Gene Ontology database', 'Shoop, Elizabeth|Casaes, Paulo|Onsongo, Getiria|Lesnett, Lisa|Petursdottir, Erla Osk|Donkor, Edward Kofi Yeboah|Tkach, Dennis|Cosimini, Michael', 'Mathematics and Computer Science Department, Macalester College, 1600 Grand Avenue, Saint Paul, MN 55105, USA. shoop@macalester.edu|Mathematics and Computer Science Department, Macalester College, 1600 Grand Avenue, Saint Paul, MN 55105, USA. shoop@macalester.edu|Mathematics and Computer Science Department, Macalester College, 1600 Grand Avenue, Saint Paul, MN 55105, USA. shoop@macalester.edu|Mathematics and Computer Science Department, Macalester College, 1600 Grand Avenue, Saint Paul, MN 55105, USA. shoop@macalester.edu|Mathematics and Computer Science Department, Macalester College, 1600 Grand Avenue, Saint Paul, MN 55105, USA. shoop@macalester.edu|Mathematics and Computer Science Department, Macalester College, 1600 Grand Avenue, Saint Paul, MN 55105, USA. shoop@macalester.edu|Mathematics and Computer Science Department, Macalester College, 1600 Grand Avenue, Saint Paul, MN 55105, USA. shoop@macalester.edu|Mathematics and Computer Science Department, Macalester College, 1600 Grand Avenue, Saint Paul, MN 55105, USA. shoop@macalester.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 9, 'Algorithms|Database Management Systems|Databases, Genetic|Documentation|Information Storage and Retrieval|Internet|Natural Language Processing|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth425', '15271779', 'To improve the ability of biologists (both researchers and students) to ask biologically interesting questions of the Gene Ontology (GO) database and to explore the ontologies by seeing large portions of the ontology graphs in context, along with details of individual terms in the ontologies.'),
(71562, 2004, 'bio', 'A probabilistic measure for alignment-free sequence comparison', 'Pham, Tuan D|Zuegg, Johannes', 'School of Computing and Information Technology, Griffith University, Nathan Campus, QLD 4111, Australia. t.pham@griffith.edu.au <t.pham@griffith.edu.au>|School of Computing and Information Technology, Griffith University, Nathan Campus, QLD 4111, Australia. t.pham@griffith.edu.au <t.pham@griffith.edu.au>', 'Australia|Australia', 84, 'Algorithms|Computer Simulation|Escherichia coli|Models, Genetic|Models, Statistical|Operon|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Shigella flexneri|Threonine', 'Comparative Study', '10.1093/bioinformatics/bth426', '15271780', 'Alignment-free sequence comparison methods are still in the early stages of development compared to those of alignment-based sequence analysis. In this paper, we introduce a probabilistic measure of similarity between two biological sequences without alignment. The method is based on the concept of comparing the similarity/dissimilarity between two constructed Markov models.'),
(71563, 2004, 'bio', 'ORFcurator: molecular curation of genes and gene clusters in prokaryotic organisms', 'Rosenfeld, Jeffrey A|Sarkar, Indra N|Planet, Paul J|Figurski, David H|DeSalle, Rob', 'Division of Invertebrate Zoology, Central Park West, 79th Street, American Museum of Natural History, New York, NY 10024, USA.|Division of Invertebrate Zoology, Central Park West, 79th Street, American Museum of Natural History, New York, NY 10024, USA.|Division of Invertebrate Zoology, Central Park West, 79th Street, American Museum of Natural History, New York, NY 10024, USA.|Division of Invertebrate Zoology, Central Park West, 79th Street, American Museum of Natural History, New York, NY 10024, USA.|Division of Invertebrate Zoology, Central Park West, 79th Street, American Museum of Natural History, New York, NY 10024, USA.', 'United States|United States|United States|United States|United States', 9, 'Algorithms|Chromosome Mapping|Conserved Sequence|Databases, Genetic|Genome, Bacterial|Internet|Multigene Family|Open Reading Frames|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth427', '15271781', 'The ability to detect clusters of functionally related genes in multiple microbial genomes has enormous potential for enhancing studies on gene function and microbial evolution. The staggering amount of new genome sequence data presents a largely untapped resource for gene cluster discovery. To date, gene cluster analysis has not been fully automated, and one must rely on manual, tedious and time-consuming manipulation of sequences. To facilitate accurate and rapid identification of conserved gene clusters, we developed a database-driven web application, called ORFcurator. We used ORFcurator to find clusters containing any genes similar to those of the 14-gene Widespread Colonization Island of Actinobacillus actinomycetemcomitans. From 126 genomes, ORFcurator identified all 73 clusters previously determined by manual searching.'),
(71564, 2004, 'bio', 'GeneNetwork: an interactive tool for reconstruction of genetic networks using microarray data', 'Wu, Chia-Chin|Huang, Hsuan-Cheng|Juan, Hsueh-Fen|Chen, Shui-Tein', 'Institute of Biological Chemistry and Genomics Research Center, Academia Sinica, Taipei, Taiwan.|Institute of Biological Chemistry and Genomics Research Center, Academia Sinica, Taipei, Taiwan.|Institute of Biological Chemistry and Genomics Research Center, Academia Sinica, Taipei, Taiwan.|Institute of Biological Chemistry and Genomics Research Center, Academia Sinica, Taipei, Taiwan.', '-|-|-|-', 41, 'Algorithms|Computer Graphics|Computer Simulation|Gene Expression Profiling|Models, Genetic|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth428', '15271782', 'Inferring genetic network architecture from time series data generated from high-throughput experimental technologies, such as cDNA microarray, can help us to understand the system behavior of living organisms. We have developed an interactive tool, GeneNetwork, which provides four reverse engineering models and three data interpolation approaches to infer relationships between genes. GeneNetwork enables a user to readily reconstruct genetic networks based on microarray data without having intimate knowledge of the mathematical models. A simple graphical user interface enables rapid, intuitive mapping and analysis of the reconstructed network allowing biologists to explore gene relationships at the system level.'),
(71565, 2004, 'bio', 'ViTO: tool for refinement of protein sequence-structure alignments', 'Catherinot, Vincent|Labesse, Gilles', 'Centre de Biochimie Structurale, INSERM U414, CNRS UMR5048, Université Montpellier 1 15, Avenue Charles Flahault 34060 Montpellier Cedex, France. catrino@cbs.cnrs.fr <catrino@cbs.cnrs.fr>|Centre de Biochimie Structurale, INSERM U414, CNRS UMR5048, Université Montpellier 1 15, Avenue Charles Flahault 34060 Montpellier Cedex, France. catrino@cbs.cnrs.fr <catrino@cbs.cnrs.fr>', 'France|France', 46, 'Amino Acid Sequence|Computer Graphics|Imaging, Three-Dimensional|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth429', '15271783', 'ViTO is a graphical application, including an editor, of multiple sequence alignment and a three-dimensional (3D) structure viewer. It is possible to manipulate alignments containing hundreds of sequences and to display a dozen structures. ViTO can handle so-called multiparts alignments to allow the visualization of complex structures (multi-chain proteins and/or small molecules and DNA) and the editing of the corresponding alignment. The 3D viewer and the alignment editor are connected together allowing rapid refinement of sequence-structure alignment by taking advantage of the immediate visualization of resulting insertions/deletions and strict conservations in their structural context. More generally, it allows the mapping of informations about the sequence conservation extracted from the alignment onto the 3D structures in a dynamic way. ViTO is also connected to two comparative modelling programs, SCWRL and MODELLER. These features make ViTO a powerful tool to characterize protein families and to optimize the alignments for comparative modelling.'),
(71566, 2004, 'bio', 'Systematic analysis of snake neurotoxins functional classification using a data warehousing approach', 'Siew, Joyce Phui Yee|Khan, Asif M|Tan, Paul T J|Koh, Judice L Y|Seah, Seng Hong|Koo, Chuay Yeng|Chai, Siaw Ching|Armugam, Arunmozhiarasi|Brusic, Vladimir|Jeyaseelan, Kandiah', 'Department of Biochemistry, Faculty of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597.|Department of Biochemistry, Faculty of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597.|Department of Biochemistry, Faculty of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597.|Department of Biochemistry, Faculty of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597.|Department of Biochemistry, Faculty of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597.|Department of Biochemistry, Faculty of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597.|Department of Biochemistry, Faculty of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597.|Department of Biochemistry, Faculty of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597.|Department of Biochemistry, Faculty of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597.|Department of Biochemistry, Faculty of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 12, 'Animals|Database Management Systems|Databases, Bibliographic|Databases, Protein|Documentation|Information Storage and Retrieval|Natural Language Processing|Neurotoxins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Snake Venoms|Snakes|Systems Integration', 'Journal Article', '10.1093/bioinformatics/bth430', '15271784', 'Sequence annotations, functional and structural data on snake venom neurotoxins (svNTXs) are scattered across multiple databases and literature sources. Sequence annotations and structural data are available in the public molecular databases, while functional data are almost exclusively available in the published articles. There is a need for a specialized svNTXs database that contains NTX entries, which are organized, well annotated and classified in a systematic manner.'),
(71567, 2004, 'bio', 'PCOAT: positional correlation analysis using multiple methods', 'Qi, Yuan|Grishin, Nick V', 'Department of Biochemistry, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-9050, USA.|Department of Biochemistry, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-9050, USA.', 'United States|United States', 5, 'Algorithms|Evolution, Molecular|Models, Molecular|Models, Statistical|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Statistics as Topic|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bth431', '15271785', 'PCOAT (Positional COrrelation Analysis Tool) is a program to perform positional correlation analysis for protein multiple sequence alignment in order to identify structurally or functionally important interactions between positions in a protein family. We implement different statistical methods to detect highly correlated position pairs, amino acid pairs, individual positions and networks of correlated positions, and utilize multiple sequence weighting and sampling methods to eliminate background correlations caused by phylogeny and stochastic events. Our program runs relatively fast and is suitable for analyzing alignments containing large number of sequences.'),
(71568, 2004, 'bio', 'the JigCell model builder and run manager', 'Vass, Marc|Allen, Nicholas|Shaffer, Clifford A|Ramakrishnan, Naren|Watson, Layne T|Tyson, John J', 'Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0106, USA.|Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0106, USA.|Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0106, USA.|Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0106, USA.|Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0106, USA.|Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0106, USA.', 'United States|United States|United States|United States|United States|United States', 29, 'Animals|Computer Simulation|Database Management Systems|Gene Expression Regulation|Humans|Information Storage and Retrieval|Models, Biological|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth422', '15273159', 'We describe the JigCell Model Builder (JCMB), a tool for creating biochemical reaction network models. JCMB is designed for ease of use and its interface uses the standard spreadsheet metaphor. The JigCell Run Manager (JCRM) is a tool for organizing the large collections of simulation runs typically required by reaction network modeling activities.'),
(71569, 2004, 'bio', 'Discovering patterns to extract protein-protein interactions from full texts', 'Huang, Minlie|Zhu, Xiaoyan|Hao, Yu|Payan, Donald G|Qu, Kunbin|Li, Ming', 'State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, University of Tsinghua, Beijing, 100084, China.|State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, University of Tsinghua, Beijing, 100084, China.|State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, University of Tsinghua, Beijing, 100084, China.|State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, University of Tsinghua, Beijing, 100084, China.|State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, University of Tsinghua, Beijing, 100084, China.|State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, University of Tsinghua, Beijing, 100084, China.', 'China|China|China|China|China|China', 164, 'Algorithms|Artificial Intelligence|Database Management Systems|Databases, Bibliographic|Information Storage and Retrieval|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Protein Interaction Mapping|Proteins|Software|Vocabulary, Controlled', 'Comparative Study', '10.1093/bioinformatics/bth451', '15284092', 'Although there are several databases storing protein-protein interactions, most such data still exist only in the scientific literature. They are scattered in scientific literature written in natural languages, defying data mining efforts. Much time and labor have to be spent on extracting protein pathways from literature. Our aim is to develop a robust and powerful methodology to mine protein-protein interactions from biomedical texts.'),
(71570, 2004, 'bio', 'NMRb: a web-site repository for raw NMR datasets', 'Pons, J L|Malliavin, T E|Tramesel, D|Delsuc, M A', 'Centre de Biochimie Structurale UMR 5048, UMR 554, UM1, 15 avenue Charles Flahault, F-34090 Montpellier, France.|Centre de Biochimie Structurale UMR 5048, UMR 554, UM1, 15 avenue Charles Flahault, F-34090 Montpellier, France.|Centre de Biochimie Structurale UMR 5048, UMR 554, UM1, 15 avenue Charles Flahault, F-34090 Montpellier, France.|Centre de Biochimie Structurale UMR 5048, UMR 554, UM1, 15 avenue Charles Flahault, F-34090 Montpellier, France.', 'France|France|France|France', 4, 'Database Management Systems|Databases, Protein|Information Dissemination|Information Storage and Retrieval|Internet|Magnetic Resonance Spectroscopy|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth450', '15284093', 'The development of NMR in structural proteomics requires the availability of automatic structure determination methods. Many researchers are commonly confronted with the lack of raw datasets during the validation step of such methods. In order to increase test possibilities, the NMRb web-site offers a database of NMR raw datasets, ordered by spectral characteristics.'),
(71571, 2004, 'bio', 'Advances to Bayesian network inference for generating causal networks from observational biological data', 'Yu, Jing|Smith, V Anne|Wang, Paul P|Hartemink, Alexander J|Jarvis, Erich D', 'Department of Neurobiology, Duke University Medical Center, Box 3209, Durham, NC 27710, USA. yu@ee.duke.edu <yu@ee.duke.edu>|Department of Neurobiology, Duke University Medical Center, Box 3209, Durham, NC 27710, USA. yu@ee.duke.edu <yu@ee.duke.edu>|Department of Neurobiology, Duke University Medical Center, Box 3209, Durham, NC 27710, USA. yu@ee.duke.edu <yu@ee.duke.edu>|Department of Neurobiology, Duke University Medical Center, Box 3209, Durham, NC 27710, USA. yu@ee.duke.edu <yu@ee.duke.edu>|Department of Neurobiology, Duke University Medical Center, Box 3209, Durham, NC 27710, USA. yu@ee.duke.edu <yu@ee.duke.edu>', 'United States|United States|United States|United States|United States', 474, 'Algorithms|Bayes Theorem|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Signal Transduction|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth448', '15284094', 'Network inference algorithms are powerful computational tools for identifying putative causal interactions among variables from observational data. Bayesian network inference algorithms hold particular promise in that they can capture linear, non-linear, combinatorial, stochastic and other types of relationships among variables across multiple levels of biological organization. However, challenges remain when applying these algorithms to limited quantities of experimental data collected from biological systems. Here, we use a simulation approach to make advances in our dynamic Bayesian network (DBN) inference algorithm, especially in the context of limited quantities of biological data.'),
(71572, 2004, 'bio', 'Quantifying reproducibility for differential proteomics: noise analysis for protein liquid chromatography-mass spectrometry of human serum', 'Anderle, Markus|Roy, Sushmita|Lin, Hua|Becker, Christopher|Joho, Keith', 'SurroMed, Inc., 1430 OBrien Drive, Menlo Park, CA 94025, USA. manderle@surromed.com <manderle@surromed.com>|SurroMed, Inc., 1430 OBrien Drive, Menlo Park, CA 94025, USA. manderle@surromed.com <manderle@surromed.com>|SurroMed, Inc., 1430 OBrien Drive, Menlo Park, CA 94025, USA. manderle@surromed.com <manderle@surromed.com>|SurroMed, Inc., 1430 OBrien Drive, Menlo Park, CA 94025, USA. manderle@surromed.com <manderle@surromed.com>|SurroMed, Inc., 1430 OBrien Drive, Menlo Park, CA 94025, USA. manderle@surromed.com <manderle@surromed.com>', 'United States|United States|United States|United States|United States', 102, 'Algorithms|Blood Chemical Analysis|Blood Proteins|Chromatography, Liquid|Humans|Mass Spectrometry|Models, Biological|Models, Chemical|Models, Statistical|Proteomics|Quality Control|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Serum|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/bth446', '15284095', 'Using replicated human serum samples, we applied an error model for proteomic differential expression profiling for a high-resolution liquid chromatography-mass spectrometry (LC-MS) platform. The detailed noise analysis presented here uses an experimental design that separates variance caused by sample preparation from variance due to analytical equipment. An analytic approach based on a two-component error model was applied, and in combination with an existing data driven technique that utilizes local sample averaging, we characterized and quantified the noise variance as a function of mean peak intensity. The results indicate that for processed LC-MS data a constant coefficient of variation is dominant for high intensities, whereas a model for low intensities explains Poisson-like variations. This result leads to a quadratic variance model which is used for the estimation of sample preparation noise present in LC-MS data.'),
(71573, 2004, 'bio', 'Discovery of meaningful associations in genomic data using partial correlation coefficients', 'de la Fuente, Alberto|Bing, Nan|Hoeschele, Ina|Mendes, Pedro', 'Virginia Polytechnic Institute and State University, Virginia Bioinformatics Institute, 1880 Pratt Drive, Blacksburg 24061, USA. alf@vbi.vt.edu <alf@vbi.vt.edu>|Virginia Polytechnic Institute and State University, Virginia Bioinformatics Institute, 1880 Pratt Drive, Blacksburg 24061, USA. alf@vbi.vt.edu <alf@vbi.vt.edu>|Virginia Polytechnic Institute and State University, Virginia Bioinformatics Institute, 1880 Pratt Drive, Blacksburg 24061, USA. alf@vbi.vt.edu <alf@vbi.vt.edu>|Virginia Polytechnic Institute and State University, Virginia Bioinformatics Institute, 1880 Pratt Drive, Blacksburg 24061, USA. alf@vbi.vt.edu <alf@vbi.vt.edu>', 'United States|United States|United States|United States', 376, 'Algorithms|Chromosome Mapping|Gene Expression Regulation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Open Reading Frames|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Statistics as Topic', 'Evaluation Studies', '10.1093/bioinformatics/bth445', '15284096', 'A major challenge of systems biology is to infer biochemical interactions from large-scale observations, such as transcriptomics, proteomics and metabolomics. We propose to use a partial correlation analysis to construct approximate Undirected Dependency Graphs from such large-scale biochemical data. This approach enables a distinction between direct and indirect interactions of biochemical compounds, thereby inferring the underlying network topology.'),
(71574, 2004, 'bio', 'CLANS: a Java application for visualizing protein families based on pairwise similarity', 'Frickey, Tancred|Lupas, Andrei', 'Max Planck Institut fuer Entwicklungsbiologie, Spemannstrasse 35, 72076 Tuebingen, Germany.|Max Planck Institut fuer Entwicklungsbiologie, Spemannstrasse 35, 72076 Tuebingen, Germany.', 'Germany|Germany', 0, 'Algorithms|Computer Graphics|Computer Simulation|Conserved Sequence|Models, Molecular|Programming Languages|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth444', '15284097', 'The main source of hypotheses on the structure and function of new proteins is their homology to proteins with known properties. Homologous relationships are typically established through sequence similarity searches, multiple alignments and phylogenetic reconstruction. In cases where the number of potential relationships is large, for example in P-loop NTPases with many thousands of members, alignments and phylogenies become computationally demanding, accumulate errors and lose resolution. In search of a better way to analyze relationships in large sequence datasets we have developed a Java application, CLANS (CLuster ANalysis of Sequences), which uses a version of the Fruchterman-Reingold graph layout algorithm to visualize pairwise sequence similarities in either two-dimensional or three-dimensional space.'),
(71575, 2004, 'bio', 'The Baumgartner-Weiss-Schindler test for the detection of differentially expressed genes in replicated microarray experiments', 'Neuhäuser, Markus|Senske, Roswitha', 'Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Hufelandstr. 55, D-45122 Essen, Germany. markus.neuhaeuser@medizin.uni-essen.de <markus.neuhaeuser@medizin.uni-essen.de>|Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Hufelandstr. 55, D-45122 Essen, Germany. markus.neuhaeuser@medizin.uni-essen.de <markus.neuhaeuser@medizin.uni-essen.de>', 'Germany|Germany', 0, 'Algorithms|Data Interpretation, Statistical|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sample Size|Software', 'Comparative Study', '10.1093/bioinformatics/bth442', '15284098', 'An important application of microarray experiments is to identify differentially expressed genes. Because microarray data are often not distributed according to a normal distribution nonparametric methods were suggested for their statistical analysis. Here, the Baumgartner-Weiss-Schindler test, a novel and powerful test based on ranks, is investigated and compared with the parametric t-test as well as with two other nonparametric tests (Wilcoxon rank sum test, Fisher-Pitman permutation test) recently recommended for the analysis of gene expression data.'),
(71576, 2004, 'bio', 'The subsequent artificial neural network (SANN) approach might bring more classificatory power to ANN-based DNA microarray analyses', 'Linder, Roland|Dew, Dawn|Sudhoff, Holger|Theegarten, Dirk|Remberger, Klaus|Pöppl, Siegfried J|Wagner, Mathias', 'Institute for Medical Informatics, Medical University of Luebeck, 23538 Luebeck, Germany. linder@imi.uni-luebeck.de <linder@imi.uni-luebeck.de>|Institute for Medical Informatics, Medical University of Luebeck, 23538 Luebeck, Germany. linder@imi.uni-luebeck.de <linder@imi.uni-luebeck.de>|Institute for Medical Informatics, Medical University of Luebeck, 23538 Luebeck, Germany. linder@imi.uni-luebeck.de <linder@imi.uni-luebeck.de>|Institute for Medical Informatics, Medical University of Luebeck, 23538 Luebeck, Germany. linder@imi.uni-luebeck.de <linder@imi.uni-luebeck.de>|Institute for Medical Informatics, Medical University of Luebeck, 23538 Luebeck, Germany. linder@imi.uni-luebeck.de <linder@imi.uni-luebeck.de>|Institute for Medical Informatics, Medical University of Luebeck, 23538 Luebeck, Germany. linder@imi.uni-luebeck.de <linder@imi.uni-luebeck.de>|Institute for Medical Informatics, Medical University of Luebeck, 23538 Luebeck, Germany. linder@imi.uni-luebeck.de <linder@imi.uni-luebeck.de>', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 42, 'Algorithms|Cluster Analysis|Expert Systems|Gene Expression Profiling|Neural Networks (Computer)|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Software', 'Comparative Study', '10.1093/bioinformatics/bth441', '15284099', 'Human decisions often proceed in two steps. Initially those most preferred are chosen followed by a subsequent choice of these preferences. Applying one artificial neural network (ANN), a classification is limited to the preselection process. The final categorization is only possible by a subsequent ANN that distinguishes the pre-chosen classes. Existing strategies using coupled ANNs are discussed and a new approach particularly suited for multiclass classification problems is introduced (Subsequent ANN, SANN).'),
(71577, 2004, 'bio', 'Accurate detection of aneuploidies in array CGH and gene expression microarray data', 'Myers, Chad L|Dunham, Maitreya J|Kung, S Y|Troyanskaya, Olga G', 'Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory.', '-|-|-|-', 0, 'Algorithms|Aneuploidy|Chromosome Mapping|DNA Mutational Analysis|Gene Dosage|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Signal Processing, Computer-Assisted|Software', 'Comparative Study', '10.1093/bioinformatics/bth440', '15284100', 'Chromosomal copy number changes (aneuploidies) are common in cell populations that undergo multiple cell divisions including yeast strains, cell lines and tumor cells. Identification of aneuploidies is critical in evolutionary studies, where changes in copy number serve an adaptive purpose, as well as in cancer studies, where amplifications and deletions of chromosomal regions have been identified as a major pathogenetic mechanism. Aneuploidies can be studied on whole-genome level using array CGH (a microarray-based method that measures the DNA content), but their presence also affects gene expression. In gene expression microarray analysis, identification of copy number changes is especially important in preventing aberrant biological conclusions based on spurious gene expression correlation or masked phenotypes that arise due to aneuploidies. Previously suggested approaches for aneuploidy detection from microarray data mostly focus on array CGH, address only whole-chromosome or whole-arm copy number changes, and rely on thresholds or other heuristics, making them unsuitable for fully automated general application to gene expression datasets. There is a need for a general and robust method for identification of aneuploidies of any size from both array CGH and gene expression microarray data.'),
(71578, 2004, 'bio', 'Primer design and marker clustering for multiplex SNP-IT primer extension genotyping assay using statistical modeling', 'Yuryev, Anton|Huang, Jianping|Scott, Kathryn E|Kuebler, Jennifer|Donaldson, Miriam|Phillips, Michael S|Pohl, Mark|Boyce-Jacino, Michael T', 'Ariadne Genomics Inc, Rockville, MD 20850, USA. ayuryev@ariadnegenomics.com <ayuryev@ariadnegenomics.com>|Ariadne Genomics Inc, Rockville, MD 20850, USA. ayuryev@ariadnegenomics.com <ayuryev@ariadnegenomics.com>|Ariadne Genomics Inc, Rockville, MD 20850, USA. ayuryev@ariadnegenomics.com <ayuryev@ariadnegenomics.com>|Ariadne Genomics Inc, Rockville, MD 20850, USA. ayuryev@ariadnegenomics.com <ayuryev@ariadnegenomics.com>|Ariadne Genomics Inc, Rockville, MD 20850, USA. ayuryev@ariadnegenomics.com <ayuryev@ariadnegenomics.com>|Ariadne Genomics Inc, Rockville, MD 20850, USA. ayuryev@ariadnegenomics.com <ayuryev@ariadnegenomics.com>|Ariadne Genomics Inc, Rockville, MD 20850, USA. ayuryev@ariadnegenomics.com <ayuryev@ariadnegenomics.com>|Ariadne Genomics Inc, Rockville, MD 20850, USA. ayuryev@ariadnegenomics.com <ayuryev@ariadnegenomics.com>', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Cluster Analysis|DNA Mutational Analysis|DNA Primers|DNA Probes|Genetic Markers|Genetic Testing|Genotype|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bth439', '15284101', 'The optimization of the primer design is critical for the development of high-throughput SNP genotyping methods. Recently developed statistical models of the SNP-IT primer extension genotyping reaction allow further improvement of primer quality for the assay.'),
(71579, 2005, 'bio', 'DNAFSMiner: a web-based software toolbox to recognize two types of functional sites in DNA sequences', 'Liu, Huiqing|Han, Hao|Li, Jinyan|Wong, Limsoon', 'Institute for Infocomm Research 21 Heng Mui Keng Terrace, Singapore, 119613. huiqing@i2r.a-star.edu.sg|Institute for Infocomm Research 21 Heng Mui Keng Terrace, Singapore, 119613. huiqing@i2r.a-star.edu.sg|Institute for Infocomm Research 21 Heng Mui Keng Terrace, Singapore, 119613. huiqing@i2r.a-star.edu.sg|Institute for Infocomm Research 21 Heng Mui Keng Terrace, Singapore, 119613. huiqing@i2r.a-star.edu.sg', 'Singapore|Singapore|Singapore|Singapore', 35, 'Algorithms|Artificial Intelligence|Database Management Systems|Humans|Information Storage and Retrieval|Internet|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Software|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bth437', '15284102', 'DNAFSMiner (DNA Functional Sites Miner) is a web-based software toolbox to recognize functional sites in nucleic acid sequences. Currently in this toolbox, we provide two software: TIS Miner and Poly(A) Signal Miner. The TIS Miner can be used to predict translation initiation sites in vertebrate DNA/mRNA/cDNA sequences, and the Poly(A) Signal Miner can be used to predict polyadenylation [poly(A)] signals in human DNA sequences. The prediction results are better than those by literature methods on two benchmark applications. This good performance is mainly attributable to our unique learning method. DNAFSMiner is available free of charge for academic and non-profit organizations.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71580, 2004, 'bio', 'Modeling interactome: scale-free or geometric?', 'Przulj, N|Corneil, D G|Jurisica, I', 'Department of Computer Science, University of Toronto, Toronto, M5S 3G4, Canada.|Department of Computer Science, University of Toronto, Toronto, M5S 3G4, Canada.|Department of Computer Science, University of Toronto, Toronto, M5S 3G4, Canada.', 'Canada|Canada|Canada', 399, 'Algorithms|Animals|Computer Simulation|Drosophila Proteins|Drosophila melanogaster|Gene Expression Regulation|Models, Biological|Protein Interaction Mapping|Proteome|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bth436', '15284103', 'Networks have been used to model many real-world phenomena to better understand the phenomena and to guide experiments in order to predict their behavior. Since incorrect models lead to incorrect predictions, it is vital to have as accurate a model as possible. As a result, new techniques and models for analyzing and modeling real-world networks have recently been introduced.'),
(71581, 2004, 'bio', 'Exploring protein fold space by secondary structure prediction using data distribution method on Grid platform', 'Lee, Soojin|Cho, Min-Kyu|Jung, Jin-Won|Kim, Jai-Hoon|Lee, Weontae', 'Distributed and Mobile Computing Laboratory, Graduate School of Information and Communication, Ajou University, Suwon 442-749, Korea.|Distributed and Mobile Computing Laboratory, Graduate School of Information and Communication, Ajou University, Suwon 442-749, Korea.|Distributed and Mobile Computing Laboratory, Graduate School of Information and Communication, Ajou University, Suwon 442-749, Korea.|Distributed and Mobile Computing Laboratory, Graduate School of Information and Communication, Ajou University, Suwon 442-749, Korea.|Distributed and Mobile Computing Laboratory, Graduate School of Information and Communication, Ajou University, Suwon 442-749, Korea.', '-|-|-|-|-', 0, 'Computing Methodologies|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Models, Chemical|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/bth435', '15284104', 'Since the newly developed Grid platform has been considered as a powerful tool to share resources in the Internet environment, it is of interest to demonstrate an efficient methodology to process massive biological data on the Grid environments at a low cost. This paper presents an efficient and economical method based on a Grid platform to predict secondary structures of all proteins in a given organism, which normally requires a long computation time through sequential execution, by means of processing a large amount of protein sequence data simultaneously. From the prediction results, a genome scale protein fold space can be pursued.'),
(71582, 2004, 'bio', 'Ontologies for behavior', 'Midford, Peter E', 'Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA. peter@biorepresentation.com <peter@biorepresentation.com>', 'United States', 10, 'Algorithms|Animals|Behavior, Animal|Models, Biological|Natural Language Processing|Software|Task Performance and Analysis|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bth433', '15284105', 'Although dozens of biological ontologies have been created and deployed, relatively little attention has been given to using ontologies to represent behavior. Ontologies for two different behavior systems are described here. One ontology was a translation of a published ethogram, and the second was coded from video clips in a comparative study of jumping spider courtship.'),
(71583, 2004, 'bio', 'DIVAA: analysis of amino acid diversity in multiple aligned protein sequences', 'Rodi, Diane J|Mandava, Suneeta|Makowski, Lee', 'Combinatorial Biology Unit, Biosciences Division, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, IL 60439, USA.|Combinatorial Biology Unit, Biosciences Division, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, IL 60439, USA.|Combinatorial Biology Unit, Biosciences Division, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, IL 60439, USA.', 'United States|United States|United States', 27, 'Algorithms|Chromosome Mapping|Evolution, Molecular|Genetic Variation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth432', '15284106', 'Multiple alignments of proteins are an effective way of identifying conserved amino acids that provide clues to functional relationships among proteins. Quantitation of the abundances of amino acids found at each position in a sequence motif can provide a basis for understanding the structural and functional constraints at each point. Distribution of information across a motif has been used previously, but the non-intuitive nature of the analysis has limited its impact.'),
(71584, 2004, 'bio', 'MedlineR: an open source library in R for Medline literature data mining', 'Lin, Simon M|McConnell, Patrick|Johnson, Kimberly F|Shoemaker, Jennifer', 'Duke Comprehensive Cancer Center, Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27710, USA. Lin00025@mc.duke.edu <Lin00025@mc.duke.edu>|Duke Comprehensive Cancer Center, Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27710, USA. Lin00025@mc.duke.edu <Lin00025@mc.duke.edu>|Duke Comprehensive Cancer Center, Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27710, USA. Lin00025@mc.duke.edu <Lin00025@mc.duke.edu>|Duke Comprehensive Cancer Center, Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27710, USA. Lin00025@mc.duke.edu <Lin00025@mc.duke.edu>', 'United States|United States|United States|United States', 0, 'Abstracting and Indexing as Topic|Database Management Systems|Gene Expression Regulation|Information Storage and Retrieval|Internet|Libraries|MEDLINE|Models, Biological|Natural Language Processing|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Periodicals as Topic|Proteomics|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth404', '15284107', 'We describe an open source library written in the R programming language for Medline literature data mining. This MedlineR library includes programs to query Medline through the NCBI PubMed database, to construct the co-occurrence matrix, and to visualize the network topology of query terms. The open source nature of this library allows users to extend it freely in the statistical programming language of R. To demonstrate its utility, we have built an application to analyze term-association by using only 10 lines of code. We provide MedlineR as a library foundation for bioinformaticians and statisticians to build more sophisticated literature data mining applications.'),
(71585, 2005, 'bio', 'PIML: the Pathogen Information Markup Language', 'He, Yongqun|Vines, Richard R|Wattam, Alice R|Abramochkin, Georgiy V|Dickerman, Allan W|Eckart, J Dana|Sobral, Bruno W S', 'Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, 1880 Pratt Drive, Blacksburg, VA 24061-0477, USA. pathinfo@vbi.vt.edu|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, 1880 Pratt Drive, Blacksburg, VA 24061-0477, USA. pathinfo@vbi.vt.edu|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, 1880 Pratt Drive, Blacksburg, VA 24061-0477, USA. pathinfo@vbi.vt.edu|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, 1880 Pratt Drive, Blacksburg, VA 24061-0477, USA. pathinfo@vbi.vt.edu|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, 1880 Pratt Drive, Blacksburg, VA 24061-0477, USA. pathinfo@vbi.vt.edu|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, 1880 Pratt Drive, Blacksburg, VA 24061-0477, USA. pathinfo@vbi.vt.edu|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, 1880 Pratt Drive, Blacksburg, VA 24061-0477, USA. pathinfo@vbi.vt.edu', 'United States|United States|United States|United States|United States|United States|United States', 18, 'Bacteria|Database Management Systems|Documentation|Information Storage and Retrieval|Internet|Natural Language Processing|Programming Languages|Software|User-Computer Interface|Viruses', 'Evaluation Studies', '10.1093/bioinformatics/bth462', '15297293', 'A vast amount of information about human, animal and plant pathogens has been acquired, stored and displayed in varied formats through different resources, both electronically and otherwise. However, there is no community standard format for organizing this information or agreement on machine-readable format(s) for data exchange, thereby hampering interoperation efforts across information systems harboring such infectious disease data.'),
(71586, 2004, 'bio', 'Predicting GPCR-G-protein coupling using hidden Markov models', 'Sreekumar, Kodangattil R|Huang, Youping|Pausch, Mark H|Gulukota, Kamalakar', 'Department of Genomics, Wyeth Research, CN8000 Princeton, NJ 08543, USA. sreekuk@wyeth.com <sreekuk@wyeth.com>|Department of Genomics, Wyeth Research, CN8000 Princeton, NJ 08543, USA. sreekuk@wyeth.com <sreekuk@wyeth.com>|Department of Genomics, Wyeth Research, CN8000 Princeton, NJ 08543, USA. sreekuk@wyeth.com <sreekuk@wyeth.com>|Department of Genomics, Wyeth Research, CN8000 Princeton, NJ 08543, USA. sreekuk@wyeth.com <sreekuk@wyeth.com>', 'United States|United States|United States|United States', 0, 'Binding Sites|Computer Simulation|GTP-Binding Proteins|Markov Chains|Models, Chemical|Models, Statistical|Protein Binding|Protein Interaction Mapping|Receptors, G-Protein-Coupled|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth434', '15297294', 'Determining the coupling specificity of G-protein coupled receptors (GPCRs) is important for understanding the biology of this class of pharmacologically important proteins. Currently available in silico methods for predicting GPCR-G-protein coupling specificity have high error rate.'),
(71587, 2004, 'bio', 'Comparative analysis of methods for representing and searching for transcription factor binding sites', 'Osada, Robert|Zaslavsky, Elena|Singh, Mona', 'Department of Computer Science & Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.|Department of Computer Science & Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.|Department of Computer Science & Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.', 'United States|United States|United States', 0, 'Algorithms|Benchmarking|Binding Sites|DNA, Bacterial|DNA-Binding Proteins|Escherichia coli|Protein Binding|Sequence Analysis, DNA|Software|Software Validation|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth438', '15297295', 'An important step in unravelling the transcriptional regulatory network of an organism is to identify, for each transcription factor, all of its DNA binding sites. Several approaches are commonly used in searching for a transcription factors binding sites, including consensus sequences and position-specific scoring matrices. In addition, methods that compute the average number of nucleotide matches between a putative site and all known sites can be employed. Such basic approaches can all be naturally extended by incorporating pairwise nucleotide dependencies and per-position information content. In this paper, we evaluate the effectiveness of these basic approaches and their extensions in finding binding sites for a transcription factor of interest without erroneously identifying other genomic sequences.'),
(71588, 2004, 'bio', 'limmaGUI: a graphical user interface for linear modeling of microarray data', 'Wettenhall, James M|Smyth, Gordon K', 'Division of Genetics and Bioinformatics, Walter and Eliza Hall Institute of Medical Research, 1G Royal Pde, Parkville, 3050, Australia. wettenhall@wehi.edu.au <wettenhall@wehi.edu.au>|Division of Genetics and Bioinformatics, Walter and Eliza Hall Institute of Medical Research, 1G Royal Pde, Parkville, 3050, Australia. wettenhall@wehi.edu.au <wettenhall@wehi.edu.au>', 'Australia|Australia', 0, 'Computer Graphics|Computer Simulation|Gene Expression Profiling|Linear Models|Models, Genetic|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth449', '15297296', 'limmaGUI is a graphical user interface (GUI) based on R-Tcl/Tk for the exploration and linear modeling of data from two-color spotted microarray experiments, especially the assessment of differential expression in complex experiments. limmaGUI provides an interface to the statistical methods of the limma package for R, and is itself implemented as an R package. The software provides point and click access to a range of methods for background correction, graphical display, normalization, and analysis of microarray data. Arbitrarily complex microarray experiments involving multiple RNA sources can be accomodated using linear models and contrasts. Empirical Bayes shrinkage of the gene-wise residual variances is provided to ensure stable results even when the number of arrays is small. Integrated support is provided for quantitative spot quality weights, control spots, within-array replicate spots and multiple testing. limmaGUI is available for most platforms on the which R runs including Windows, Mac and most flavors of Unix.'),
(71589, 2004, 'bio', 'Training HMM structure with genetic algorithm for biological sequence analysis', 'Won, Kyoung-Jae|Prügel-Bennett, Adam|Krogh, Anders', 'ISIS Group, ECS, University of Southampton, SO17 1BJ, UK. j.won@ecs.soton.ac.uk <j.won@ecs.soton.ac.uk>|ISIS Group, ECS, University of Southampton, SO17 1BJ, UK. j.won@ecs.soton.ac.uk <j.won@ecs.soton.ac.uk>|ISIS Group, ECS, University of Southampton, SO17 1BJ, UK. j.won@ecs.soton.ac.uk <j.won@ecs.soton.ac.uk>', 'United Kingdom|United Kingdom|United Kingdom', 36, 'Algorithms|Artificial Intelligence|Campylobacter jejuni|Chromosome Mapping|Markov Chains|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bth454', '15297297', 'Hidden Markov models (HMMs) are widely used for biological sequence analysis because of their ability to incorporate biological information in their structure. An automatic means of optimizing the structure of HMMs would be highly desirable. However, this raises two important issues, first, the new HMMs should be biologically interpretable, and second, we need to control the complexity of the HMM so that it has good generalization performance on unseen sequences. In this paper, we explore the possibility of using a genetic algorithm (GA) for optimizing the HMM structure. GAs are sufficiently flexible to allow incorporation of other techniques such as Baum-Welch training within their evolutionary cycle. Furthermore, operators that alter the structure of HMMs can be designed to favour interpretable and simple structures. In this paper, a training strategy using GAs is proposed, and it is tested on finding HMM structures for the promoter and coding region of the bacterium Campylobacter jejuni. The proposed GA for hidden Markov models (GA-HMM) allows, HMMs with different numbers of states to evolve. To prevent over-fitting, a separate dataset is used for comparing the performance of the HMMs to that used for the Baum-Welch training. The GA-HMM was capable of finding an HMM comparable to a hand-coded HMM designed for the same task, which has been published previously.'),
(71590, 2004, 'bio', 'Highly specific prediction of phosphorylation sites in proteins', 'Koenig, Matthias|Grabe, Niels', 'CeVis, University of Bremen, Universitaetsallee 29, 28359 Bremen, Germany. koenig@cevis.uni-bremen.de <koenig@cevis.uni-bremen.de>|CeVis, University of Bremen, Universitaetsallee 29, 28359 Bremen, Germany. koenig@cevis.uni-bremen.de <koenig@cevis.uni-bremen.de>', 'Germany|Germany', 8, 'Algorithms|Binding Sites|Phosphorus Compounds|Phosphorylation|Protein Binding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth455', '15297298', 'The prediction of significant short functional protein sequences has inherent problems. In predicting phosphorylation sites, problems came from the shortness of phosphorylation sites, the difficulties in maintaining many different predefined models of binding sites, and the difficulties of obtaining highly sensitive predictions and of obtaining predictions with a constant sensitivity and specificity. The algorithm presented in this paper overcomes these problems. The proposed algorithm PHOSITE is based on the case-based sequence analysis. This enables the prediction of phosphorylation sites with constant specificity and sensitivity. Furthermore, this method leads not only to the prediction of phosphorylation sites in general but also predicts the most probable type of kinase involved.'),
(71591, 2004, 'bio', 'GO::TermFinder--open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes', 'Boyle, Elizabeth I|Weng, Shuai|Gollub, Jeremy|Jin, Heng|Botstein, David|Cherry, J Michael|Sherlock, Gavin', 'Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.|Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.|Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.|Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.|Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.|Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.|Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.', 'United States|United States|United States|United States|United States|United States|United States', 1176, 'Abstracting and Indexing as Topic|Database Management Systems|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Natural Language Processing|Oligonucleotide Array Sequence Analysis|Programming Languages|Software|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bth456', '15297299', 'GO::TermFinder comprises a set of object-oriented Perl modules for accessing Gene Ontology (GO) information and evaluating and visualizing the collective annotation of a list of genes to GO terms. It can be used to draw conclusions from microarray and other biological data, calculating the statistical significance of each annotation. GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script.'),
(71592, 2005, 'bio', 'Haploview: analysis and visualization of LD and haplotype maps', 'Barrett, J C|Fry, B|Maller, J|Daly, M J', 'Whitehead Institute for Biomedical Research Cambridge, MA 02142, USA. jcbarret@broad.mit.edu|Whitehead Institute for Biomedical Research Cambridge, MA 02142, USA. jcbarret@broad.mit.edu|Whitehead Institute for Biomedical Research Cambridge, MA 02142, USA. jcbarret@broad.mit.edu|Whitehead Institute for Biomedical Research Cambridge, MA 02142, USA. jcbarret@broad.mit.edu', 'United States|United States|United States|United States', 4959, 'Algorithms|Chromosome Mapping|Haplotypes|Internet|Linkage Disequilibrium|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth457', '15297300', 'Research over the last few years has revealed significant haplotype structure in the human genome. The characterization of these patterns, particularly in the context of medical genetic association studies, is becoming a routine research activity. Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface.'),
(71593, 2005, 'bio', 'Network structures and algorithms in Bioconductor', 'Carey, Vincent J|Gentry, Jeff|Whalen, Elizabeth|Gentleman, Robert', 'Channing Laboratory, Brigham and Womens Hospital 75 Francis Street, Boston, MA 02115, USA. stvjc@channing.harvard.edu|Channing Laboratory, Brigham and Womens Hospital 75 Francis Street, Boston, MA 02115, USA. stvjc@channing.harvard.edu|Channing Laboratory, Brigham and Womens Hospital 75 Francis Street, Boston, MA 02115, USA. stvjc@channing.harvard.edu|Channing Laboratory, Brigham and Womens Hospital 75 Francis Street, Boston, MA 02115, USA. stvjc@channing.harvard.edu', 'United States|United States|United States|United States', 56, 'Algorithms|Computer Graphics|Computer Simulation|Gene Expression Regulation|Information Storage and Retrieval|Internet|Models, Biological|Signal Transduction|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth458', '15297301', 'In this paper, we review the central concepts and implementations of tools for working with network structures in Bioconductor. Interfaces to open source resources for visualization (AT&T Graphviz) and network algorithms (Boost) have been developed to support analysis of graphical structures in genomics and computational biology.'),
(71594, 2004, 'bio', 'Modular, scriptable and automated analysis tools for high-throughput peptide mass fingerprinting', 'Samuelsson, Jim|Dalevi, Daniel|Levander, Fredrik|Rögnvaldsson, Thorsteinn', 'Genedata GmbH, Lena-Christ-Strasse 50, 82152 Martinsried, Germany.|Genedata GmbH, Lena-Christ-Strasse 50, 82152 Martinsried, Germany.|Genedata GmbH, Lena-Christ-Strasse 50, 82152 Martinsried, Germany.|Genedata GmbH, Lena-Christ-Strasse 50, 82152 Martinsried, Germany.', 'Germany|Germany|Germany|Germany', 21, 'Algorithms|Database Management Systems|Documentation|Information Storage and Retrieval|Peptide Mapping|Programming Languages|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth460', '15297302', 'A set of new algorithms and software tools for automatic protein identification using peptide mass fingerprinting is presented. The software is automatic, fast and modular to suit different laboratory needs, and it can be operated either via a Java user interface or called from within scripts. The software modules do peak extraction, peak filtering and protein database matching, and communicate via XML. Individual modules can therefore easily be replaced with other software if desired, and all intermediate results are available to the user. The algorithms are designed to operate without human intervention and contain several novel approaches. The performance and capabilities of the software is illustrated on spectra from different mass spectrometer manufacturers, and the factors influencing successful identification are discussed and quantified.'),
(71595, 2005, 'bio', 'How many samples are needed to build a classifier: a general sequential approach', 'Fu, Wenjiang J|Dougherty, Edward R|Mallick, Bani|Carroll, Raymond J', 'Department of Statistics, Texas A&M University, 447 Blocker Building, College Station, TX 77843, USA. wfu@stat.tamu.edu|Department of Statistics, Texas A&M University, 447 Blocker Building, College Station, TX 77843, USA. wfu@stat.tamu.edu|Department of Statistics, Texas A&M University, 447 Blocker Building, College Station, TX 77843, USA. wfu@stat.tamu.edu|Department of Statistics, Texas A&M University, 447 Blocker Building, College Station, TX 77843, USA. wfu@stat.tamu.edu', 'United States|United States|United States|United States', 22, 'Algorithms|Artificial Intelligence|Breast Neoplasms|Cluster Analysis|Humans|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth461', '15297303', 'The standard paradigm for a classifier design is to obtain a sample of feature-label pairs and then to apply a classification rule to derive a classifier from the sample data. Typically in laboratory situations the sample size is limited by cost, time or availability of sample material. Thus, an investigator may wish to consider a sequential approach in which there is a sufficient number of patients to train a classifier in order to make a sound decision for diagnosis while at the same time keeping the number of patients as small as possible to make the studies affordable.'),
(71596, 2005, 'bio', 'A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data', 'Zou, Min|Conzen, Suzanne D', 'Department of Medicine, 5841 South Maryland Avenue, University of Chicago, Chicago, IL 60637, USA.|Department of Medicine, 5841 South Maryland Avenue, University of Chicago, Chicago, IL 60637, USA.', 'United States|United States', 412, 'Algorithms|Bayes Theorem|Cell Cycle Proteins|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Time Factors|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth463', '15308537', 'Signaling pathways are dynamic events that take place over a given period of time. In order to identify these pathways, expression data over time are required. Dynamic Bayesian network (DBN) is an important approach for predicting the gene regulatory networks from time course expression data. However, two fundamental problems greatly reduce the effectiveness of current DBN methods. The first problem is the relatively low accuracy of prediction, and the second is the excessive computational time.'),
(71597, 2005, 'bio', 'Gene clustering by latent semantic indexing of MEDLINE abstracts', 'Homayouni, Ramin|Heinrich, Kevin|Wei, Lai|Berry, Michael W', 'Department of Neurology, University of Tennessee Health Science Center, 855 Monroe Avenue, 416 Link Bldg, Memphis, TN 38163, USA. rhomayouni@utmem.edu|Department of Neurology, University of Tennessee Health Science Center, 855 Monroe Avenue, 416 Link Bldg, Memphis, TN 38163, USA. rhomayouni@utmem.edu|Department of Neurology, University of Tennessee Health Science Center, 855 Monroe Avenue, 416 Link Bldg, Memphis, TN 38163, USA. rhomayouni@utmem.edu|Department of Neurology, University of Tennessee Health Science Center, 855 Monroe Avenue, 416 Link Bldg, Memphis, TN 38163, USA. rhomayouni@utmem.edu', 'United States|United States|United States|United States', 0, 'Abstracting and Indexing as Topic|Algorithms|Cluster Analysis|Documentation|Gene Expression Profiling|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Pattern Recognition, Automated|Proteins|Semantics|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bth464', '15308538', 'A major challenge in the interpretation of high-throughput genomic data is understanding the functional associations between genes. Previously, several approaches have been described to extract gene relationships from various biological databases using term-matching methods. However, more flexible automated methods are needed to identify functional relationships (both explicit and implicit) between genes from the biomedical literature. In this study, we explored the utility of Latent Semantic Indexing (LSI), a vector space model for information retrieval, to automatically identify conceptual gene relationships from titles and abstracts in MEDLINE citations.'),
(71598, 2005, 'bio', 'BioLingua: a programmable knowledge environment for biologists', 'Massar, J P|Travers, Michael|Elhai, Jeff|Shrager, Jeff', 'Institute for Study of Learning and Expertise Palo Alto, CA, USA.|Institute for Study of Learning and Expertise Palo Alto, CA, USA.|Institute for Study of Learning and Expertise Palo Alto, CA, USA.|Institute for Study of Learning and Expertise Palo Alto, CA, USA.', 'United States|United States|United States|United States', 29, 'Artificial Intelligence|Computational Biology|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Models, Biological|Models, Chemical|Programming Languages|Proteins|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth465', '15308539', 'BioLingua is an interactive, web-based programming environment that enables biologists to analyze biological systems by combining knowledge and data through direct end-user programming. BioLingua embeds a mature symbolic programming language in a frame-based knowledge environment, integrating genomic and pathway knowledge about a class of similar organisms. The BioLingua language provides interfaces to numerous state-of-the-art bioinformatic tools, making these available as an integrated package through the novel use of web-based programmability and an integrated Wiki-based community code and data store. The pilot instantiation of BioLingua, which has been developed in collaboration with several cyanobacteriologists, integrates knowledge about a subset of cyanobacteria with the Gene Ontology, KEGG and BioCyc knowledge bases. We introduce the BioLingua concept, architecture and language, and give several examples of its use in complex analyses.'),
(71599, 2005, 'bio', 'Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes', 'Chou, Kuo-Chen', 'Gordon Life Science Institute, San Diego, CA 92130, USA. kchou@san.rr.com', 'United States', 710, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Computer Simulation|Enzymes|Hydrophobic and Hydrophilic Interactions|Models, Chemical|Models, Statistical|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bth466', '15308540', 'With protein sequences entering into databanks at an explosive pace, the early determination of the family or subfamily class for a newly found enzyme molecule becomes important because this is directly related to the detailed information about which specific target it acts on, as well as to its catalytic process and biological function. Unfortunately, it is both time-consuming and costly to do so by experiments alone. In a previous study, the covariant-discriminant algorithm was introduced to identify the 16 subfamily classes of oxidoreductases. Although the results were quite encouraging, the entire prediction process was based on the amino acid composition alone without including any sequence-order information. Therefore, it is worthy of further investigation.'),
(71600, 2005, 'bio', 'Protein structure alignment by deterministic annealing', 'Chen, Luonan|Zhou, Tianshou|Tang, Yun', 'Department of Electrical Engineering and Electronics, Osaka Sangyo University, Osaka 574-8530, Japan. chen@elec.osaka-sandai.ac.jp|Department of Electrical Engineering and Electronics, Osaka Sangyo University, Osaka 574-8530, Japan. chen@elec.osaka-sandai.ac.jp|Department of Electrical Engineering and Electronics, Osaka Sangyo University, Osaka 574-8530, Japan. chen@elec.osaka-sandai.ac.jp', 'Japan|Japan|Japan', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1093/bioinformatics/bth467', '15308541', 'Protein structure alignment is one of the most important computational problems in molecular biology and plays a key role in protein structure prediction, fold family classification, motif finding, phylogenetic tree reconstruction and so on. From the viewpoint of computational complexity, a pairwise structure alignment is also a NP-hard problem, in contrast to the polynomial time algorithm for a pairwise sequence alignment.'),
(71601, 2005, 'bio', 'Outcome signature genes in breast cancer: is there a unique set?', 'Ein-Dor, Liat|Kela, Itai|Getz, Gad|Givol, David|Domany, Eytan', 'Department of Physics of Complex Systems, Weizmann Institute of Science Rehovot 76100, Israel.|Department of Physics of Complex Systems, Weizmann Institute of Science Rehovot 76100, Israel.|Department of Physics of Complex Systems, Weizmann Institute of Science Rehovot 76100, Israel.|Department of Physics of Complex Systems, Weizmann Institute of Science Rehovot 76100, Israel.|Department of Physics of Complex Systems, Weizmann Institute of Science Rehovot 76100, Israel.', 'Israel|Israel|Israel|Israel|Israel', 592, 'Biomarkers, Tumor|Breast Neoplasms|Clinical Trials as Topic|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Testing|Genetic Variation|Humans|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Prognosis|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Survival Analysis|Treatment Outcome', 'Evaluation Studies', '10.1093/bioinformatics/bth469', '15308542', 'Predicting the metastatic potential of primary malignant tissues has direct bearing on the choice of therapy. Several microarray studies yielded gene sets whose expression profiles successfully predicted survival. Nevertheless, the overlap between these gene sets is almost zero. Such small overlaps were observed also in other complex diseases, and the variables that could account for the differences had evoked a wide interest. One of the main open questions in this context is whether the disparity can be attributed only to trivial reasons such as different technologies, different patients and different types of analyses.'),
(71602, 2005, 'bio', 'SNP Chart: an integrated platform for visualization and interpretation of microarray genotyping data', 'Tebbutt, Scott J|Opushnyev, Igor V|Tripp, Ben W|Kassamali, Ayaz M|Alexander, Wendy L|Andersen, Marilyn I', 'James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St Pauls Hospital, University of British Columbia Vancouver, Canada. stebbutt@mrl.ubc.ca|James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St Pauls Hospital, University of British Columbia Vancouver, Canada. stebbutt@mrl.ubc.ca|James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St Pauls Hospital, University of British Columbia Vancouver, Canada. stebbutt@mrl.ubc.ca|James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St Pauls Hospital, University of British Columbia Vancouver, Canada. stebbutt@mrl.ubc.ca|James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St Pauls Hospital, University of British Columbia Vancouver, Canada. stebbutt@mrl.ubc.ca|James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St Pauls Hospital, University of British Columbia Vancouver, Canada. stebbutt@mrl.ubc.ca', 'Canada|Canada|Canada|Canada|Canada|Canada', 14, 'Computer Graphics|Database Management Systems|Gene Expression Profiling|Genotype|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth470', '15308543', 'SNP Chart is a Java application for the visualization and interpretation of microarray genotyping data primarily derived from arrayed primer extension-based chemistries. Spot intensity output files from microarray analysis tools are imported into SNP Chart, together with a multi-channel TIFF image of the original array experiment and a list of the actual single nucleotide polymorphisms (SNPs) being tested. Data from different and/or replicate probes that interrogate the same SNP, but that are scattered across the array grid, can be reassembled into a single chart format, specific for the SNP. This allows a quick and very effective visualization/quality control of the data from multiple probes for the same SNP that can be easily interpreted and manually scored as a genotype.'),
(71603, 2005, 'bio', 'A rapid method for computationally inferring transcriptome coverage and microarray sensitivity', 'Reverter, A|McWilliam, S M|Barris, W|Dalrymple, B P', 'Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, QLD 4067, Australia. Tony.Reverter-Gomez@csiro.au|Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, QLD 4067, Australia. Tony.Reverter-Gomez@csiro.au|Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, QLD 4067, Australia. Tony.Reverter-Gomez@csiro.au|Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, QLD 4067, Australia. Tony.Reverter-Gomez@csiro.au', 'Australia|Australia|Australia|Australia', 27, 'Algorithms|Chromosome Mapping|Expressed Sequence Tags|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Proteome|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth472', '15308544', 'There are many different gene expression technologies, including cDNA and oligo-based microarrays, SAGE and MPSS. For each organism of interest, coverage of the transcriptome and the genome will be different. We address the question of what level of coverage is required to exploit the sensitivity of the different technologies, and what is the sensitivity of the different approaches in the experimental study.'),
(71604, 2005, 'bio', 'Construction of robust prognostic predictors by using projective adaptive resonance theory as a gene filtering method', 'Takahashi, Hiro|Kobayashi, Takeshi|Honda, Hiroyuki', 'Department of Biotechnology, School of Engineering, Nagoya University Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.|Department of Biotechnology, School of Engineering, Nagoya University Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.|Department of Biotechnology, School of Engineering, Nagoya University Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.', 'Japan|Japan|Japan', 22, 'Algorithms|Biomarkers, Tumor|Breast Neoplasms|Clinical Trials as Topic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Testing|Genetic Variation|Humans|Internet|Leukemia|Lung Neoplasms|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Prognosis|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Software|Treatment Outcome', 'Comparative Study', '10.1093/bioinformatics/bth473', '15308545', 'For establishing prognostic predictors of various diseases using DNA microarray analysis technology, it is desired to find selectively significant genes for constructing the prognostic model and it is also necessary to eliminate non-specific genes or genes with error before constructing the model.'),
(71605, 2005, 'bio', 'Microarray data mining with visual programming', 'Curk, Tomaz|Demsar, Janez|Xu, Qikai|Leban, Gregor|Petrovic, Uros|Bratko, Ivan|Shaulsky, Gad|Zupan, Blaz', 'Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.', 'Slovenia|Slovenia|Slovenia|Slovenia|Slovenia|Slovenia|Slovenia|Slovenia', 108, 'Chromosome Mapping|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth474', '15308546', 'Visual programming offers an intuitive means of combining known analysis and visualization methods into powerful applications. The system presented here enables users who are not programmers to manage microarray and genomic data flow and to customize their analyses by combining common data analysis tools to fit their needs.'),
(71606, 2005, 'bio', 'Origins of introns based on the definition of exon modules and their conserved interfaces', 'de Roos, Albert D G', 'The Beagle Armada Postbus 964, 4600 AZ Bergen op Zoom, The Netherlands. albert.de.roos@thebeaglearmada.nl', 'Netherlands', 11, 'Animals|Chromosome Mapping|Computer Simulation|Conserved Sequence|Evolution, Molecular|Exons|Gene Expression Regulation|Genetic Variation|Genetics, Population|Humans|Introns|Models, Genetic|RNA, Catalytic', 'Journal Article', '10.1093/bioinformatics/bth475', '15308547', 'Central to the unraveling of the early evolution of the genome is the origin and role of introns. The evolution of the genome can be characterized by a continuous expansion of functional modules that occurs without the interruption of existing processes. The design-by-contract methodology of software development offers a modular approach to design that seeks to increase flexibility by focusing on the design of constant interfaces between functional modules. Here, it is shown that design-by-contract can offer a framework for genome evolution. The definition of an ancient exon module with identical splice sites leads to a relatively simple sequence of events that explains the role of introns, intron phase differences and the evolution of multi-exon proteins in an RNA world. An interaction of the experimentally defined six-nucleotide splicing consensus sequence together with a limited number of primitive ribozymes can account for a rapid creation of protein diversity.'),
(71607, 2005, 'bio', 'BlastAlign: a program that uses blast to align problematic nucleotide sequences', 'Belshaw, Robert|Katzourakis, Aris', 'Department of Biological Sciences, Imperial College Silwood Park Campus, Ascot, Berks SL5 7PY, UK. r.belshaw@imperial.ac.uk|Department of Biological Sciences, Imperial College Silwood Park Campus, Ascot, Berks SL5 7PY, UK. r.belshaw@imperial.ac.uk', 'United Kingdom|United Kingdom', 55, 'Algorithms|Base Sequence|Information Storage and Retrieval|Internet|Molecular Sequence Data|National Institutes of Health (U.S.)|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|United States', 'Journal Article', '10.1093/bioinformatics/bth459', '15310559', 'BlastAlign uses NCBI blastn to build a multiple nucleotide alignment and is intended for use with sequences that have large indels or are otherwise difficult to align globally. The program builds a matrix representing regions of homology along the sequences, from which it selects the most representative sequence and then extracts the blastn query-anchored multiple alignment for this sequence. The matrix is printed and allows subgroups to be identified visually and an option allows other sequences to be used as the most representative. The program contains elements of both Perl and Python and will run on UNIX (including Mac OSX) and DOS. An additional Perl program BlastAlignP uses tblastn to align nucleotide sequences to a single amino acid sequence, thus allowing an open reading frame to be maintained in the resulting multiple alignment.'),
(71608, 2005, 'bio', 'DisProt: a database of protein disorder', 'Vucetic, Slobodan|Obradovic, Zoran|Vacic, Vladimir|Radivojac, Predrag|Peng, Kang|Iakoucheva, Lilia M|Cortese, Marc S|Lawson, J David|Brown, Celeste J|Sikes, Jason G|Newton, Crystal D|Dunker, A Keith', 'Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.|Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.|Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.|Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.|Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.|Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.|Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.|Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.|Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.|Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.|Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.|Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 173, 'Amino Acid Sequence|Database Management Systems|Databases, Protein|Documentation|Information Dissemination|Information Storage and Retrieval|Molecular Sequence Data|Protein Conformation|Proteins|PubMed', 'Journal Article', '10.1093/bioinformatics/bth476', '15310560', 'The Database of Protein Disorder (DisProt) is a curated database that provides structure and function information about proteins that lack a fixed three-dimensional (3D) structure under putatively native conditions, either in their entirety or in part. Starting from the central premise that intrinsic disorder is an important structural class of protein and in order to meet the increasing interest thereof, DisProt is aimed at becoming a central repository of disorder-related information. For each disordered protein, the database includes the name of the protein, various aliases, accession codes, amino acid sequence, location of the disordered region(s), and methods used for structural (disorder) characterization. If applicable, most entries also list the biological function(s) of each disordered region, how each region of disorder is used for function, as well as provide links to PubMed abstracts and major protein databases.'),
(71609, 2004, 'bio', 'Comment on protein isoelectric point as a predictor for increased crystallization screening efficiency', 'Huber, Thomas|Kobe, Bostjan', 'Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.|Center for Information Science and Technology, Temple University Philadelphia, PA 19122, USA.', 'United States|United States', 3, 'Computer Simulation|Crystallization|Crystallography|Databases, Protein|Isoelectric Point|Models, Chemical|Models, Molecular|Models, Statistical|Protein Conformation|Proteins|Sensitivity and Specificity|Sequence Analysis, Protein', 'Comment', '10.1093/bioinformatics/bth452', '15317693', '-'),
(71610, 2005, 'bio', 'Supervised identification of allergen-representative peptides for in silico detection of potentially allergenic proteins', 'Björklund, Asa K|Soeria-Atmadja, Daniel|Zorzet, Anna|Hammerling, Ulf|Gustafsson, Mats G', 'Division of Toxicology, National Food Administration, P.O. Box 622, SE-751 26 Uppsala, Sweden.|Division of Toxicology, National Food Administration, P.O. Box 622, SE-751 26 Uppsala, Sweden.|Division of Toxicology, National Food Administration, P.O. Box 622, SE-751 26 Uppsala, Sweden.|Division of Toxicology, National Food Administration, P.O. Box 622, SE-751 26 Uppsala, Sweden.|Division of Toxicology, National Food Administration, P.O. Box 622, SE-751 26 Uppsala, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden', 68, 'Algorithms|Allergens|Amino Acid Motifs|Artificial Intelligence|Internet|Pattern Recognition, Automated|Peptides|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth477', '15319257', 'Identification of potentially allergenic proteins is needed for the safety assessment of genetically modified foods, certain pharmaceuticals and various other products on the consumer market. Current methods in bioinformatic allergology exploit common features among allergens for the detection of amino acid sequences of potentially allergenic proteins. Features for identification still unexplored include the motifs occurring commonly in allergens, but rarely in ordinary proteins. In this paper, we present an algorithm for the identification of such motifs with the purpose of biocomputational detection of amino acid sequences of potential allergens.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71611, 2005, 'bio', 'Simulating genetic networks made easy: network construction with simple building blocks', 'Vercruysse, Steven|Kuiper, Martin', 'Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent University Technologiepark 927, B-9052, Gent, Belgium.|Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent University Technologiepark 927, B-9052, Gent, Belgium.', 'Belgium|Belgium', 6, 'Algorithms|Computer Simulation|Gene Expression Regulation|Internet|Models, Genetic|Programming Languages|Signal Transduction|Software|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth478', '15319258', 'We present SIM-plex, a genetic network simulator with a very intuitive interface in which a user can easily specify interactions as simple if-then statements. The simulator is based on the mathematical model of Piecewise Linear Differential Equations (PLDEs). With PLDEs, genetic interactions are approximated as acting in a switch-like manner.'),
(71612, 2005, 'bio', 'A method for estimating stochastic noise in large genetic regulatory networks', 'Orrell, David|Ramsey, Stephen|de Atauri, Pedro|Bolouri, Hamid', 'Institute for Systems Biology 1441 North 34th Street, Seattle, WA 98103, USA. dorrell@systemsbiology.org|Institute for Systems Biology 1441 North 34th Street, Seattle, WA 98103, USA. dorrell@systemsbiology.org|Institute for Systems Biology 1441 North 34th Street, Seattle, WA 98103, USA. dorrell@systemsbiology.org|Institute for Systems Biology 1441 North 34th Street, Seattle, WA 98103, USA. dorrell@systemsbiology.org', 'United States|United States|United States|United States', 13, 'Algorithms|Galactose|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Stochastic Processes|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth479', '15319259', 'Genetic regulatory networks are often affected by stochastic noise, due to the low number of molecules taking part in certain reactions. The networks can be simulated using stochastic techniques that model each reaction as a stochastic event. As models become increasingly large and sophisticated, however, the solution time can become excessive, particularly if one wishes to determine the effect on noise of changes to a series of parameters, or the model structure. Methods are therefore required to rapidly estimate stochastic noise.'),
(71613, 2005, 'bio', 'Similarity of position frequency matrices for transcription factor binding sites', 'Schones, Dustin E|Sumazin, Pavel|Zhang, Michael Q', 'Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA. dschones@cshl.edu|Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA. dschones@cshl.edu|Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA. dschones@cshl.edu', 'United States|United States|United States', 85, 'Algorithms|Binding Sites|Protein Binding|Sequence Alignment|Sequence Analysis, Protein|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth480', '15319260', 'Transcription-factor binding sites (TFBS) in promoter sequences of higher eukaryotes are commonly modeled using position frequency matrices (PFM). The ability to compare PFMs representing binding sites is especially important for de novo sequence motif discovery, where it is desirable to compare putative matrices to one another and to known matrices.'),
(71614, 2005, 'bio', 'MCQTL: multi-allelic QTL mapping in multi-cross design', 'Jourjon, Marie-Françoise|Jasson, Sylvain|Marcel, Jacques|Ngom, Baba|Mangin, Brigitte', 'INRA, Unité de Biométrie et dIntelligence Artificielle B.P. 27, 31326 Castanet-Tolosan, France.|INRA, Unité de Biométrie et dIntelligence Artificielle B.P. 27, 31326 Castanet-Tolosan, France.|INRA, Unité de Biométrie et dIntelligence Artificielle B.P. 27, 31326 Castanet-Tolosan, France.|INRA, Unité de Biométrie et dIntelligence Artificielle B.P. 27, 31326 Castanet-Tolosan, France.|INRA, Unité de Biométrie et dIntelligence Artificielle B.P. 27, 31326 Castanet-Tolosan, France.', 'France|France|France|France|France', 78, 'Algorithms|Chromosome Mapping|Crosses, Genetic|Gene Frequency|Genetic Variation|Genotype|Linear Models|Quantitative Trait Loci|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/bth481', '15319261', 'The aim of the MCQTL software package is to perform QTL mapping in multi-cross designs. It allows the analysis of the usual populations derived from inbred lines and can link the families by assuming that the QTL locations are the same in all of them. Moreover, a diallel modelling of the QTL genotypic effects is allowed in multiple related families. The implemented model is a linear regression model. A composite interval mapping and an iterative QTL mapping are implemented to deal with multiple QTL models. Marker cofactor selections by forward or backward stepwise methods are implemented as well as computation of threshold test value by permutation.'),
(71615, 2005, 'bio', 'Predicting protein-protein interactions using signature products', 'Martin, Shawn|Roe, Diana|Faulon, Jean-Loup', 'Sandia National Laboratories, Computational Biology 9212, P.O. Box 5800, MS 310, Albuquerque, NM, 87185, USA. smartin@sandia.gov|Sandia National Laboratories, Computational Biology 9212, P.O. Box 5800, MS 310, Albuquerque, NM, 87185, USA. smartin@sandia.gov|Sandia National Laboratories, Computational Biology 9212, P.O. Box 5800, MS 310, Albuquerque, NM, 87185, USA. smartin@sandia.gov', 'United States|United States|United States', 282, 'Algorithms|Animals|Artificial Intelligence|Binding Sites|Humans|Mice|Models, Chemical|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bth483', '15319262', 'Proteome-wide prediction of protein-protein interaction is a difficult and important problem in biology. Although there have been recent advances in both experimental and computational methods for predicting protein-protein interactions, we are only beginning to see a confluence of these techniques. In this paper, we describe a very general, high-throughput method for predicting protein-protein interactions. Our method combines a sequence-based description of proteins with experimental information that can be gathered from any type of protein-protein interaction screen. The method uses a novel description of interacting proteins by extending the signature descriptor, which has demonstrated success in predicting peptide/protein binding interactions for individual proteins. This descriptor is extended to protein pairs by taking signature products. The signature product is implemented within a support vector machine classifier as a kernel function.'),
(71616, 2005, 'bio', 'DWE: discriminating word enumerator', 'Sumazin, Pavel|Chen, Gengxin|Hata, Naoya|Smith, Andrew D|Zhang, Theresa|Zhang, Michael Q', 'Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA. ps@cs.pdx.edu|Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA. ps@cs.pdx.edu|Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA. ps@cs.pdx.edu|Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA. ps@cs.pdx.edu|Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA. ps@cs.pdx.edu|Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA. ps@cs.pdx.edu', 'United States|United States|United States|United States|United States|United States', 23, 'Algorithms|Amino Acid Motifs|Animals|Binding Sites|Consensus Sequence|Conserved Sequence|Gene Expression Profiling|Humans|Liver|Nuclear Proteins|Promoter Regions, Genetic|Sequence Alignment|Sequence Analysis, Protein|Software|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth471', '15333453', 'Tissue-specific transcription factor binding sites give insight into tissue-specific transcription regulation.'),
(71617, 2005, 'bio', 'HapBlock: haplotype block partitioning and tag SNP selection software using a set of dynamic programming algorithms', 'Zhang, Kui|Qin, Zhaohui|Chen, Ting|Liu, Jun S|Waterman, Michael S|Sun, Fengzhu', 'Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.', 'United States|United States|United States|United States|United States|United States', 92, 'Algorithms|Chromosome Mapping|Expressed Sequence Tags|Genetic Variation|Haplotypes|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bth482', '15333454', 'Recent studies have revealed that linkage disequilibrium (LD) patterns vary across the human genome with some regions of high LD interspersed with regions of low LD. Such LD patterns make it possible to select a set of single nucleotide polymorphism (SNPs, tag SNPs) for genome-wide association studies. We have developed a suite of computer programs to analyze the block-like LD patterns and to select the corresponding tag SNPs. Compared to other programs for haplotype block partitioning and tag SNP selection, our program has several notable features. First, the dynamic programming algorithms implemented are guaranteed to find the block partition with minimum number of tag SNPs for the given criteria of blocks and tag SNPs. Second, both haplotype data and genotype data from unrelated individuals and/or from general pedigrees can be analyzed. Third, several existing measures/criteria for haplotype block partitioning and tag SNP selection have been implemented in the program. Finally, the programs provide flexibility to include specific SNPs (e.g. non-synonymous SNPs) as tag SNPs.'),
(71618, 2005, 'bio', 'Comment on Discrepancies in dbSNP confirmations rates and allele frequency distributions from varying genotyping error rates and patterns', 'Carlson, Christopher S|Reider, Mark J|Nickerson, Deborah A|Eberle, Michael A|Kruglyak, Leonid', 'Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.', 'United States|United States|United States|United States|United States', 6, 'Algorithms|Data Interpretation, Statistical|Databases, Nucleic Acid|Gene Expression Profiling|Gene Frequency|Genotype|Models, Genetic|Models, Statistical|Polymorphism, Single Nucleotide|Quality Control|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Statistical Distributions', 'Comment', '10.1093/bioinformatics/bth492', '15333455', '-'),
(71619, 2005, 'bio', 'SABmark--a benchmark for sequence alignment that covers the entire known fold space', 'Van Walle, Ivo|Lasters, Ignace|Wyns, Lode', 'Department of Ultrastructure, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussel, Belgium. ivwalle@vub.ac.be|Department of Ultrastructure, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussel, Belgium. ivwalle@vub.ac.be|Department of Ultrastructure, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussel, Belgium. ivwalle@vub.ac.be', 'Belgium|Belgium|Belgium', 159, 'Algorithms|Amino Acid Sequence|Benchmarking|Molecular Sequence Data|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth493', '15333456', 'The Sequence Alignment Benchmark (SABmark) provides sets of multiple alignment problems derived from the SCOP classification. These sets, Twilight Zone and Superfamilies, both cover the entire known fold space using sequences with very low to low, and low to intermediate similarity, respectively. In addition, each set has an alternate version in which unalignable but apparently similar sequences are added to each problem.'),
(71620, 2005, 'bio', 'OntologyTraverser: an R package for GO analysis', 'Young, A|Whitehouse, N|Cho, J|Shaw, C', 'Baylor College of Medicine, Department of Molecular and Human Genetics Houston, TX, USA.|Baylor College of Medicine, Department of Molecular and Human Genetics Houston, TX, USA.|Baylor College of Medicine, Department of Molecular and Human Genetics Houston, TX, USA.|Baylor College of Medicine, Department of Molecular and Human Genetics Houston, TX, USA.', 'United States|United States|United States|United States', 28, 'Algorithms|Database Management Systems|Databases, Protein|Documentation|Information Storage and Retrieval|Internet|Natural Language Processing|Phylogeny|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bth495', '15333457', 'Gene Ontology (GO) annotations have become a major tool for analysis of genome-scale experiments. We have created OntologyTraverser--an R package for GO analysis of gene lists. Our system is a major advance over previous work because (1) the system can be installed as an R package, (2) the system uses Java to instantiate the GO structure and the SJava system to integrate R and Java and (3) the system is also deployed as a publicly available web tool.'),
(71621, 2005, 'bio', 'Gene name ambiguity of eukaryotic nomenclatures', 'Chen, Lifeng|Liu, Hongfang|Friedman, Carol', 'Department of BioMedical Informatics, Columbia University New York, NY 10032, USA. lifeng.chen@dbmi.columbia.edu|Department of BioMedical Informatics, Columbia University New York, NY 10032, USA. lifeng.chen@dbmi.columbia.edu|Department of BioMedical Informatics, Columbia University New York, NY 10032, USA. lifeng.chen@dbmi.columbia.edu', 'United States|United States|United States', 0, 'Abstracting and Indexing as Topic|Algorithms|Animals|Artificial Intelligence|Databases, Genetic|Documentation|Eukaryotic Cells|Genes|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Proteins|PubMed|Terminology as Topic', 'Comparative Study', '10.1093/bioinformatics/bth496', '15333458', 'With more and more scientific literature published online, the effective management and reuse of this knowledge has become problematic. Natural language processing (NLP) may be a potential solution by extracting, structuring and organizing biomedical information in online literature in a timely manner. One essential task is to recognize and identify genomic entities in text. Recognition can be accomplished using pattern matching and machine learning. But for identification these techniques are not adequate. In order to identify genomic entities, NLP needs a comprehensive resource that specifies and classifies genomic entities as they occur in text and that associates them with normalized terms and also unique identifiers so that the extracted entities are well defined. Online organism databases are an excellent resource to create such a lexical resource. However, gene name ambiguity is a serious problem because it affects the appropriate identification of gene entities. In this paper, we explore the extent of the problem and suggest ways to address it.'),
(71622, 2005, 'bio', 'A new algorithm for detecting low-complexity regions in protein sequences', 'Shin, Sung W|Kim, Sam M', 'Department of Computer Engineering, Kyungpook National University Daegu 702-701, Korea. swshin@bioinfo.knu.ac.kr|Department of Computer Engineering, Kyungpook National University Daegu 702-701, Korea. swshin@bioinfo.knu.ac.kr', '-|-', 14, 'Algorithms|Amino Acid Sequence|Internet|Models, Chemical|Models, Molecular|Models, Statistical|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/bth497', '15333459', 'Pair-wise alignment of protein sequences and local similarity searches produce many false positives because of compositionally biased regions, also called low-complexity regions (LCRs), of amino acid residues. Masking and filtering such regions significantly improves the reliability of homology searches and, consequently, functional predictions. Most of the available algorithms are based on a statistical approach. We wished to investigate the structural properties of LCRs in biological sequences and develop an algorithm for filtering them.'),
(71623, 2005, 'bio', 'Filtering of ineffective siRNAs and improved siRNA design tool', 'Yiu, S M|Wong, Prudence W H|Lam, T W|Mui, Y C|Kung, H F|Lin, Marie|Cheung, Y T', 'Department of Computer Science, University of Hong Kong, Hong Kong. smyiu@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong. smyiu@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong. smyiu@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong. smyiu@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong. smyiu@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong. smyiu@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong. smyiu@cs.hku.hk', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong', 0, 'Algorithms|Artificial Intelligence|Base Sequence|Benchmarking|Computer-Aided Design|Genetic Engineering|Models, Chemical|Models, Molecular|Molecular Sequence Data|RNA, Small Interfering|Sequence Alignment|Sequence Analysis, RNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth498', '15333460', 'Short interfering RNAs (siRNAs) can be used to suppress gene expression and possess many potential applications in therapy, but how to design an effective siRNA is still not clear. Based on the MPI (Max-Planck-Institute) basic principles, a number of siRNA design tools have been developed recently. The set of candidates reported by these tools is usually large and often contains ineffective siRNAs. In view of this, we initiate the study of filtering ineffective siRNAs.'),
(71624, 2005, 'bio', 'Missing value estimation for DNA microarray gene expression data: local least squares imputation', 'Kim, Hyunsoo|Golub, Gene H|Park, Haesun', 'Department of Computer Science and Engineering, University of Minnesota Twin Cities, 200 Union Street S.E., Minneapolis, MN 55455, USA.|Department of Computer Science and Engineering, University of Minnesota Twin Cities, 200 Union Street S.E., Minneapolis, MN 55455, USA.|Department of Computer Science and Engineering, University of Minnesota Twin Cities, 200 Union Street S.E., Minneapolis, MN 55455, USA.', 'United States|United States|United States', 298, 'Algorithms|Gene Expression Profiling|Least-Squares Analysis|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sample Size|Software', 'Comparative Study', '10.1093/bioinformatics/bth499', '15333461', 'Gene expression data often contain missing expression values. Effective missing value estimation methods are needed since many algorithms for gene expression data analysis require a complete matrix of gene array values. In this paper, imputation methods based on the least squares formulation are proposed to estimate missing values in the gene expression data, which exploit local similarity structures in the data as well as least squares optimization process.'),
(71625, 2005, 'bio', 'Recombination Analysis Tool (RAT): a program for the high-throughput detection of recombination', 'Etherington, Graham J|Dicks, Jo|Roberts, Ian N', 'Department of Food Safety Science, Institute of Food Research Norwich Research Park, Colney Lane, Norwich NR4 7HA, UK. Graham.Etherington@bbsrc.ac.uk|Department of Food Safety Science, Institute of Food Research Norwich Research Park, Colney Lane, Norwich NR4 7HA, UK. Graham.Etherington@bbsrc.ac.uk|Department of Food Safety Science, Institute of Food Research Norwich Research Park, Colney Lane, Norwich NR4 7HA, UK. Graham.Etherington@bbsrc.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 80, 'DNA, Viral|Genome, Viral|HIV-1|Recombination, Genetic|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth500', '15333462', 'Recombination can be a prevailing drive in shaping genome evolution. RAT (Recombination Analysis Tool) is a Java-based tool for investigating recombination events in any number of aligned sequences (protein or DNA) of any length (short viral sequences to full genomes). It is an uncomplicated and intuitive application and allows the user to view only the regions of sequence alignments they are interested in.'),
(71626, 2005, 'bio', 'Dual-genome primer design for construction of DNA microarrays', 'Andersson, Anders|Bernander, Rolf|Nilsson, Peter', 'Department of Biotechnology, KTH-Royal Institute of Technology, SE-106 91 Stockholm, Sweden. anders.andersson@biotech.kth.se|Department of Biotechnology, KTH-Royal Institute of Technology, SE-106 91 Stockholm, Sweden. anders.andersson@biotech.kth.se|Department of Biotechnology, KTH-Royal Institute of Technology, SE-106 91 Stockholm, Sweden. anders.andersson@biotech.kth.se', 'Sweden|Sweden|Sweden', 16, 'Algorithms|Chromosome Mapping|Computer-Aided Design|DNA Primers|Genome, Archaeal|Oligonucleotide Array Sequence Analysis|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA|Software|Sulfolobus solfataricus', 'Evaluation Studies', '10.1093/bioinformatics/bti001', '15333463', 'Microarray experiments using probes covering a whole transcriptome are expensive to initiate, and a major part of the costs derives from synthesizing gene-specific PCR primers or hybridization probes. The high costs may force researchers to limit their studies to a single organism, although comparing gene expression in different species would yield valuable information.'),
(71627, 2005, 'bio', 'ProViz: protein interaction visualization and exploration', 'Iragne, Florian|Nikolski, Macha|Mathieu, Bertrand|Auber, David|Sherman, David', 'LaBRI UMR 5800, Université Bordeaux 1 351 cours de la Libération, 33405 Talence Cedex, France.|LaBRI UMR 5800, Université Bordeaux 1 351 cours de la Libération, 33405 Talence Cedex, France.|LaBRI UMR 5800, Université Bordeaux 1 351 cours de la Libération, 33405 Talence Cedex, France.|LaBRI UMR 5800, Université Bordeaux 1 351 cours de la Libération, 33405 Talence Cedex, France.|LaBRI UMR 5800, Université Bordeaux 1 351 cours de la Libération, 33405 Talence Cedex, France.', 'France|France|France|France|France', 79, 'Computer Graphics|Databases, Protein|Documentation|Gene Expression Regulation|Information Storage and Retrieval|Models, Biological|Protein Interaction Mapping|Signal Transduction|Software|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth494', '15347570', 'ProViz is a tool for the visualization of protein-protein interaction networks, developed by the IntAct European project. It provides facilities for navigating in large graphs and exploring biologically relevant features, and adopts emerging standards such as GO and PSI-MI.'),
(71628, 2005, 'bio', 'BarleyExpress: a web-based submission tool for enriched microarray database annotations', 'Tang, Xiaoyun|Shen, Lishuang|Dickerson, Julie A', 'Electrical and Computer Engineering Department, Iowa State University, Ames, IA 50011-3060, USA.|Electrical and Computer Engineering Department, Iowa State University, Ames, IA 50011-3060, USA.|Electrical and Computer Engineering Department, Iowa State University, Ames, IA 50011-3060, USA.', 'United States|United States|United States', 6, 'Database Management Systems|Databases, Genetic|Documentation|Gene Expression Profiling|Information Storage and Retrieval|Internet|Natural Language Processing|Oligonucleotide Array Sequence Analysis|Plant Proteins|Software|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bti002', '15347571', 'BarleyExpress is a web-based microarray experiment data submission tool for BarleyBase, a public data resource of Affymetrix GeneChip data for plants. BarleyExpress uses the Plant Ontology vocabularies and enhances the MIAME guidelines to standardize the annotation of microarray gene expression experiments. In addition, BarleyExpress provides explicit support for factorial experiment design and template loading methods to ease the submission process for large experiments.'),
(71629, 2005, 'bio', 'A more efficient search strategy for aging genes based on connectivity', 'Ferrarini, Luca|Bertelli, Luca|Feala, Jacob|McCulloch, Andrew D|Paternostro, Giovanni', 'The Burnham Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA.|The Burnham Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA.|The Burnham Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA.|The Burnham Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA.|The Burnham Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA.', 'United States|United States|United States|United States|United States', 43, 'Aging|Computer Simulation|Evolution, Molecular|Gene Expression Profiling|Gene Expression Regulation|Genetics, Population|Models, Genetic|Models, Statistical|Mutation|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/bti004', '15347572', 'Many aging genes have been found from unbiased screens in model organisms. Genetic interventions promoting longevity are usually quantitative, while in many other biological fields (e.g. development) null mutations alone have been very informative. Therefore, in the case of aging the task is larger and the need for a more efficient genetic search strategy is especially strong.'),
(71630, 2005, 'bio', 'SNPbox: a modular software package for large-scale primer design', 'Weckx, Stefan|De Rijk, Peter|Van Broeckhoven, Christine|Del-Favero, Jurgen', 'Department of Molecular Genetics , Bioinformatics Unit, Flanders Interuniversity Institute for Biotechnology, University of Antwerp, B-2610 Antwerpen, Belgium.|Department of Molecular Genetics , Bioinformatics Unit, Flanders Interuniversity Institute for Biotechnology, University of Antwerp, B-2610 Antwerpen, Belgium.|Department of Molecular Genetics , Bioinformatics Unit, Flanders Interuniversity Institute for Biotechnology, University of Antwerp, B-2610 Antwerpen, Belgium.|Department of Molecular Genetics , Bioinformatics Unit, Flanders Interuniversity Institute for Biotechnology, University of Antwerp, B-2610 Antwerpen, Belgium.', 'Belgium|Belgium|Belgium|Belgium', 24, 'Algorithms|DNA Mutational Analysis|DNA Primers|Polymerase Chain Reaction|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti006', '15347573', 'We developed a modular software package SNPbox that automates and standardizes the generation of PCR primers and is used in the strategy for constructing single nucleotide polymorphisms (SNPs) maps. In this strategy, the focus of primer design can be either on the validation of annotated public SNPs or on the SNP discovery in exon regions or extended genomic regions, both by resequencing. SNPbox relies on Primer3 for the primer design and combines this program with other publicly available software tools such as BLAST, Spidey and RepeatMasker, and newly developed algorithms. Primer conditions were chosen such that PCR amplifications are uniform for each PCR amplicon facilitating the use of high-throughput genetic platforms. SNPbox can also be used for the design of primer sets for mutation analysis, STR marker genotyping and microarray oligo design. Of the 2500 primer sets designed by SNPbox, 95% successfully amplified genomic DNA under uniform PCR conditions.'),
(71631, 2005, 'bio', 'Detecting overlapping coding sequences with pairwise alignments', 'Firth, Andrew E|Brown, Chris M', 'Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, New Zealand.|Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, New Zealand.', 'New Zealand|New Zealand', 34, 'Algorithms|Computer Simulation|Conserved Sequence|DNA Mutational Analysis|Genes, Overlapping|Models, Genetic|Models, Statistical|Open Reading Frames|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/bti007', '15347574', 'Overlapping gene coding sequences (CDSs) are particularly common in viruses but also occur in more complex genomes. Detecting such genes with conventional gene-finding algorithms can be difficult for several reasons. If an overlapping CDS is on the same read-strand as a known CDS, then there may not be a distinct promoter or mRNA. Furthermore, the constraints imposed by double-coding can result in atypical codon biases. However, these same constraints lead to particular mutation patterns that may be detectable in sequence alignments.'),
(71632, 2005, 'bio', 'Evaluating putative chimeric sequences from PCR-amplified products', 'Gonzalez, Juan M|Zimmermann, Johannes|Saiz-Jimenez, Cesareo', 'Instituto de Recursos Naturales y Agrobiologia, CSIC Apartado 1052, 41080 Sevilla, Spain. jmgrau@irnase.csic.es|Instituto de Recursos Naturales y Agrobiologia, CSIC Apartado 1052, 41080 Sevilla, Spain. jmgrau@irnase.csic.es|Instituto de Recursos Naturales y Agrobiologia, CSIC Apartado 1052, 41080 Sevilla, Spain. jmgrau@irnase.csic.es', 'Spain|Spain|Spain', 71, 'Algorithms|Base Sequence|Chimera|Molecular Sequence Data|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti008', '15347575', 'PCR amplification of highly homologous genes from complex DNA mixtures is known to generate a significant proportion of chimeric sequences. Ribosomal RNA genes are used for microbial species detection and identification in natural environments, and current assessments of microbial diversity are based on these sequences. Thus, chimeric sequences could lead to the discovery of non-existent microbial species and false diversity estimates.'),
(71633, 2005, 'bio', 'easyLINKAGE: a PERL script for easy and automated two-/multi-point linkage analyses', 'Lindner, Tom H|Hoffmann, K', 'Division of Nephrology, Department of Medicine, Medical University Clinic at the University of Würzburg, Würzburg, Germany. tom.linder@mail.uni-wuerzburg.de|Division of Nephrology, Department of Medicine, Medical University Clinic at the University of Würzburg, Würzburg, Germany. tom.linder@mail.uni-wuerzburg.de', 'Germany|Germany', 144, 'Chromosome Mapping|Computer Graphics|Computer Simulation|DNA Mutational Analysis|Models, Genetic|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti009', '15347576', 'We have generated the program easyLINKAGE that combines automated setup and performance of linkage analyses and simulation under an easy to handle graphical user interface for Microsoft Windows 2000/XP and standard UNIX systems. The program package supports two-point linkage analyses (FastLink v4.1 and SPLink v1.09), multi-point linkage analyses [GENEHUNTER v2.1, GENEHUNTER-PLUS with the emendation by Kong and Cox v1.2 (allele sharing modelling)] and the simulation package SLINK v2.65, and provides genome-wide as well as chromosomal postscript plots of LOD scores, NPL scores, P-values and other parameters.'),
(71634, 2005, 'bio', 'Tracker: continuous HMMER and BLAST searching', 'Marchin, Madelaine|Kelly, Paul T|Fang, Jianwen', 'Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66045, USA.|Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66045, USA.|Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66045, USA.', 'United States|United States|United States', 0, 'Database Management Systems|Databases, Genetic|Documentation|Electronic Mail|Information Storage and Retrieval|Internet|Natural Language Processing|PubMed|Sequence Alignment|Sequence Analysis|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bti012', '15347577', 'Tracker is a web-based email alert system for monitoring protein database searches using HMMER and Blast-P, nucleotide searches using Blast-N and literature searches of the PubMed database. Users submit searches via a web-based interface. Searches are saved and run against updated databases to alert users about new information. If there are new results from the saved searches, users will be notified by email and will then be able to access results and link to additional information on the NCBI website. Tracker supports Boolean AND/OR operations on HMMER and BLASTP result sets to allow users to broaden or narrow protein searches.'),
(71635, 2005, 'bio', 'The SSEA server for protein secondary structure alignment', 'Fontana, Paolo|Bindewald, Eckart|Toppo, Stefano|Velasco, Riccardo|Valle, Giorgio|Tosatto, Silvio C E', 'Istituto Agrario di San Michele allAdige, via E. Mach 1, 38010 S. Michele allAdige (TN), Italy.|Istituto Agrario di San Michele allAdige, via E. Mach 1, 38010 S. Michele allAdige (TN), Italy.|Istituto Agrario di San Michele allAdige, via E. Mach 1, 38010 S. Michele allAdige (TN), Italy.|Istituto Agrario di San Michele allAdige, via E. Mach 1, 38010 S. Michele allAdige (TN), Italy.|Istituto Agrario di San Michele allAdige, via E. Mach 1, 38010 S. Michele allAdige (TN), Italy.|Istituto Agrario di San Michele allAdige, via E. Mach 1, 38010 S. Michele allAdige (TN), Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 36, 'Algorithms|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti013', '15347578', 'We present a web server that computes alignments of protein secondary structures. The server supports both performing pairwise alignments and searching a secondary structure against a library of domain folds. It can calculate global and local secondary structure element alignments. A combination of local and global alignment steps can be used to search for domains inside the query sequence or help in the discrimination of novel folds. Both the SCOP and PDB fold libraries, clustered at 95 and 40% sequence identity, are available for alignment.'),
(71636, 2005, 'bio', 'Genome Properties: a system for the investigation of prokaryotic genetic content for microbiology, genome annotation and comparative genomics', 'Haft, Daniel H|Selengut, Jeremy D|Brinkac, Lauren M|Zafar, Nikhat|White, Owen', 'The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA.|The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA.|The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA.|The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA.|The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA.', 'United States|United States|United States|United States|United States', 0, 'Chromosome Mapping|Database Management Systems|Databases, Genetic|Documentation|Gene Expression Profiling|Gene Expression Regulation|Genomics|Information Storage and Retrieval|Microbiological Techniques|Natural Language Processing|Prokaryotic Cells|Proteome|Signal Transduction|Software|User-Computer Interface|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/bti015', '15347579', 'The presence or absence of metabolic pathways and structures provide a context that makes protein annotation far more reliable. Compiling such information across microbial genomes improves the functional classification of proteins and provides a valuable resource for comparative genomics.'),
(71637, 2005, 'bio', 'SNAP: workbench management tool for evolutionary population genetic analysis', 'Price, Eric W|Carbone, Ignazio', 'Center for Integrated Fungal Research, Department of Plant Pathology, North Carolina State University, Raleigh, NC 27695, USA.|Center for Integrated Fungal Research, Department of Plant Pathology, North Carolina State University, Raleigh, NC 27695, USA.', 'United States|United States', 118, 'Computer Simulation|DNA Mutational Analysis|Evolution, Molecular|Genetic Variation|Genetics, Population|Models, Genetic|Models, Statistical|Sequence Alignment|Sequence Analysis, DNA|Software|Systems Integration', 'Journal Article', '10.1093/bioinformatics/bti003', '15353448', 'The reconstruction of population processes from DNA sequence variation requires the coordinated implementation of several coalescent-based methods, each bound by specific assumptions and limitations. In practice, the application of these coalescent-based methods for parameter estimation is difficult because they make strict assumptions that must be verified a priori and their parameter-rich nature makes the estimation of all model parameters very complex and computationally intensive. A further complication is their distribution as console applications that require the user to navigate through console menus or specify complex command-line arguments. To facilitate the implementation of these coalescent-based tools we developed SNAP Workbench, a Java program that manages and coordinates a series of programs. The workbench enhances population parameter estimation by ensuring that the assumptions and program limitations of each method are met and by providing a step-by-step methodology for examining population processes that integrates both summary-statistic methods and coalescent-based population genetic models.'),
(71638, 2005, 'bio', 'Capturing biological information with class-responsibility-collaboration cards', 'Shegogue, Daniel|Zheng, W Jim', 'Department of Biostatistics, Bioinformatics and Epidemiology, 135 Cannon Street, P.O. Box 250835, Charleston, SC 29425, USA.|Department of Biostatistics, Bioinformatics and Epidemiology, 135 Cannon Street, P.O. Box 250835, Charleston, SC 29425, USA.', 'United States|United States', 2, 'Computational Biology|Database Management Systems|Databases, Protein|Documentation|Information Storage and Retrieval|Programming Languages|Proteins|Software|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bti005', '15353449', 'Class-responsibility-collaboration (CRC) cards have been used extensively in the software industry for defining complex object-oriented software requirements. We have adapted this tool to capture information about biological components, collaborators and responsibilities within these collaborations, which is not captured by current annotation tools. CRC cards should provide a common ground that will facilitate communication between biologist and computer scientists.'),
(71639, 2005, 'bio', 'iPfam: visualization of protein-protein interactions in PDB at domain and amino acid resolutions', 'Finn, Robert D|Marshall, Mhairi|Bateman, Alex', 'The Wellcome Trust Sanger Institute, The Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK. rdf@sanger.ac.uk|The Wellcome Trust Sanger Institute, The Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK. rdf@sanger.ac.uk|The Wellcome Trust Sanger Institute, The Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK. rdf@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 247, 'Amino Acids|Binding Sites|Computer Simulation|Databases, Protein|Internet|Models, Chemical|Models, Molecular|Protein Binding|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti011', '15353450', 'There are many resources that contain information about binary interactions between proteins. However, protein interactions are defined by only a subset of residues in any protein. We have implemented a web resource that allows the investigation of protein interactions in the Protein Data Bank structures at the level of Pfam domains and amino acid residues. This detailed knowledge relies on the fact that there are a large number of multidomain proteins and protein complexes being deposited in the structure databases. The resource called iPfam is hosted within the Pfam UK website. Most resources focus on the interactions between proteins, iPfam includes these as well as interactions between domains in a single protein.'),
(71640, 2005, 'bio', 'A Bayesian approach to reconstructing genetic regulatory networks with hidden factors', 'Beal, Matthew J|Falciani, Francesco|Ghahramani, Zoubin|Rangel, Claudia|Wild, David L', 'Department of Computer Science & Engineering, State University of New York at Buffalo, 201 Bell Hall, Buffalo, NY 14260-2000, USA.|Department of Computer Science & Engineering, State University of New York at Buffalo, 201 Bell Hall, Buffalo, NY 14260-2000, USA.|Department of Computer Science & Engineering, State University of New York at Buffalo, 201 Bell Hall, Buffalo, NY 14260-2000, USA.|Department of Computer Science & Engineering, State University of New York at Buffalo, 201 Bell Hall, Buffalo, NY 14260-2000, USA.|Department of Computer Science & Engineering, State University of New York at Buffalo, 201 Bell Hall, Buffalo, NY 14260-2000, USA.', 'United States|United States|United States|United States|United States', 216, 'Bayes Theorem|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Markov Chains|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Signal Transduction|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti014', '15353451', 'We have used state-space models (SSMs) to reverse engineer transcriptional networks from highly replicated gene expression profiling time series data obtained from a well-established model of T cell activation. SSMs are a class of dynamic Bayesian networks in which the observed measurements depend on some hidden state variables that evolve according to Markovian dynamics. These hidden variables can capture effects that cannot be directly measured in a gene expression profiling experiment, for example: genes that have not been included in the microarray, levels of regulatory proteins, the effects of mRNA and protein degradation, etc.'),
(71641, 2005, 'bio', 'VizRank: finding informative data projections in functional genomics by machine learning', 'Leban, Gregor|Bratko, Ivan|Petrovic, Uros|Curk, Tomaz|Zupan, Blaz', 'University of Ljubljana, Faculty of Computer and Information Science, Ljubljana, Slovenia.|University of Ljubljana, Faculty of Computer and Information Science, Ljubljana, Slovenia.|University of Ljubljana, Faculty of Computer and Information Science, Ljubljana, Slovenia.|University of Ljubljana, Faculty of Computer and Information Science, Ljubljana, Slovenia.|University of Ljubljana, Faculty of Computer and Information Science, Ljubljana, Slovenia.', 'Slovenia|Slovenia|Slovenia|Slovenia|Slovenia', 30, 'Algorithms|Artificial Intelligence|Computer Graphics|Gene Expression Profiling|Genomics|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae Proteins|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti016', '15358614', 'VizRank is a tool that finds interesting two-dimensional projections of class-labeled data. When applied to multi-dimensional functional genomics datasets, VizRank can systematically find relevant biological patterns.'),
(71642, 2005, 'bio', 'Human-Mouse Gene Searcher: a tool to assist discovery of malformation-associated genes by using phenotype databases', 'Bradford, Ian|Winter, Robin|Evans, Carl|Bard, Jonathan', 'Institute of Child Health, 30 Guilford Street, London WC1N 1EH, UK. i.bradford@ich.ucl.ac.uk|Institute of Child Health, 30 Guilford Street, London WC1N 1EH, UK. i.bradford@ich.ucl.ac.uk|Institute of Child Health, 30 Guilford Street, London WC1N 1EH, UK. i.bradford@ich.ucl.ac.uk|Institute of Child Health, 30 Guilford Street, London WC1N 1EH, UK. i.bradford@ich.ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 2, 'Animals|Computer Graphics|Congenital Abnormalities|DNA Mutational Analysis|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Humans|Information Storage and Retrieval|Internet|Mice|Phenotype|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti017', '15358615', 'An open-access World Wide Web application has been developed which enables the cross-linking of anatomical data on the phenotypic manifestations of human and mouse malformation syndromes to data on gene function and/or expression patterns in the mouse GXD database. Ultimately, the system has been designed to assist biologists in the process of discovering hitherto unidentified malformation genes. More specifically, it facilitates search from the phenotypic level.'),
(71643, 2005, 'bio', 'Simulation tools for biochemical networks: evaluation of performance and usability', 'Pettinen, Antti|Aho, Tommi|Smolander, Olli-Pekka|Manninen, Tiina|Saarinen, Antti|Taattola, Kaisa-Leena|Yli-Harja, Olli|Linne, Marja-Leena', 'Institute of Signal Processing, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. antti.pettinen@tut.fi|Institute of Signal Processing, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. antti.pettinen@tut.fi|Institute of Signal Processing, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. antti.pettinen@tut.fi|Institute of Signal Processing, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. antti.pettinen@tut.fi|Institute of Signal Processing, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. antti.pettinen@tut.fi|Institute of Signal Processing, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. antti.pettinen@tut.fi|Institute of Signal Processing, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. antti.pettinen@tut.fi|Institute of Signal Processing, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. antti.pettinen@tut.fi', 'Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland', 35, 'Animals|Cell Physiological Phenomena|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Biological|Models, Statistical|Signal Transduction|Software|Software Validation|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bti018', '15358616', 'Simulation of dynamic biochemical systems is receiving considerable attention due to increasing availability of experimental data of complex cellular functions. Numerous simulation tools have been developed for numerical simulation of the behavior of a system described in mathematical form. However, there exist only a few evaluation studies of these tools. Knowledge of the properties and capabilities of the simulation tools would help bioscientists in building models based on experimental data.'),
(71644, 2005, 'bio', 'Discovery of stable and significant binding motif pairs from PDB complexes and protein interaction datasets', 'Li, Haiquan|Li, Jinyan', 'Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. haiquan@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. haiquan@i2r.a-star.edu.sg', 'Singapore|Singapore', 0, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Binding Sites|Databases, Protein|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bti019', '15374856', 'Discovery of binding sites is important in the study of protein-protein interactions. In this paper, we introduce stable and significant motif pairs to model protein-binding sites. The stability is the patterns resistance to some transformation. The significance is the unexpected frequency of occurrence of the pattern in a sequence dataset comprising known interacting protein pairs. Discovery of stable motif pairs is an iterative process, undergoing a chain of changing but converging patterns. Determining the starting point for such a chain is an interesting problem. We use a protein complex dataset extracted from the Protein Data Bank to help in identifying those starting points, so that the computational complexity of the problem is much released.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71645, 2005, 'bio', 'RAP: a new computer program for de novo identification of repeated sequences in whole genomes', 'Campagna, Davide|Romualdi, Chiara|Vitulo, Nicola|Del Favero, Micky|Lexa, Matej|Cannata, Nicola|Valle, Giorgio', 'CRIBI, Università degli Studi di Padova via Ugo Bassi 58b, I-35121 Padova, Italy.|CRIBI, Università degli Studi di Padova via Ugo Bassi 58b, I-35121 Padova, Italy.|CRIBI, Università degli Studi di Padova via Ugo Bassi 58b, I-35121 Padova, Italy.|CRIBI, Università degli Studi di Padova via Ugo Bassi 58b, I-35121 Padova, Italy.|CRIBI, Università degli Studi di Padova via Ugo Bassi 58b, I-35121 Padova, Italy.|CRIBI, Università degli Studi di Padova via Ugo Bassi 58b, I-35121 Padova, Italy.|CRIBI, Università degli Studi di Padova via Ugo Bassi 58b, I-35121 Padova, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 26, 'Algorithms|Animals|Caenorhabditis elegans|Chromosome Mapping|DNA|Pattern Recognition, Automated|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti039', '15374857', 'DNA repeats are a common feature of most genomic sequences. Their de novo identification is still difficult despite being a crucial step in genomic analysis and oligonucleotides design. Several efficient algorithms based on word counting are available, but too short words decrease specificity while long words decrease sensitivity, particularly in degenerated repeats.'),
(71646, 2005, 'bio', 'Expression-based monitoring of transcription factor activity: the TELiS database', 'Cole, Steve W|Yan, Weihong|Galic, Zoran|Arevalo, Jesusa|Zack, Jerome A', 'UCLA Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1678, USA. coles@ucla.edu|UCLA Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1678, USA. coles@ucla.edu|UCLA Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1678, USA. coles@ucla.edu|UCLA Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1678, USA. coles@ucla.edu|UCLA Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1678, USA. coles@ucla.edu', 'United States|United States|United States|United States|United States', 118, 'Algorithms|Computer Systems|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Promoter Regions, Genetic|Proteome|Sequence Analysis, Protein|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti038', '15374858', 'In microarray studies it is often of interest to identify upstream transcription control pathways mediating observed changes in gene expression. The Transcription Element Listening System (TELiS) combines sequence-based analysis of gene regulatory regions with statistical prevalence analyses to identify transcription-factor binding motifs (TFBMs) that are over-represented among the promoters of up- or down-regulated genes. Efficiency is maximized by decomposing the problem into two steps: (1) a priori compilation of prevalence matrices specifying the number of putative binding sites for a variety of transcription factors in promoters from all genes assayed by a given microarray, and (2) real-time statistical analysis of pre-compiled prevalence matrices to identify TFBMs that are over- or under-represented in promoters of differentially expressed genes. The interlocking JAVA applications namely, PromoterScan and PromoterStats carry out these tasks, and together constitute the TELiS database for reverse inference of transcription factor activity.'),
(71647, 2005, 'bio', 'Online synonymous codon usage analyses with the ade4 and seqinR packages', 'Charif, D|Thioulouse, J|Lobry, J R|Perrière, G', 'Laboratoire de Biométrie et Biologie Evolutive-CNRS UMR 5558, and INRIA Helix project, Université Claude Bernard-Lyon I 43 bd. du 11 Novembre 1918, F-69622 Villeurbanne cedex, France.|Laboratoire de Biométrie et Biologie Evolutive-CNRS UMR 5558, and INRIA Helix project, Université Claude Bernard-Lyon I 43 bd. du 11 Novembre 1918, F-69622 Villeurbanne cedex, France.|Laboratoire de Biométrie et Biologie Evolutive-CNRS UMR 5558, and INRIA Helix project, Université Claude Bernard-Lyon I 43 bd. du 11 Novembre 1918, F-69622 Villeurbanne cedex, France.|Laboratoire de Biométrie et Biologie Evolutive-CNRS UMR 5558, and INRIA Helix project, Université Claude Bernard-Lyon I 43 bd. du 11 Novembre 1918, F-69622 Villeurbanne cedex, France.', 'France|France|France|France', 57, 'Algorithms|Codon|Computer Graphics|Online Systems|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti037', '15374859', 'Correspondence analysis of codon usage data is a widely used method in sequence analysis, but the variability in amino acid composition between proteins is a confounding factor when one wants to analyse synonymous codon usage variability. A simple and natural way to cope with this problem is to use within-group correspondence analysis. There is, however, no user-friendly implementation of this method available for genomic studies. Our motivation was to provide to the community a Web facility to easily study synonymous codon usage on a subset of data available in public genomic databases.'),
(71648, 2005, 'bio', 'Reliability analysis of microarray data using fuzzy c-means and normal mixture modeling based classification methods', 'Asyali, Musa H|Alci, Musa', 'Department of Biostatistics, Epidemiology and Scientific Computing, King Faisal Specialist Hospital and Research Center PO Box 3354, MBC-03, Riyadh 11211, Saudi Arabia. asyali@kfshrc.edu.sa|Department of Biostatistics, Epidemiology and Scientific Computing, King Faisal Specialist Hospital and Research Center PO Box 3354, MBC-03, Riyadh 11211, Saudi Arabia. asyali@kfshrc.edu.sa', 'Saudi Arabia|Saudi Arabia', 33, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computer Simulation|Fuzzy Logic|Gene Expression Profiling|Models, Genetic|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bti036', '15374860', 'A serious limitation in microarray analysis is the unreliability of the data generated from low signal intensities. Such data may produce erroneous gene expression ratios and cause unnecessary validation or post-analysis follow-up tasks. Therefore, the elimination of unreliable signal intensities will enhance reproducibility and reliability of gene expression ratios produced from microarray data. In this study, we applied fuzzy c-means (FCM) and normal mixture modeling (NMM) based classification methods to separate microarray data into reliable and unreliable signal intensity populations.'),
(71649, 2005, 'bio', 'tPatternHunter: gapped, fast and sensitive translated homology search', 'Kisman, Derek|Li, Ming|Ma, Bin|Wang, Li', 'Bioinformatics Solutions Inc. 145 Columbia St West, Waterloo, Ontario, Canada N2L 3L2.|Bioinformatics Solutions Inc. 145 Columbia St West, Waterloo, Ontario, Canada N2L 3L2.|Bioinformatics Solutions Inc. 145 Columbia St West, Waterloo, Ontario, Canada N2L 3L2.|Bioinformatics Solutions Inc. 145 Columbia St West, Waterloo, Ontario, Canada N2L 3L2.', 'Canada|Canada|Canada|Canada', 14, 'Algorithms|Conserved Sequence|Protein Biosynthesis|Sequence Alignment|Sequence Analysis|Sequence Homology|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti035', '15374861', 'New ideas, spaced seeds and gapped alignment before 6-frame translation are implemented for translated homology search in tPatternHunter. The new software compares favorably with tBLASTx.'),
(71650, 2005, 'bio', 'A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis', 'Statnikov, Alexander|Aliferis, Constantin F|Tsamardinos, Ioannis|Hardin, Douglas|Levy, Shawn', 'Department of Biomedical Informatics, Vanderbilt University Nashville, TN, USA. alexander.statnikov@vanderbilt.edu|Department of Biomedical Informatics, Vanderbilt University Nashville, TN, USA. alexander.statnikov@vanderbilt.edu|Department of Biomedical Informatics, Vanderbilt University Nashville, TN, USA. alexander.statnikov@vanderbilt.edu|Department of Biomedical Informatics, Vanderbilt University Nashville, TN, USA. alexander.statnikov@vanderbilt.edu|Department of Biomedical Informatics, Vanderbilt University Nashville, TN, USA. alexander.statnikov@vanderbilt.edu', 'United States|United States|United States|United States|United States', 590, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Cluster Analysis|Diagnosis, Computer-Assisted|Gene Expression Profiling|Genetic Predisposition to Disease|Genetic Testing|Humans|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bti033', '15374862', 'Cancer diagnosis is one of the most important emerging clinical applications of gene expression microarray technology. We are seeking to develop a computer system for powerful and reliable cancer diagnostic model creation based on microarray data. To keep a realistic perspective on clinical applications we focus on multicategory diagnosis. To equip the system with the optimum combination of classifier, gene selection and cross-validation methods, we performed a systematic and comprehensive evaluation of several major algorithms for multicategory classification, several gene selection methods, multiple ensemble classifier methods and two cross-validation designs using 11 datasets spanning 74 diagnostic categories and 41 cancer types and 12 normal tissue types.'),
(71651, 2005, 'bio', 'A semiparametric approach for marker gene selection based on gene expression data', 'Guan, Zhong|Zhao, Hongyu', 'Department of Mathematical Sciences, Indiana University South Bend South Bend, IN 46634, USA.|Department of Mathematical Sciences, Indiana University South Bend South Bend, IN 46634, USA.', 'India|India', 24, 'Biomarkers, Tumor|Data Interpretation, Statistical|Diagnosis, Computer-Assisted|Gene Expression Profiling|Genetic Markers|Genetic Predisposition to Disease|Genetic Testing|Humans|Leukemia|Models, Genetic|Models, Statistical|Neoplasm Proteins|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bti032', '15374863', 'Identification of differentially expressed genes is a major issue in gene expression data analysis and selection of marker genes is critical in tumor classification using gene expression data. In this paper, we propose a semiparametric two-sample test to identify both differentially expressed genes and select marker genes for sample classification.'),
(71652, 2005, 'bio', 'ESTminer: a Web interface for mining EST contig and cluster databases', 'Huang, Yecheng|Pumphrey, Janie|Gingle, Alan R', 'Center for Applied Genetic Technologies, University of Georgia 111 Riverbend Road, Athens, GA 30602, USA.|Center for Applied Genetic Technologies, University of Georgia 111 Riverbend Road, Athens, GA 30602, USA.|Center for Applied Genetic Technologies, University of Georgia 111 Riverbend Road, Athens, GA 30602, USA.', 'Georgia|Georgia|Georgia', 4, 'Algorithms|Cluster Analysis|Contig Mapping|Database Management Systems|Databases, Nucleic Acid|Expressed Sequence Tags|Information Storage and Retrieval|Internet|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti030', '15374864', 'ESTminer is a Web application and database schema for interactive mining of expressed sequence tag (EST) contig and cluster datasets. The Web interface contains a query frame that allows the selection of contigs/clusters with specific cDNA library makeup or a threshold number of members. The results are displayed as color-coded tree nodes, where the color indicates the fractional size of each cDNA library component. The nodes are expandable, revealing library statistics as well as EST or contig members, with links to sequence data, GenBank records or user configurable links. Also, the interface allows queries within queries where the result set of a query is further filtered by the subsequent query.'),
(71653, 2005, 'bio', 'Statistical methods of translating microarray data into clinically relevant diagnostic information in colorectal cancer', 'Kim, Byung Soo|Kim, Inyoung|Lee, Sunho|Kim, Sangcheol|Rha, Sun Young|Chung, Hyun Cheol', 'Department of Applied Statistics, College of Medicine, Yonsei University Seoul, South Korea. bskim@yonsei.ac.kr|Department of Applied Statistics, College of Medicine, Yonsei University Seoul, South Korea. bskim@yonsei.ac.kr|Department of Applied Statistics, College of Medicine, Yonsei University Seoul, South Korea. bskim@yonsei.ac.kr|Department of Applied Statistics, College of Medicine, Yonsei University Seoul, South Korea. bskim@yonsei.ac.kr|Department of Applied Statistics, College of Medicine, Yonsei University Seoul, South Korea. bskim@yonsei.ac.kr|Department of Applied Statistics, College of Medicine, Yonsei University Seoul, South Korea. bskim@yonsei.ac.kr', '-|-|-|-|-|-', 21, 'Adult|Aged|Aged, 80 and over|Biomarkers, Tumor|Colorectal Neoplasms|Data Interpretation, Statistical|Diagnosis, Computer-Assisted|Female|Gene Expression Profiling|Genetic Markers|Genetic Predisposition to Disease|Genetic Testing|Humans|Male|Middle Aged|Models, Genetic|Models, Statistical|Neoplasm Proteins|Reproducibility of Results|Sensitivity and Specificity', 'Clinical Trial', '10.1093/bioinformatics/bti029', '15374865', 'It is a common practice in cancer microarray experiments that a normal tissue is collected from the same individual from whom the tumor tissue was taken. The indirect design is usually adopted for the experiment that uses a common reference RNA hybridized both to normal and tumor tissues. However, it is often the case that the test material is not large enough for the experimenter to extract enough RNA to conduct the microarray experiment. Hence, collecting n cases does not necessarily end up with a matched pair sample of size n. Instead we usually have a matched pair sample of size n1, and two independent samples of sizes n2 and n3, respectively, for reference versus normal tissue only and reference versus tumor tissue only hybridizations (n=n1 + n2 + n3). Standard statistical methods need to be modified and new statistical procedures are developed for analyzing this mixed dataset.'),
(71654, 2005, 'bio', 'SPAAN: a software program for prediction of adhesins and adhesin-like proteins using neural networks', 'Sachdeva, Gaurav|Kumar, Kaushal|Jain, Preti|Ramachandran, Srinivasan', 'G.N. Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology Mall Road, Delhi 110 007, India.|G.N. Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology Mall Road, Delhi 110 007, India.|G.N. Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology Mall Road, Delhi 110 007, India.|G.N. Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology Mall Road, Delhi 110 007, India.', 'India|India|India|India', 95, 'Adhesins, Bacterial|Algorithms|Animals|Humans|Models, Biological|Models, Chemical|Models, Statistical|Neural Networks (Computer)|Protein Isoforms|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti028', '15374866', 'The adhesion of microbial pathogens to host cells is mediated by adhesins. Experimental methods used for characterizing adhesins are time-consuming and demand large resources. The availability of specialized software can rapidly aid experimenters in simplifying this problem. We have employed 105 compositional properties and artificial neural networks to develop SPAAN, which predicts the probability of a protein being an adhesin (Pad).'),
(71655, 2005, 'bio', 'Improving genome annotations using phylogenetic profile anomaly detection', 'Mikkelsen, Tarjei S|Galagan, James E|Mesirov, Jill P', 'The Eli & Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University 320 Charles Street, Cambridge, MA 02141, USA. tarjei@broad.mit.edu|The Eli & Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University 320 Charles Street, Cambridge, MA 02141, USA. tarjei@broad.mit.edu|The Eli & Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University 320 Charles Street, Cambridge, MA 02141, USA. tarjei@broad.mit.edu', 'United States|United States|United States', 19, 'Algorithms|Bayes Theorem|Chromosome Mapping|DNA Mutational Analysis|Evolution, Molecular|Gene Expression Profiling|Genomics|Models, Genetic|Models, Statistical|Phylogeny|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bti027', '15374867', 'A promising strategy for refining genome annotations is to detect features that conflict with known functional or evolutionary relationships between groups of genes. Previous work in this area has been focused on investigating the absence of housekeeping genes or components of well-studied pathways. We have sought to develop a method for improving new annotations that can automatically synthesize and use the information available in a database of other annotated genomes.'),
(71656, 2005, 'bio', 'Identifying time-lagged gene clusters using gene expression data', 'Ji, Liping|Tan, Kian-Lee', 'Department of Computer Science, National University of Singapore 3 Science Drive 2, Singapore 117543, Singapore. jiliping@comp.nus.edu.sg|Department of Computer Science, National University of Singapore 3 Science Drive 2, Singapore 117543, Singapore. jiliping@comp.nus.edu.sg', 'Singapore|Singapore', 68, 'Cluster Analysis|Gene Expression Profiling|Gene Expression Regulation, Fungal|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Software|Time Factors', 'Comparative Study', '10.1093/bioinformatics/bti026', '15374868', 'Analysis of gene expression data can provide insights into the time-lagged co-regulation of genes/gene clusters. However, existing methods such as the Event Method and the Edge Detection Method are inefficient as they compare only two genes at a time. More importantly, they neglect some important information due to their scoring criterian. In this paper, we propose an efficient algorithm to identify time-lagged co-regulated gene clusters. The algorithm facilitates localized comparison and processes several genes simultaneously to generate detailed and complete time-lagged information for genes/gene clusters.'),
(71657, 2005, 'bio', 'Prediction of splice sites with dependency graphs and their expanded bayesian networks', 'Chen, Te-Ming|Lu, Chung-Chin|Li, Wen-Hsiung', 'Department of Electrical Engineering, National Tsing Hua University Hsinchu 30013, Taiwan.|Department of Electrical Engineering, National Tsing Hua University Hsinchu 30013, Taiwan.|Department of Electrical Engineering, National Tsing Hua University Hsinchu 30013, Taiwan.', '-|-|-', 69, 'Bayes Theorem|Gene Expression Profiling|Models, Genetic|Models, Statistical|RNA Splicing|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bti025', '15374869', 'Owing to the complete sequencing of human and many other genomes, huge amounts of DNA sequence data have been accumulated. In bioinformatics, an important issue is how to predict the complete structure of genes from the genomic DNA sequence, especially the human genome. A crucial part in the gene structure prediction is to determine the precise exon-intron boundaries, i.e. the splice sites, in the coding region.'),
(71658, 2005, 'bio', 'MAP-O-MAT: internet-based linkage mapping', 'Kong, X|Matise, T C', 'Department of Genetics, Rutgers University Piscataway NJ 08854, USA.|Department of Genetics, Rutgers University Piscataway NJ 08854, USA.', 'United States|United States', 25, 'Chromosome Mapping|Genetic Markers|Internet|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti024', '15374870', 'MAP-O-MAT is a web-based server for automated linkage mapping of human polymorphic DNA markers. MAP-O-MAT facilitates the verification of order and map distances for custom mapping sets using genotype data from the CEPH database, and from the Marshfield, SNP Consortium and Rutgers linkage maps (exclusive to the deCODE genotyping data). The CRI-MAP program is used for likelihood calculations and some mapping algorithms, and physical map positions are provided from the human genome assembly.'),
(71659, 2005, 'bio', 'VarMixt: efficient variance modelling for the differential analysis of replicated gene expression data', 'Delmar, Paul|Robin, Stéphane|Daudin, Jean Jacques', 'Laboratoire MAS Ecole Centrale Paris, Grande Voie des vignes, 92295 Chatenay Malabry, France. delmar@inapg.inra.fr|Laboratoire MAS Ecole Centrale Paris, Grande Voie des vignes, 92295 Chatenay Malabry, France. delmar@inapg.inra.fr|Laboratoire MAS Ecole Centrale Paris, Grande Voie des vignes, 92295 Chatenay Malabry, France. delmar@inapg.inra.fr', 'France|France|France', 78, 'Algorithms|Analysis of Variance|Computer Simulation|DNA Replication|Gene Expression Profiling|Genetic Variation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Software', 'Comparative Study', '10.1093/bioinformatics/bti023', '15374871', 'Identifying differentially regulated genes in experiments comparing two experimental conditions is often a key step in the microarray data analysis process. Many different approaches and methodological developments have been put forward, yet the question remains open.'),
(71660, 2005, 'bio', 'An experimental evaluation of a loop versus a reference design for two-channel microarrays', 'Vinciotti, V|Khanin, R|DAlimonte, D|Liu, X|Cattini, N|Hotchkiss, G|Bucca, G|de Jesus, O|Rasaiyaah, J|Smith, C P|Kellam, P|Wit, E', 'Department of Information Systems and Computing, Brunel University Uxbridge UB8 3PH, UK. veronica.vinciotti@brunel.ac.uk|Department of Information Systems and Computing, Brunel University Uxbridge UB8 3PH, UK. veronica.vinciotti@brunel.ac.uk|Department of Information Systems and Computing, Brunel University Uxbridge UB8 3PH, UK. veronica.vinciotti@brunel.ac.uk|Department of Information Systems and Computing, Brunel University Uxbridge UB8 3PH, UK. veronica.vinciotti@brunel.ac.uk|Department of Information Systems and Computing, Brunel University Uxbridge UB8 3PH, UK. veronica.vinciotti@brunel.ac.uk|Department of Information Systems and Computing, Brunel University Uxbridge UB8 3PH, UK. veronica.vinciotti@brunel.ac.uk|Department of Information Systems and Computing, Brunel University Uxbridge UB8 3PH, UK. veronica.vinciotti@brunel.ac.uk|Department of Information Systems and Computing, Brunel University Uxbridge UB8 3PH, UK. veronica.vinciotti@brunel.ac.uk|Department of Information Systems and Computing, Brunel University Uxbridge UB8 3PH, UK. veronica.vinciotti@brunel.ac.uk|Department of Information Systems and Computing, Brunel University Uxbridge UB8 3PH, UK. veronica.vinciotti@brunel.ac.uk|Department of Information Systems and Computing, Brunel University Uxbridge UB8 3PH, UK. veronica.vinciotti@brunel.ac.uk|Department of Information Systems and Computing, Brunel University Uxbridge UB8 3PH, UK. veronica.vinciotti@brunel.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 81, 'Algorithms|Bacterial Proteins|Biomarkers, Tumor|Cell Line, Tumor|Computer Simulation|Gene Expression Profiling|Humans|Lymphoma, B-Cell|Models, Biological|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Protein Kinase C|Streptomyces coelicolor', 'Comparative Study', '10.1093/bioinformatics/bti022', '15374872', 'Despite theoretical arguments that so-called loop designs for two-channel DNA microarray experiments are more efficient, biologists continue to use reference designs. We describe two sets of microarray experiments with RNA from two different biological systems (TPA-stimulated mammalian cells and Streptomyces coelicolor). In each case, both a loop and a reference design were used with the same RNA preparations with the aim of studying their relative efficiency.'),
(71661, 2005, 'bio', 'Iterative cluster analysis of protein interaction data', 'Arnau, Vicente|Mars, Sergio|Marín, Ignacio', 'Departamento de Informática, Universidad de Valencia, Burjassot 46100, Valencia, Spain.|Departamento de Informática, Universidad de Valencia, Burjassot 46100, Valencia, Spain.|Departamento de Informática, Universidad de Valencia, Burjassot 46100, Valencia, Spain.', 'Spain|Spain|Spain', 0, 'Actins|Algorithms|Cluster Analysis|Cytoskeleton|Gene Expression Profiling|Pattern Recognition, Automated|Protein Interaction Mapping|Proteins|Saccharomyces cerevisiae Proteins|Signal Transduction|Software', 'Comparative Study', '10.1093/bioinformatics/bti021', '15374873', 'Generation of fast tools of hierarchical clustering to be applied when distances among elements of a set are constrained, causing frequent distance ties, as happens in protein interaction data.'),
(71662, 2005, 'bio', 'Clann: investigating phylogenetic information through supertree analyses', 'Creevey, C J|McInerney, J O', 'Bioinformatics and Pharmacogenomics Laboratory, Department of Biology, National University of Ireland Maynooth, Co. Kildare, Ireland. chris.creevey@may.ie|Bioinformatics and Pharmacogenomics Laboratory, Department of Biology, National University of Ireland Maynooth, Co. Kildare, Ireland. chris.creevey@may.ie', 'Ireland|Ireland', 146, 'Algorithms|Biological Evolution|Cluster Analysis|Computer Simulation|Models, Genetic|Pedigree|Software', 'Journal Article', '10.1093/bioinformatics/bti020', '15374874', 'Clann has been developed in order to provide methods of investigating phylogenetic information through the application of supertrees.'),
(71663, 2005, 'bio', 'PhenomicDB: a multi-species genotype/phenotype database for comparative phenomics', 'Kahraman, Abdullah|Avramov, Andrey|Nashev, Lyubomir G|Popov, Dimitar|Ternes, Rainer|Pohlenz, Hans-Dieter|Weiss, Bertram', 'Department of Bioinformatics, University of Applied Science Giessen, 35596 Giessen, Germany.|Department of Bioinformatics, University of Applied Science Giessen, 35596 Giessen, Germany.|Department of Bioinformatics, University of Applied Science Giessen, 35596 Giessen, Germany.|Department of Bioinformatics, University of Applied Science Giessen, 35596 Giessen, Germany.|Department of Bioinformatics, University of Applied Science Giessen, 35596 Giessen, Germany.|Department of Bioinformatics, University of Applied Science Giessen, 35596 Giessen, Germany.|Department of Bioinformatics, University of Applied Science Giessen, 35596 Giessen, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 51, 'Animals|Databases, Genetic|Documentation|Gene Expression Profiling|Genomics|Genotype|Humans|Information Dissemination|Information Storage and Retrieval|Phenotype|Species Specificity', 'Journal Article', '10.1093/bioinformatics/bti010', '15374875', 'We have created PhenomicDB, a multi-species genotype/phenotype database by merging public genotype/phenotype data from a wide range of model organisms and Homo sapiens. Until now these data were available in distinct organism-specific databases (e.g. WormBase, OMIM, FlyBase and MGI). We compiled this wealth of data into a single integrated resource by coarse-grained semantic mapping of the phenotypic data fields, by including common gene indices (NCBI Gene), and by the use of associated orthology relationships. With its use-case-oriented user interface, PhenomicDB allows scientists to compare and browse known phenotypes for a given gene or a set of genes from different organisms simultaneously.'),
(71664, 2005, 'bio', 'A memory-efficient algorithm for multiple sequence alignment with constraints', 'Lu, Chin Lung|Huang, Yen Pin', 'Department of Biological Science and Technology, National Chiao Tung University Hsinchu 300, Taiwan, Republic of China. cllu@mail.nctu.edu.tw|Department of Biological Science and Technology, National Chiao Tung University Hsinchu 300, Taiwan, Republic of China. cllu@mail.nctu.edu.tw', 'China|China', 20, 'Algorithms|Amino Acid Sequence|Base Sequence|Information Storage and Retrieval|Internet|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis|Sequence Analysis, Protein|Sequence Analysis, RNA|Sequence Homology|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth468', '15374876', 'Recently, the concept of the constrained sequence alignment was proposed to incorporate the knowledge of biologists about structures/functionalities/consensuses of their datasets into sequence alignment such that the user-specified residues/nucleotides are aligned together in the computed alignment. The currently developed programs use the so-called progressive approach to efficiently obtain a constrained alignment of several sequences. However, the kernels of these programs, the dynamic programming algorithms for computing an optimal constrained alignment between two sequences, run in (gamman2) memory, where gamma is the number of the constraints and n is the maximum of the lengths of sequences. As a result, such a high memory requirement limits the overall programs to align short sequences only.'),
(71665, 2005, 'bio', 'Superiority of network motifs over optimal networks and an application to the revelation of gene network evolution', 'Ott, S|Hansen, A|Kim, S-Y|Miyano, S', 'Human Genome Center, Institute of Medical Science, University of Tokyo 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan. sascha-ott@gmx.net|Human Genome Center, Institute of Medical Science, University of Tokyo 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan. sascha-ott@gmx.net|Human Genome Center, Institute of Medical Science, University of Tokyo 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan. sascha-ott@gmx.net|Human Genome Center, Institute of Medical Science, University of Tokyo 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan. sascha-ott@gmx.net', 'Japan|Japan|Japan|Japan', 0, 'Algorithms|Bacillus subtilis|Bacterial Proteins|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Oligonucleotide Array Sequence Analysis|Signal Transduction|Software|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth484', '15377501', 'Estimating the network of regulative interactions between genes from gene expression measurements is a major challenge. Recently, we have shown that for gene networks of up to around 35 genes, optimal network models can be computed. However, even optimal gene network models will in general contain false edges, since the expression data will not unambiguously point to a single network.'),
(71666, 2005, 'bio', 'The Los Alamos hepatitis C sequence database', 'Kuiken, Carla|Yusim, Karina|Boykin, Laura|Richardson, Russell', 'HCV database, Los Alamos National Laboratory, Los Alamos, NM, USA.|HCV database, Los Alamos National Laboratory, Los Alamos, NM, USA.|HCV database, Los Alamos National Laboratory, Los Alamos, NM, USA.|HCV database, Los Alamos National Laboratory, Los Alamos, NM, USA.', 'United States|United States|United States|United States', 298, 'Amino Acid Sequence|Base Sequence|DNA, Viral|Database Management Systems|Databases, Genetic|Genome, Viral|Hepacivirus|Information Storage and Retrieval|Molecular Sequence Data|New Mexico|Sequence Alignment|Sequence Analysis|User-Computer Interface|Viral Proteins', 'Journal Article', '10.1093/bioinformatics/bth485', '15377502', 'The hepatitis C virus (HCV) is a significant threat to public health worldwide. The virus is highly variable and evolves rapidly, making it an elusive target for the immune system and for vaccine and drug design. At present, some 30 000 HCV sequences have been published. A central website that provides annotated sequences and analysis tools will be helpful to HCV scientists worldwide.'),
(71667, 2005, 'bio', 'SNPP: automating large-scale SNP genotype data management', 'Zhao, Lan-Juan|Li, Miao-Xin|Guo, Yan-Fang|Xu, Fu-Hua|Li, Jin-Long|Deng, Hong-Wen', 'Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University Changsha, Hunan 410081, China.|Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University Changsha, Hunan 410081, China.|Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University Changsha, Hunan 410081, China.|Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University Changsha, Hunan 410081, China.|Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University Changsha, Hunan 410081, China.|Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University Changsha, Hunan 410081, China.', 'China|China|China|China|China|China', 16, 'Algorithms|Chromosome Mapping|Database Management Systems|Databases, Nucleic Acid|Genotype|Information Storage and Retrieval|Internet|Linkage Disequilibrium|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth486', '15377503', 'To manage high-throughput single nucleotide polymorphism (SNP) genotyping data efficiently, we developed a dynamic general database management system-SNPP (SNP Processor). It provides several functions, including data importing with comparison, Mendelian inheritance check within pedigrees, data compiling and exporting. Furthermore, SNPP may generate files for repeat genotyping and transform them into files that can be executed by a liquid handling system.'),
(71668, 2005, 'bio', 'A simple and fast secondary structure prediction method using hidden neural networks', 'Lin, Kuang|Simossis, Victor A|Taylor, Willam R|Heringa, Jaap', 'Division of Mathematical Biology, The National Institute for Medical Research The Ridgeway, Mill Hill, London NW7 1AA, UK. kxlin@nimr.mrc.ac.uk|Division of Mathematical Biology, The National Institute for Medical Research The Ridgeway, Mill Hill, London NW7 1AA, UK. kxlin@nimr.mrc.ac.uk|Division of Mathematical Biology, The National Institute for Medical Research The Ridgeway, Mill Hill, London NW7 1AA, UK. kxlin@nimr.mrc.ac.uk|Division of Mathematical Biology, The National Institute for Medical Research The Ridgeway, Mill Hill, London NW7 1AA, UK. kxlin@nimr.mrc.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 68, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Markov Chains|Models, Chemical|Models, Molecular|Models, Statistical|Molecular Sequence Data|Neural Networks (Computer)|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/bth487', '15377504', 'In this paper, we present a secondary structure prediction method YASPIN that unlike the current state-of-the-art methods utilizes a single neural network for predicting the secondary structure elements in a 7-state local structure scheme and then optimizes the output using a hidden Markov model, which results in providing more information for the prediction.'),
(71669, 2005, 'bio', 'HaploPainter: a tool for drawing pedigrees with complex haplotypes', 'Thiele, Holger|Nürnberg, Peter', 'Gene Mapping Center, Max Delbrueck Center (MDC) for Molecular Medicine, Berlin-Buch, Germany. holger.thiele@uni-koeln.de|Gene Mapping Center, Max Delbrueck Center (MDC) for Molecular Medicine, Berlin-Buch, Germany. holger.thiele@uni-koeln.de', 'Germany|Germany', 208, 'Chromosome Mapping|Computer Graphics|DNA Mutational Analysis|Evolution, Molecular|Haplotypes|Pedigree|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth488', '15377505', 'HaploPainter is a user-friendly pedigree-drawing application with special features for easy visualization of complex haplotype information. It has been developed to facilitate gene mapping in Mendelian diseases in terms of fast and reliable definition of the smallest critical interval harbouring the underlying gene defect. HaploPainter is written in Perl and may be used for visualization of haplotypes calculated by any of the common linkage programs. With special features like haplotype compression or the ability of marker section cut-out it particularly addresses the requirements for viewing large haplotypes as obtained by using for genome scans high-density marker panels of many thousands of single nucleotide polymorphisms (SNPs).'),
(71670, 2005, 'bio', 'RALEE--RNA ALignment editor in Emacs', 'Griffiths-Jones, Sam', 'The Wellcome Trust Sanger Institute Wellcome Trust Genome Campus, Hinxton, CAMBS, CB10 1SA, UK. sgj@sanger.ac.uk', 'United Kingdom', 0, 'Algorithms|Computer Graphics|Consensus Sequence|Programming Languages|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Software|User-Computer Interface|Word Processing', 'Journal Article', '10.1093/bioinformatics/bth489', '15377506', 'Production of high quality multiple sequence alignments of structured RNAs relies on an iterative combination of manual editing and structure prediction. An essential feature of an RNA alignment editor is the facility to mark-up the alignment based on how it matches a given secondary structure prediction, but few available alignment editors offer such a feature. The RALEE (RNA ALignment Editor in Emacs) tool provides a simple environment for RNA multiple sequence alignment editing, including structure-specific colour schemes, utilizing helper applications for structure prediction and many more conventional editing functions. This is accomplished by extending the commonly used text editor, Emacs, which is available for Linux, most UNIX systems, Windows and Mac OS.'),
(71671, 2005, 'bio', 'RDP2: recombination detection and analysis from sequence alignments', 'Martin, D P|Williamson, C|Posada, D', 'Institute of Infectious Diseases and Molecular Medicine, University of Cape Town Cape Town 7000, South Africa. darren@science.uct.ac.za|Institute of Infectious Diseases and Molecular Medicine, University of Cape Town Cape Town 7000, South Africa. darren@science.uct.ac.za|Institute of Infectious Diseases and Molecular Medicine, University of Cape Town Cape Town 7000, South Africa. darren@science.uct.ac.za', 'South Africa|South Africa|South Africa', 862, 'Algorithms|Evolution, Molecular|Internet|Phylogeny|Recombination, Genetic|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth490', '15377507', 'RDP2 is a Windows 95/XP program that examines nucleotide sequence alignments and attempts to identify recombinant sequences and recombination breakpoints using 10 published recombination detection methods, including GENECONV, BOOTSCAN, MAXIMUM chi(2), CHIMAERA and SISTER SCANNING. The program enables fast automated analysis of large alignments (up to 300 sequences containing 13 000 sites), and interactive exploration, management and verification of results with different recombination detection and tree drawing methods.'),
(71672, 2005, 'bio', 'Predicting protein functions with message passing algorithms', 'Leone, Michele|Pagnani, Andrea', 'Institute for Scientific Interchange (ISI) Viale Settimio Severo 65, Turin, I-10133, Italy. leone@isiosf.isi.it|Institute for Scientific Interchange (ISI) Viale Settimio Severo 65, Turin, I-10133, Italy. leone@isiosf.isi.it', 'Italy|Italy', 20, 'Algorithms|Computer Simulation|Information Storage and Retrieval|Models, Biological|Models, Chemical|Protein Interaction Mapping|Proteins|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Analysis, Protein|Signal Transduction|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth491', '15377508', 'In the last few years, a growing interest in biology has been shifting toward the problem of optimal information extraction from the huge amount of data generated via large-scale and high-throughput techniques. One of the most relevant issues has recently emerged that of correctly and reliably predicting the functions of a given protein with that of functions exploiting information coming from the whole network of proteins physically interacting with the functionally undetermined one. In the present work, we will refer to an observed protein as the one present in the protein-protein interaction networks published in the literature.'),
(71673, 2004, 'bio', 'Analysis of array CGH data: from signal ratio to gain and loss of DNA regions', 'Hupé, Philippe|Stransky, Nicolas|Thiery, Jean-Paul|Radvanyi, François|Barillot, Emmanuel', 'Service Bioinformatique, UMR 144 CNRS/Institut Curie, 26, rue dUlm, Paris, 75248 cedex 05, France. glad@curie.fr <glad@curie.fr>|Service Bioinformatique, UMR 144 CNRS/Institut Curie, 26, rue dUlm, Paris, 75248 cedex 05, France. glad@curie.fr <glad@curie.fr>|Service Bioinformatique, UMR 144 CNRS/Institut Curie, 26, rue dUlm, Paris, 75248 cedex 05, France. glad@curie.fr <glad@curie.fr>|Service Bioinformatique, UMR 144 CNRS/Institut Curie, 26, rue dUlm, Paris, 75248 cedex 05, France. glad@curie.fr <glad@curie.fr>|Service Bioinformatique, UMR 144 CNRS/Institut Curie, 26, rue dUlm, Paris, 75248 cedex 05, France. glad@curie.fr <glad@curie.fr>', 'France|France|France|France|France', 423, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|Gene Dosage|Genetic Variation|Humans|In Situ Hybridization|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Software|Stochastic Processes|Urinary Bladder Neoplasms', 'Comparative Study', '10.1093/bioinformatics/bth418', '15381628', 'Genomic DNA regions are frequently lost or gained during tumor progression. Array Comparative Genomic Hybridization (array CGH) technology makes it possible to assess these changes in DNA in cancers, by comparison with a normal reference. The identification of systematically deleted or amplified genomic regions in a set of tumors enables biologists to identify genes involved in cancer progression because tumor suppressor genes are thought to be located in lost genomic regions and oncogenes, in gained regions. Array CGH profiles should also improve the classification of tumors. The achievement of these goals requires a methodology for detecting the breakpoints delimiting altered regions in genomic patterns and assigning a status (normal, gained or lost) to each chromosomal region.'),
(71674, 2005, 'bio', 'wEMBOSS: a web interface for EMBOSS', 'Sarachu, Martín|Colet, Marc', 'Argentinian EMBnet Node (AR.EMBnet), IBBM, Facultad de Ciencias Exactas, Universidad Nacional de La Plata Calle 115 entre 49 y 50, 1900 La Plata, Argentina. msarachu@biol.unlp.edu.ar|Argentinian EMBnet Node (AR.EMBnet), IBBM, Facultad de Ciencias Exactas, Universidad Nacional de La Plata Calle 115 entre 49 y 50, 1900 La Plata, Argentina. msarachu@biol.unlp.edu.ar', 'Argentina|Argentina', 47, 'Computer Graphics|Database Management Systems|Information Storage and Retrieval|Internet|Molecular Biology|Sequence Alignment|Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti031', '15388516', 'wEMBOSS provides a web environment from which the user can access EMBOSS in a user-friendly way. wEMBOSS supplies each user with space and tools to organize and review his or her work.'),
(71675, 2005, 'bio', 'GLAD: a system for developing and deploying large-scale bioinformatics grid', 'Teo, Yong-Meng|Wang, Xianbing|Ng, Yew-Kwong', 'Department of Computer Science, National University of Singapore, Singapore 117543. teoym@comp.nus.edu.sg|Department of Computer Science, National University of Singapore, Singapore 117543. teoym@comp.nus.edu.sg|Department of Computer Science, National University of Singapore, Singapore 117543. teoym@comp.nus.edu.sg', 'Singapore|Singapore|Singapore', 8, 'Computational Biology|Computer Communication Networks|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Programming Languages|Sequence Analysis|Software|Software Design|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti034', '15388517', 'Grid computing is used to solve large-scale bioinformatics problems with gigabytes database by distributing the computation across multiple platforms. Until now in developing bioinformatics grid applications, it is extremely tedious to design and implement the component algorithms and parallelization techniques for different classes of problems, and to access remotely located sequence database files of varying formats across the grid. In this study, we propose a grid programming toolkit, GLAD (Grid Life sciences Applications Developer), which facilitates the development and deployment of bioinformatics applications on a grid.'),
(71676, 2005, 'bio', 'Stepwise detection of recombination breakpoints in sequence alignments', 'Graham, Jinko|McNeney, Brad|Seillier-Moiseiwitsch, Françoise', 'Department of Statistics and Actuarial Science, Simon Fraser University Burnaby, Canada V5A 1S6. jgraham@stat.sfu.ca|Department of Statistics and Actuarial Science, Simon Fraser University Burnaby, Canada V5A 1S6. jgraham@stat.sfu.ca|Department of Statistics and Actuarial Science, Simon Fraser University Burnaby, Canada V5A 1S6. jgraham@stat.sfu.ca', 'Canada|Canada|Canada', 10, 'Algorithms|Chromosome Breakage|Chromosomes, Human, Pair 7|Computer Simulation|Genome, Viral|HIV-1|Humans|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Recombination, Genetic|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bti040', '15388518', 'We propose a stepwise approach to identify recombination breakpoints in a sequence alignment. The approach can be applied to any recombination detection method that uses a permutation test and provides estimates of breakpoints.'),
(71677, 2005, 'bio', 'Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification', 'Yanai, Itai|Benjamin, Hila|Shmoish, Michael|Chalifa-Caspi, Vered|Shklar, Maxim|Ophir, Ron|Bar-Even, Arren|Horn-Saban, Shirley|Safran, Marilyn|Domany, Eytan|Lancet, Doron|Shmueli, Orit', 'Department of Molecular Genetics, Weizmann Institute of Science 76100 Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science 76100 Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science 76100 Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science 76100 Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science 76100 Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science 76100 Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science 76100 Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science 76100 Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science 76100 Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science 76100 Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science 76100 Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science 76100 Rehovot, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 462, 'Algorithms|Chromosome Mapping|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Organ Specificity|Proteome|Software|Tissue Distribution|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti042', '15388519', 'Genes are often characterized dichotomously as either housekeeping or single-tissue specific. We conjectured that crucial functional information resides in genes with midrange profiles of expression.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71678, 2005, 'bio', 'APART: automated preprocessing for NMR assignments with reduced tedium', 'Pawley, Norma H|Gans, Jason D|Michalczyk, Ryszard', 'Los Alamos National Laboratory, Bioscience Division MS G758, Los Alamos, NM 87545, USA. npawley@lanl.gov|Los Alamos National Laboratory, Bioscience Division MS G758, Los Alamos, NM 87545, USA. npawley@lanl.gov|Los Alamos National Laboratory, Bioscience Division MS G758, Los Alamos, NM 87545, USA. npawley@lanl.gov', 'United States|United States|United States', 4, 'Algorithms|Magnetic Resonance Spectroscopy|Models, Chemical|Models, Statistical|Pattern Recognition, Automated|Protein Conformation|Proteins|Signal Processing, Computer-Assisted|Software|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/bti043', '15388520', 'High-throughput NMR structure determination is a goal that will require progress on many fronts, one of which is rapid resonance assignment. An important rate-limiting step in the resonance assignment process is accurate identification of resonance peaks in the NMR spectra. Peak-picking schemes range from incomplete (which lose essential assignment connectivities) to noisy (which obscure true connectivities with many false ones). We introduce an automated preassignment process that removes false peaks from noisy peak lists by requiring consensus between multiple NMR experiments and exploiting a priori information about NMR spectra. This process is designed to accept multiple input formats and generate multiple output formats, in an effort to be compatible with a variety of user preferences.'),
(71679, 2004, 'bio', 'Which is better for cDNA-microarray-based classification: ratios or direct intensities', 'Attoor, Sanju|Dougherty, Edward R|Chen, Yidong|Bittner, Michael L|Trent, Jeffrey M', 'Department of Electrical Engineering, Texas A&M University, College Station, TX 78041, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 78041, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 78041, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 78041, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 78041, USA.', 'United States|United States|United States|United States|United States', 25, 'Algorithms|Computer Simulation|DNA|Equipment Failure Analysis|Gene Expression Profiling|Genetic Variation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bth272', '15454406', 'There are two general methods for making gene-expression microarrays: one is to hybridize a single test set of labeled targets to the probe, and measure the background-subtracted intensity at each probe site, the other is to hybridize both a test and a reference set of differentially labeled targets to a single detector array, and measure the ratio of the background-subtracted intensities at each probe site. Which method is better depends on the variability in the cell system and the random factors resulting from the microarray technology. It also depends on the purpose for which the microarray is being used. Classification is a fundamental application and it is the one considered here.'),
(71680, 2005, 'bio', 'CIS: compound importance sampling method for protein-DNA binding site p-value estimation', 'Barash, Y|Elidan, G|Kaplan, T|Friedman, N', 'School of Computer Science & Engineering, The Hebrew University Jerusalem 91904, Israel.|School of Computer Science & Engineering, The Hebrew University Jerusalem 91904, Israel.|School of Computer Science & Engineering, The Hebrew University Jerusalem 91904, Israel.|School of Computer Science & Engineering, The Hebrew University Jerusalem 91904, Israel.', 'Israel|Israel|Israel|Israel', 20, 'Algorithms|Binding Sites|DNA|DNA-Binding Proteins|Data Interpretation, Statistical|Models, Biological|Models, Chemical|Models, Statistical|Protein Binding|Sample Size|Sequence Analysis, DNA|Software|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bti041', '15454407', 'A key aspect of transcriptional regulation is the binding of transcription factors to sequence-specific binding sites that allow them to modulate the expression of nearby genes. Given models of such binding sites, one can scan regulatory regions for putative binding sites and construct a genome-wide regulatory network. In such genome-wide scans, it is crucial to control the amount of false positive predictions. Recently, several works demonstrated the benefits of modeling dependencies between positions within the binding site. Yet, computing the statistical significance of putative binding sites in this scenario remains a challenge.'),
(71681, 2005, 'bio', 'A graph-theoretic approach for the separation of b and y ions in tandem mass spectra', 'Yan, Bo|Pan, Chongle|Olman, Victor N|Hettich, Robert L|Xu, Ying', 'Computational Systems Biology Laboratory, Department of Biochemical and Molecular Biology, University of Georgia, Athens, GA 30602, USA.|Computational Systems Biology Laboratory, Department of Biochemical and Molecular Biology, University of Georgia, Athens, GA 30602, USA.|Computational Systems Biology Laboratory, Department of Biochemical and Molecular Biology, University of Georgia, Athens, GA 30602, USA.|Computational Systems Biology Laboratory, Department of Biochemical and Molecular Biology, University of Georgia, Athens, GA 30602, USA.|Computational Systems Biology Laboratory, Department of Biochemical and Molecular Biology, University of Georgia, Athens, GA 30602, USA.', 'Georgia|Georgia|Georgia|Georgia|Georgia', 31, 'Algorithms|Amino Acid Sequence|Computer Graphics|Computer Simulation|Fungal Proteins|Ions|Mass Spectrometry|Models, Chemical|Models, Molecular|Molecular Sequence Data|Numerical Analysis, Computer-Assisted|Peptide Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti044', '15454408', 'Ion-type identification is a fundamental problem in computational proteomics. Methods for accurate identification of ion types provide the basis for many mass spectrometry data interpretation problems, including (a) de novo sequencing, (b) identification of post-translational modifications and mutations and (c) validation of database search results.'),
(71682, 2005, 'bio', 'Modelling cellular systems with PySCeS', 'Olivier, Brett G|Rohwer, Johann M|Hofmeyr, Jan-Hendrik S', 'Department of Biochemistry, Triple-J Group for Molecular Cell Physiology, University of Stellenbosch Private Bag X1, Matieland 7602, South Africa. bgoli@sun.ac.za|Department of Biochemistry, Triple-J Group for Molecular Cell Physiology, University of Stellenbosch Private Bag X1, Matieland 7602, South Africa. bgoli@sun.ac.za|Department of Biochemistry, Triple-J Group for Molecular Cell Physiology, University of Stellenbosch Private Bag X1, Matieland 7602, South Africa. bgoli@sun.ac.za', 'South Africa|South Africa|South Africa', 97, 'Cell Physiological Phenomena|Computer Simulation|Models, Biological|Numerical Analysis, Computer-Assisted|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/bti046', '15454409', 'The Python Simulator for Cellular Systems (PySCeS) is an extendable research tool for the numerical analysis and investigation of cellular systems.'),
(71683, 2005, 'bio', 'Improving promoter prediction for the NNPP22 algorithm: a case study using Escherichia coli DNA sequences', 'Burden, S|Lin, Y-X|Zhang, R', 'Department of Mathematics and Applied Statistics, University of Wollongong Wollongong, NSW 2522, Australia. alh98@uow.edu.au|Department of Mathematics and Applied Statistics, University of Wollongong Wollongong, NSW 2522, Australia. alh98@uow.edu.au|Department of Mathematics and Applied Statistics, University of Wollongong Wollongong, NSW 2522, Australia. alh98@uow.edu.au', 'Australia|Australia|Australia', 27, 'Algorithms|Chromosome Mapping|DNA, Bacterial|Escherichia coli|Neural Networks (Computer)|Promoter Regions, Genetic|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bti047', '15454410', 'Although a great deal of research has been undertaken in the area of promoter prediction, prediction techniques are still not fully developed. Many algorithms tend to exhibit poor specificity, generating many false positives, or poor sensitivity. The neural network prediction program NNPP2.2 is one such example.'),
(71684, 2005, 'bio', 'Seq2Struct: a resource for establishing sequence-structure links', 'Via, Allegra|Zanzoni, Andreas|Helmer-Citterich, Manuela', 'Department of Biology, Centre for Molecular Bioinformatics, University of Rome Tor Vergata 00133 Rome, Italy. seq2struct@cbm.bio.uniroma2.it|Department of Biology, Centre for Molecular Bioinformatics, University of Rome Tor Vergata 00133 Rome, Italy. seq2struct@cbm.bio.uniroma2.it|Department of Biology, Centre for Molecular Bioinformatics, University of Rome Tor Vergata 00133 Rome, Italy. seq2struct@cbm.bio.uniroma2.it', 'Italy|Italy|Italy', 7, 'Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Models, Chemical|Models, Molecular|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bti049', '15454411', 'Several methods for establishing cross-links between Protein Data Bank (PDB) structures or Structural Classification of Proteins (SCOP) domains and Swiss-Prot + TrEMBL sequences (or vice versa) rely on database annotations. Alternatively, sequence alignment procedures can be used. In this study, we describe Seq2Struct, a web resource for the identification of sequence-structure links. The resource consists of an exhaustive collection of annotated links between Swiss-Prot + TrEMBL and PDB + SCOP database entries. Links are based on pre-established highly reliable thresholds and stored in a relational database, which has been enhanced using annotations derived from Swiss-Prot, PDB, SCOP, GOA and DSSP databases. The Seq2Struct database contents, supported by a WWW web interface, can be queried both online and downloaded.'),
(71685, 2005, 'bio', 'Weighted analysis of microarray gene expression using maximum-likelihood', 'Bakewell, David J|Wit, Ernst', 'Cancer Research UK Beatson Laboratories, Garscube Estate, Bearsden, Glasgow G61 1BD, UK. d.bakewell@beatson.gla.ac.uk|Cancer Research UK Beatson Laboratories, Garscube Estate, Bearsden, Glasgow G61 1BD, UK. d.bakewell@beatson.gla.ac.uk', 'United Kingdom|United Kingdom', 6, 'Algorithms|Gene Expression Profiling|Likelihood Functions|Models, Genetic|Models, Statistical|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis', 'Comparative Study', '10.1093/bioinformatics/bti051', '15454412', 'The numerical values of gene expression measured using microarrays are usually presented to the biological end-user as summary statistics of spot pixel data, such as the spot mean, median and mode. Much of the subsequent data analysis reported in the literature, however, uses only one of these spot statistics. This results in sub-optimal estimates of gene expression levels and a need for improvement in quantitative spot variation surveillance.'),
(71686, 2005, 'bio', 'arrayMagic: two-colour cDNA microarray quality control and preprocessing', 'Buness, Andreas|Huber, Wolfgang|Steiner, Klaus|Sültmann, Holger|Poustka, Annemarie', 'Department of Molecular Genome Analysis, German Cancer Research Center INF 580, Heidelberg, 69120, Germany. a.buness@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center INF 580, Heidelberg, 69120, Germany. a.buness@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center INF 580, Heidelberg, 69120, Germany. a.buness@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center INF 580, Heidelberg, 69120, Germany. a.buness@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center INF 580, Heidelberg, 69120, Germany. a.buness@dkfz.de', 'Germany|Germany|Germany|Germany|Germany', 18, 'Algorithms|Database Management Systems|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti052', '15454413', 'arrayMagic is a software package for quality control and preprocessing of two-colour cDNA microarray data. The automated analysis pipeline comprises data import, normalization, replica merging, quality diagnostics and data export. The script-based processing combines reproducibility and flexibility at high-throughput and provides quality-assured and preprocessed microarray data to high-level follow-up analysis.'),
(71687, 2005, 'bio', 'An efficient Monte Carlo approach to assessing statistical significance in genomic studies', 'Lin, D Y', 'Department of Biostatistics, University of North Carolina, McGavran-Greenberg Hall, CB #7420, Chapel Hill, NC 27599-7420, USA. lin@bios.unc.edu', 'United States', 129, 'Algorithms|Biomarkers, Tumor|Chromosome Mapping|Data Interpretation, Statistical|Gene Expression Profiling|Genomics|Humans|Lung Neoplasms|Models, Genetic|Models, Statistical|Monte Carlo Method|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bti053', '15454414', 'Multiple hypothesis testing is a common problem in genome research, particularly in microarray experiments and genomewide association studies. Failure to account for the effects of multiple comparisons would result in an abundance of false positive results. The Bonferroni correction and Holms step-down procedure are overly conservative, whereas the permutation test is time-consuming and is restricted to simple problems.'),
(71688, 2005, 'bio', 'Using shared genomic synteny and shared protein functions to enhance the identification of orthologous gene pairs', 'Zheng, Xiangqun H|Lu, Fu|Wang, Zhen-Yuan|Zhong, Fei|Hoover, Jeffrey|Mural, Richard', 'Assays and Bioinformatics, Celera Genomics Corporation, 45 West Gude Drive, Rockville, MD 20850, USA.|Assays and Bioinformatics, Celera Genomics Corporation, 45 West Gude Drive, Rockville, MD 20850, USA.|Assays and Bioinformatics, Celera Genomics Corporation, 45 West Gude Drive, Rockville, MD 20850, USA.|Assays and Bioinformatics, Celera Genomics Corporation, 45 West Gude Drive, Rockville, MD 20850, USA.|Assays and Bioinformatics, Celera Genomics Corporation, 45 West Gude Drive, Rockville, MD 20850, USA.|Assays and Bioinformatics, Celera Genomics Corporation, 45 West Gude Drive, Rockville, MD 20850, USA.', 'United States|United States|United States|United States|United States|United States', 39, 'Algorithms|Animals|Chromosome Mapping|Chromosomes, Mammalian|Conserved Sequence|Evolution, Molecular|Genetic Linkage|Genome|Humans|Mice|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Evaluation Studies', '10.1093/bioinformatics/bti045', '15458983', 'The identification of orthologous gene pairs is generally based on sequence similarity. Gene pairs that are mutually best hits between the genomes being compared are asserted to be orthologs. Although this method identifies most orthologous gene pairs with high confidence, it will miss a fraction of them, especially genes in duplicated gene families. In addition, the approach depends heavily on the completeness and quality of gene annotation. When the gene sequences are not correctly represented the approach is unlikely to find the correct ortholog. To overcome these limitations, we have developed an approach to identify orthologous gene pairs using shared chromosomal synteny and the annotation of protein function.'),
(71689, 2005, 'bio', 'Biological sequence analysis through the one-dimensional percolation transform and its enhanced version', 'da Fontoura Costa, Luciano', 'Cybernetic Vision Research Group, GII-IFSC, Universidade de São Paulo, São Carlos, SP, Caixa Postal 369, 13560-970, Brazil. luciano@if.sc.usp.br', 'Brazil', 0, 'Algorithms|Animals|Gene Expression Profiling|Proteome|Sequence Alignment|Sequence Analysis, Protein|Xenopus|Xenopus Proteins|Xenopus laevis|Zebrafish|Zebrafish Proteins', 'Comparative Study', '10.1093/bioinformatics/bti050', '15458984', 'The necessity to characterize the spatial uniformity (or lack of it) of symbols in biological sequences, given its implications for identification of the properties of the structures associated with the sequences.'),
(71690, 2005, 'bio', 'TFExplorer: integrated analysis database for predicted transcription regulatory elements', 'Kim, Jinsoo|Seo, Jungmin|Lee, Young Seek|Kim, Sangsoo', 'National Genome Information Center KRIBB, Daejeon, Korea.|National Genome Information Center KRIBB, Daejeon, Korea.|National Genome Information Center KRIBB, Daejeon, Korea.|National Genome Information Center KRIBB, Daejeon, Korea.', '-|-|-|-', 6, 'Algorithms|Database Management Systems|Databases, Protein|Gene Expression Regulation|Genes, Regulator|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, Protein|Systems Integration|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti048', '15466909', 'TFExplorer is a web-based integrated database for predicted regulatory elements in human, mouse and rat. It shows predicted binding sites of transcription factors in the promoter regions, along with their phylogenetic footprinting information. In addition, TFExplorer can search for genes that have a given sequence pattern in their promoter regions using the motif-searching method.'),
(71691, 2004, 'bio', 'BagBoosting for tumor classification with gene expression data', 'Dettling, Marcel', 'Seminar für Statistik, ETH Zürich, CH-8092 Switzerland. dettling@stat.math.ethz.ch <dettling@stat.math.ethz.ch>', 'Switzerland', 0, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Cluster Analysis|Gene Expression Profiling|Genetic Testing|Humans|Models, Genetic|Models, Statistical|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Software', 'Comparative Study', '10.1093/bioinformatics/bth447', '15466910', 'Microarray experiments are expected to contribute significantly to the progress in cancer treatment by enabling a precise and early diagnosis. They create a need for class prediction tools, which can deal with a large number of highly correlated input variables, perform feature selection and provide class probability estimates that serve as a quantification of the predictive uncertainty. A very promising solution is to combine the two ensemble schemes bagging and boosting to a novel algorithm called BagBoosting.'),
(71692, 2004, 'bio', 'GenomeMixer: a complex genetic cross simulator', 'Williams, Alexander G|Williams, Robert W', 'Center of Genomics and Bioinformatics, Department of Anatomy and Neurobiology, University of Tennessee, 875 Monroe Avenue, Memphis, TN 38163, USA.|Center of Genomics and Bioinformatics, Department of Anatomy and Neurobiology, University of Tennessee, 875 Monroe Avenue, Memphis, TN 38163, USA.', 'United States|United States', 0, 'Chromosome Mapping|Computer Simulation|Crosses, Genetic|Genetic Variation|Genetics, Population|Models, Genetic|Models, Statistical|Pedigree|Polymorphism, Genetic|Recombination, Genetic|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth269', '15477491', 'GenomeMixer is a cross-platform application that simulates meiotic recombination events for large and complex multigenerational genetic crosses among sexually reproducing diploid species and outputs simulated progeny to several standard mapping programs.'),
(71693, 2005, 'bio', 'An empirical Bayes approach to inferring large-scale gene association networks', 'Schäfer, Juliane|Strimmer, Korbinian', 'Department of Statistics, University of Munich, Ludwigstrasse 33, D-80539 Munich, Germany.|Department of Statistics, University of Munich, Ludwigstrasse 33, D-80539 Munich, Germany.', 'Germany|Germany', 526, 'Algorithms|Artificial Intelligence|Bayes Theorem|Biomarkers, Tumor|Breast Neoplasms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Biological|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Signal Transduction|Transcription Factors|Tumor Cells, Cultured', 'Evaluation Studies', '10.1093/bioinformatics/bti062', '15479708', 'Genetic networks are often described statistically using graphical models (e.g. Bayesian networks). However, inferring the network structure offers a serious challenge in microarray analysis where the sample size is small compared to the number of considered genes. This renders many standard algorithms for graphical models inapplicable, and inferring genetic networks an ill-posed inverse problem.'),
(71694, 2005, 'bio', 'ParIS Genome Rearrangement server', 'Miklós, I|Ittzés, P|Hein, J', 'Theoretical Biology and Ecology Modelling Group, Hungarian Academy of Sciences and Eötvös Loránd University, Pázmány Péter Sétány 1/c. H-1117 Budapest, Hungary. miklosi@ramet.elte.hu|Theoretical Biology and Ecology Modelling Group, Hungarian Academy of Sciences and Eötvös Loránd University, Pázmány Péter Sétány 1/c. H-1117 Budapest, Hungary. miklosi@ramet.elte.hu|Theoretical Biology and Ecology Modelling Group, Hungarian Academy of Sciences and Eötvös Loránd University, Pázmány Péter Sétány 1/c. H-1117 Budapest, Hungary. miklosi@ramet.elte.hu', 'Hungary|Hungary|Hungary', 0, 'Algorithms|Chromosome Aberrations|Chromosome Mapping|DNA Mutational Analysis|Internet|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bti060', '15479709', 'ParIS Genome Rearrangement is a web server for a Bayesian analysis of unichromosomal genome pairs. The underlying model allows inversions, transpositions and inverted transpositions. The server generates a Markov chain using a Partial Importance Sampler technique, and samples trajectories of mutations from this chain. The user can specify several marginalizations to the posterior: the posterior distribution of number of mutations needed to transform one genome into another, length distribution of mutations, number of mutations that have occurred at a given site. Both text and graphical outputs are available. We provide a limited server, a downloadable unlimited server that can be installed locally on any linux/Unix operating system, and a database of mitochondrial gene orders.'),
(71695, 2005, 'bio', 'A simple procedure for estimating the false discovery rate', 'Dalmasso, Cyril|Broët, Philippe|Moreau, Thierry', 'INSERM U472, Faculté de Médecine Paris-Sud 16 Avenue Paul Vaillant-Couturier, 94807 Villejuif Cedex, France.|INSERM U472, Faculté de Médecine Paris-Sud 16 Avenue Paul Vaillant-Couturier, 94807 Villejuif Cedex, France.|INSERM U472, Faculté de Médecine Paris-Sud 16 Avenue Paul Vaillant-Couturier, 94807 Villejuif Cedex, France.', 'France|France|France', 68, 'Algorithms|Biomarkers, Tumor|Breast Neoplasms|Computer Simulation|Data Interpretation, Statistical|Diagnosis, Computer-Assisted|False Positive Reactions|Gene Expression Profiling|Humans|Leukemia|Models, Genetic|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis', 'Comparative Study', '10.1093/bioinformatics/bti063', '15479710', 'The most used criterion in microarray data analysis is nowadays the false discovery rate (FDR). In the framework of estimating procedures based on the marginal distribution of the P-values without any assumption on gene expression changes, estimators of the FDR are necessarily conservatively biased. Indeed, only an upper bound estimate can be obtained for the key quantity pi0, which is the probability for a gene to be unmodified. In this paper, we propose a novel family of estimators for pi0 that allows the calculation of FDR.'),
(71696, 2005, 'bio', 'Database driven test case generation for protein-protein docking', 'Zöllner, Frank|Neumann, Steffen|Kummert, Franz|Sagerer, Gerhard', 'Applied Computer Science, Faculty of Technology, Bielefeld University D-33594 Bielefeld, Germany. fzoellne@techfak.uni-bielefeld.de|Applied Computer Science, Faculty of Technology, Bielefeld University D-33594 Bielefeld, Germany. fzoellne@techfak.uni-bielefeld.de|Applied Computer Science, Faculty of Technology, Bielefeld University D-33594 Bielefeld, Germany. fzoellne@techfak.uni-bielefeld.de|Applied Computer Science, Faculty of Technology, Bielefeld University D-33594 Bielefeld, Germany. fzoellne@techfak.uni-bielefeld.de', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Benchmarking|Binding Sites|Databases, Protein|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/bti061', '15479711', 'We present a method for automatic test case generation for protein-protein docking. A consensus-type approach is proposed processing the whole PDB and classifying protein structures into complexes and unbound proteins by combining information from three different approaches (current PDB-at-a-glance classification, search of complexes by sequence identical unbound structures and chain naming). Out of this classification test cases are generated automatically. All calculations were run on the database. The information stored is available via a web interface. The user can choose several criteria for generating his own subset out of our test cases, e.g. for testing docking algorithms.'),
(71697, 2005, 'bio', 'TRbase: a database relating tandem repeats to disease genes for the human genome', 'Boby, T|Patch, A-M|Aves, S J', 'School of Biological and Chemical Sciences, Washington Singer Laboratories, University of Exeter, Perry Road, Exeter EX4 4QG, UK.|School of Biological and Chemical Sciences, Washington Singer Laboratories, University of Exeter, Perry Road, Exeter EX4 4QG, UK.|School of Biological and Chemical Sciences, Washington Singer Laboratories, University of Exeter, Perry Road, Exeter EX4 4QG, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Chromosome Mapping|Databases, Genetic|Genetic Predisposition to Disease|Genetic Testing|Genome, Human|Humans|Quantitative Trait Loci|Tandem Repeat Sequences', 'Comparative Study', '10.1093/bioinformatics/bti059', '15479712', 'Tandem repeats are associated with disease genes, play an important role in evolution and are important in genomic organization and function. Although much research has been done on short perfect patterns of repeats, there has been less focus on imperfect repeats. Thus, there is an acute need for a tandem repeats database that provides reliable and up to date information on both perfect and imperfect tandem repeats in the human genome and relates these to disease genes.'),
(71698, 2005, 'bio', 'Understanding protein dispensability through machine-learning analysis of high-throughput data', 'Chen, Yu|Xu, Dong', 'UT-ORNL Graduate School of Genome Science and Technology Oak Ridge, TN, USA.|UT-ORNL Graduate School of Genome Science and Technology Oak Ridge, TN, USA.', 'United States|United States', 65, 'Artificial Intelligence|Gene Deletion|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Protein Interaction Mapping|Proteins|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/bti058', '15479713', 'Protein dispensability is fundamental to the understanding of gene function and evolution. Recent advances in generating high-throughput data such as genomic sequence data, protein-protein interaction data, gene-expression data and growth-rate data of mutants allow us to investigate protein dispensability systematically at the genome scale.'),
(71699, 2005, 'bio', 'Bayesian analysis of signaling networks governing embryonic stem cell fate decisions', 'Woolf, Peter J|Prudhomme, Wendy|Daheron, Laurence|Daley, George Q|Lauffenburger, Douglas A', 'Department of Chemical Engineering, University of Michigan, Room 3320, G. G. Brown Building, 2300 Hayward Street, Ann Arbor, MI 48109-2125, USA. pwoolf@umich.edu|Department of Chemical Engineering, University of Michigan, Room 3320, G. G. Brown Building, 2300 Hayward Street, Ann Arbor, MI 48109-2125, USA. pwoolf@umich.edu|Department of Chemical Engineering, University of Michigan, Room 3320, G. G. Brown Building, 2300 Hayward Street, Ann Arbor, MI 48109-2125, USA. pwoolf@umich.edu|Department of Chemical Engineering, University of Michigan, Room 3320, G. G. Brown Building, 2300 Hayward Street, Ann Arbor, MI 48109-2125, USA. pwoolf@umich.edu|Department of Chemical Engineering, University of Michigan, Room 3320, G. G. Brown Building, 2300 Hayward Street, Ann Arbor, MI 48109-2125, USA. pwoolf@umich.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Artificial Intelligence|Bayes Theorem|Cell Differentiation|Cell Proliferation|Cell Survival|Cells, Cultured|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Mice|Models, Biological|Models, Statistical|Proteome|Signal Transduction|Stem Cells|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti056', '15479714', 'Signaling events that direct mouse embryonic stem (ES) cell self-renewal and differentiation are complex and accordingly difficult to understand in an integrated manner. We address this problem by adapting a Bayesian network learning algorithm to model proteomic signaling data for ES cell fate responses to external cues. Using this model we were able to characterize the signaling pathway influences as quantitative, logic-circuit type interactions. Our experimental dataset includes measurements for 28 signaling protein phosphorylation states across 16 different factorial combinations of cytokine and matrix stimuli as reported previously.'),
(71700, 2005, 'bio', 'Improving conformational searches by geometric screening', 'Zhang, Ming|White, R Allen|Wang, Liqun|Goldman, Ronald|Kavraki, Lydia|Hassett, Brendan', 'Department of Biostatistics and Applied Mathematics, The University of Texas M.D. Anderson Cancer Center Houston, TX 77030, USA. mzhang@mdanderson.org|Department of Biostatistics and Applied Mathematics, The University of Texas M.D. Anderson Cancer Center Houston, TX 77030, USA. mzhang@mdanderson.org|Department of Biostatistics and Applied Mathematics, The University of Texas M.D. Anderson Cancer Center Houston, TX 77030, USA. mzhang@mdanderson.org|Department of Biostatistics and Applied Mathematics, The University of Texas M.D. Anderson Cancer Center Houston, TX 77030, USA. mzhang@mdanderson.org|Department of Biostatistics and Applied Mathematics, The University of Texas M.D. Anderson Cancer Center Houston, TX 77030, USA. mzhang@mdanderson.org|Department of Biostatistics and Applied Mathematics, The University of Texas M.D. Anderson Cancer Center Houston, TX 77030, USA. mzhang@mdanderson.org', 'United States|United States|United States|United States|United States|United States', 18, 'Algorithms|Computer Simulation|Models, Chemical|Models, Molecular|Protein Conformation|Protein Interaction Mapping|Proteins|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti055', '15479715', 'Conformational searches in molecular docking are a time-consuming process with wide range of applications. Favorable conformations of the ligands that successfully bind with receptors are sought to form stable ligand-receptor complexes. Usually a large number of conformations are generated and their binding energies are examined. We propose adding a geometric screening phase before an energy minimization procedure so that only conformations that geometrically fit in the binding site will be prompted for energy calculation.'),
(71701, 2005, 'bio', 'Circular genome visualization and exploration using CGView', 'Stothard, Paul|Wishart, David S', 'Department of Biological Sciences and Computing Science, University of Alberta Edmonton, Alberta, Canada T6G 2E8.|Department of Biological Sciences and Computing Science, University of Alberta Edmonton, Alberta, Canada T6G 2E8.', 'Canada|Canada', 239, 'Chromosome Mapping|Computer Graphics|Database Management Systems|Information Storage and Retrieval|Programming Languages|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti054', '15479716', 'CGView (Circular Genome Viewer) is a Java application and library for generating high-quality, zoomable maps of circular genomes. It converts XML or tab-delimited input into a graphical map (PNG, JPG or Scalable Vector Graphics format), complete with sequence features, labels, legends and footnotes. In addition to the default full view map, the program can generate a series of hyperlinked maps showing expanded views. The linked maps can be explored using any Web browser, allowing rapid genome browsing and facilitating data sharing.'),
(71702, 2005, 'bio', 'OCRE: a novel domain made of imperfect, aromatic-rich octamer repeats', 'Callebaut, Isabelle|Mornon, Jean-Paul', 'Département de Biologie Structurale, LMCP, CNRS UMR7590, Universités Paris 6 & Paris 7, Case 115, 4 place Jussieu, 75252 Paris Cedex 05, France. Isabelle. Callebaut@lmcp.jussieu.fr|Département de Biologie Structurale, LMCP, CNRS UMR7590, Universités Paris 6 & Paris 7, Case 115, 4 place Jussieu, 75252 Paris Cedex 05, France. Isabelle. Callebaut@lmcp.jussieu.fr', 'France|France', 0, 'Angiogenic Proteins|Hydrocarbons, Aromatic|Intracellular Signaling Peptides and Proteins|Pattern Recognition, Automated|Protein Structure, Tertiary|RNA|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bti065', '15486042', 'In this study, we describe a novel domain, OCRE, which is shared by the recently identified angiogenic factor VG5Q and a specific family of RNA-binding motif proteins. The OCRE domain is characterized by a 5-fold, imperfectly repeated octameric sequence, which includes a triplet of often-conserved aromatic amino acids predicted to form a beta-strand and in which the slightly modified fifth repeat might act as a repeat terminator. Although the function of this domain remains to be elucidated, the domain architecture of OCRE containing proteins and experimental data suggest a role in RNA metabolism and/or in signalling pathways activated by the tumor necrosis factor superfamily of cytokines.'),
(71703, 2005, 'bio', 'Reconstructing biological networks using conditional correlation analysis', 'Rice, John Jeremy|Tu, Yuhai|Stolovitzky, Gustavo', 'Computational Biology Center, IBM T.J. Watson Research Center, PO Box 218, Yorktown Heights, NY 10598, USA.|Computational Biology Center, IBM T.J. Watson Research Center, PO Box 218, Yorktown Heights, NY 10598, USA.|Computational Biology Center, IBM T.J. Watson Research Center, PO Box 218, Yorktown Heights, NY 10598, USA.', 'United States|United States|United States', 83, 'Algorithms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Signal Transduction|Statistics as Topic|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti064', '15486043', 'One of the present challenges in biological research is the organization of the data originating from high-throughput technologies. One way in which this information can be organized is in the form of networks of influences, physical or statistical, between cellular components. We propose an experimental method for probing biological networks, analyzing the resulting data and reconstructing the network architecture.'),
(71704, 2005, 'bio', 'Comparison of different melting temperature calculation methods for short DNA sequences', 'Panjkovich, Alejandro|Melo, Francisco', 'Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Alameda 340, Santiago, Chile.|Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Alameda 340, Santiago, Chile.', 'Chile|Chile', 19, 'Algorithms|Benchmarking|Computer Simulation|Models, Chemical|Oligonucleotides|Sequence Analysis, DNA|Software|Transition Temperature', 'Comparative Study', '10.1093/bioinformatics/bti066', '15501913', 'The overall performance of several molecular biology techniques involving DNA/DNA hybridization depends on the accurate prediction of the experimental value of a critical parameter: the melting temperature Tm. Till date, many computer software programs based on different methods and/or parameterizations are available for the theoretical estimation of the experimental Tm value of any given short oligonucleotide sequence. However, in most cases, large and significant differences in the estimations of Tm were obtained while using different methods. Thus, it is difficult to decide which Tm value is the accurate one. In addition, it seems that most people who use these methods are unaware about the limitations, which are well described in the literature but not stated properly or restricted the inputs of most of the web servers and standalone software programs that implement them.'),
(71705, 2005, 'bio', 'PSORTb v20: expanded prediction of bacterial protein subcellular localization and insights gained from comparative proteome analysis', 'Gardy, J L|Laird, M R|Chen, F|Rey, S|Walsh, C J|Ester, M|Brinkman, F S L', 'Department of Molecular Biology and Biochemistry, Simon Fraser University Burnaby, BC, Canada V5A 1S6.|Department of Molecular Biology and Biochemistry, Simon Fraser University Burnaby, BC, Canada V5A 1S6.|Department of Molecular Biology and Biochemistry, Simon Fraser University Burnaby, BC, Canada V5A 1S6.|Department of Molecular Biology and Biochemistry, Simon Fraser University Burnaby, BC, Canada V5A 1S6.|Department of Molecular Biology and Biochemistry, Simon Fraser University Burnaby, BC, Canada V5A 1S6.|Department of Molecular Biology and Biochemistry, Simon Fraser University Burnaby, BC, Canada V5A 1S6.|Department of Molecular Biology and Biochemistry, Simon Fraser University Burnaby, BC, Canada V5A 1S6.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 595, 'Algorithms|Bacterial Proteins|Gene Expression Profiling|Gram-Negative Bacteria|Gram-Positive Bacteria|Proteome|Sequence Alignment|Sequence Analysis, Protein|Software|Subcellular Fractions', 'Comparative Study', '10.1093/bioinformatics/bti057', '15501914', 'PSORTb v.1.1 is the most precise bacterial localization prediction tool available. However, the programs predictive coverage and recall are low and the method is only applicable to Gram-negative bacteria. The goals of the present work are as follows: increase PSORTbs coverage while maintaining the existing precision level, expand it to include Gram-positive bacteria and then carry out a comparative analysis of localization.'),
(71706, 2005, 'bio', 'HyPhy: hypothesis testing using phylogenies', 'Pond, Sergei L Kosakovsky|Frost, Simon D W|Muse, Spencer V', 'Antiviral Research Center, University of California San Diego San Diego, CA 92103, USA.|Antiviral Research Center, University of California San Diego San Diego, CA 92103, USA.|Antiviral Research Center, University of California San Diego San Diego, CA 92103, USA.', 'United States|United States|United States', 991, 'Algorithms|Computer Simulation|Evolution, Molecular|Models, Genetic|Phylogeny|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti079', '15509596', 'The HyPhypackage is designed to provide a flexible and unified platform for carrying out likelihood-based analyses on multiple alignments of molecular sequence data, with the emphasis on studies of rates and patterns of sequence evolution.'),
(71707, 2005, 'bio', 'COPS--cis/trans peptide bond conformation prediction of amino acids on the basis of secondary structure information', 'Pahlke, Doreen|Leitner, Dietmar|Wiedemann, Urs|Labudde, Dirk', 'Forschungsinstitut für Molekulare Pharmakologie Robert-Rössle-Str. 10, 13125 Berlin, Germany.|Forschungsinstitut für Molekulare Pharmakologie Robert-Rössle-Str. 10, 13125 Berlin, Germany.|Forschungsinstitut für Molekulare Pharmakologie Robert-Rössle-Str. 10, 13125 Berlin, Germany.|Forschungsinstitut für Molekulare Pharmakologie Robert-Rössle-Str. 10, 13125 Berlin, Germany.', 'Germany|Germany|Germany|Germany', 23, 'Algorithms|Amino Acids|Binding Sites|Isomerism|Peptides|Protein Binding|Protein Conformation|Protein Structure, Secondary|Proteins|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/bti089', '15509597', 'COPS predicts for all 20 naturally occurring amino acids whether the peptide bond in a protein is in cis or trans conformation. The algorithm is based only on secondary structure information of amino acid triplets without considering the amino acid sequence information. Conformation parameters are derived from solved 3D structures deposited in the PDB and led to propensities based on modified Chou-Fasman parameters. COPS analyses amino acid triplets taking only their respective secondary structure into consideration and upon application of a set of rules utilizing the conformation parameters, the N-terminal peptide bond conformation of the middle residue is predicted. COPS was tested on a random selection of protein datasets.'),
(71708, 2005, 'bio', 'LabArray: real-time imaging and analytical tool for microarrays', 'Ng, Johnson Kian-Kok|Liu, Wen-Tso', 'Division of Bioengineering 10 Kent Ridge Crescent, Singapore 119260, Singapore.|Division of Bioengineering 10 Kent Ridge Crescent, Singapore 119260, Singapore.', 'Singapore|Singapore', 9, 'Algorithms|Computer Systems|Gene Expression Profiling|Image Interpretation, Computer-Assisted|In Situ Hybridization, Fluorescence|Microscopy, Fluorescence|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti088', '15509598', 'Microarrays have been used to perform high-throughput genetic analyses such as single-nucleotide polymorphisms detection and microbial genome analysis. Some of these analyses require real-time monitoring of the hybridization signals with respect to a varying experimental condition, such as temperature. However, current microarray imaging and analysis packages typically do not possess such real-time capabilities. Therefore, microarray image analyses are often time-consuming and labour-intensive. LabArray was developed to expedite such processes by enabling real-time monitoring of microarray signals.'),
(71709, 2005, 'bio', 'MedKit: a helper toolkit for automatic mining of MEDLINE/PubMed citations', 'Ding, Jing|Berleant, Daniel', 'Department of Electrical and Computer Engineering, Iowa State University Ames, IA 50011, USA.|Department of Electrical and Computer Engineering, Iowa State University Ames, IA 50011, USA.', 'United States|United States', 0, 'Abstracting and Indexing as Topic|Artificial Intelligence|Database Management Systems|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Periodicals as Topic|PubMed|Software|User-Computer Interface|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/bti087', '15509599', 'MEDLINE/PubMed is one of the most important information sources for bioinformatics text mining. However, there remain limitations in working with MEDLINE/PubMed citations. For example, PubMed imposes an upper limit of 10,000 for downloading PMID list or citations, and MEDLINE files are too large for most off-the-shelf XML parsers. We developed a Java package, MedKit, to work-around the limitations, as well as provide other useful functionalities, e.g. random sampling. Its four modules (querier, sampler, fetcher and parser) can work independently, or be pipelined in various combinations. It can be used as a stand-alone GUI application, or integrated into other text-mining systems. Text mining researchers and others may download and use the toolkit free for non-commercial purposes.'),
(71710, 2005, 'bio', 'Statistical analysis of domains in interacting protein pairs', 'Nye, Tom M W|Berzuini, Carlo|Gilks, Walter R|Babu, M Madan|Teichmann, Sarah A', 'Medical Research Council Biostatistics Unit, Cambridge, UK. thomas.nye@mrc-bsu.cam.ac.uk|Medical Research Council Biostatistics Unit, Cambridge, UK. thomas.nye@mrc-bsu.cam.ac.uk|Medical Research Council Biostatistics Unit, Cambridge, UK. thomas.nye@mrc-bsu.cam.ac.uk|Medical Research Council Biostatistics Unit, Cambridge, UK. thomas.nye@mrc-bsu.cam.ac.uk|Medical Research Council Biostatistics Unit, Cambridge, UK. thomas.nye@mrc-bsu.cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Binding Sites|Computer Simulation|Databases, Protein|Models, Chemical|Models, Statistical|Protein Binding|Protein Interaction Mapping|Protein Structure, Tertiary|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti086', '15509600', 'Several methods have recently been developed to analyse large-scale sets of physical interactions between proteins in terms of physical contacts between the constituent domains, often with a view to predicting new pairwise interactions. Our aim is to combine genomic interaction data, in which domain-domain contacts are not explicitly reported, with the domain-level structure of individual proteins, in order to learn about the structure of interacting protein pairs. Our approach is driven by the need to assess the evidence for physical contacts between domains in a statistically rigorous way.'),
(71711, 2005, 'bio', 'Automatic extraction of gene/protein biological functions from biomedical text', 'Koike, Asako|Niwa, Yoshiki|Takagi, Toshihisa', 'Department of Computational Biology, Graduate School of Frontier Science, The University of Tokyo Kiban-3A1(CB01) 5-1-5, Kashiwanoha Kashiwa, Chiba 277-8561, Japan. akoike@hgc.jp|Department of Computational Biology, Graduate School of Frontier Science, The University of Tokyo Kiban-3A1(CB01) 5-1-5, Kashiwanoha Kashiwa, Chiba 277-8561, Japan. akoike@hgc.jp|Department of Computational Biology, Graduate School of Frontier Science, The University of Tokyo Kiban-3A1(CB01) 5-1-5, Kashiwanoha Kashiwa, Chiba 277-8561, Japan. akoike@hgc.jp', 'Japan|Japan|Japan', 0, 'Abstracting and Indexing as Topic|Artificial Intelligence|Biology|Database Management Systems|Databases, Bibliographic|Databases, Genetic|Information Storage and Retrieval|Medicine|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Proteins|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/bti084', '15509601', 'With the rapid advancement of biomedical science and the development of high-throughput analysis methods, the extraction of various types of information from biomedical text has become critical. Since automatic functional annotations of genes are quite useful for interpreting large amounts of high-throughput data efficiently, the demand for automatic extraction of information related to gene functions from text has been increasing.'),
(71712, 2005, 'bio', 'Vocabulon: a dictionary model approach for reconstruction and localization of transcription factor binding sites', 'Sabatti, Chiara|Rohlin, Lars|Lange, Kenneth|Liao, James C', 'Department of Human Genetics, UCLA Los Angeles, CA 90095-7088, USA. csabatti@mednet.ucla.edu|Department of Human Genetics, UCLA Los Angeles, CA 90095-7088, USA. csabatti@mednet.ucla.edu|Department of Human Genetics, UCLA Los Angeles, CA 90095-7088, USA. csabatti@mednet.ucla.edu|Department of Human Genetics, UCLA Los Angeles, CA 90095-7088, USA. csabatti@mednet.ucla.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Binding Sites|Models, Chemical|Models, Genetic|Models, Statistical|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Software|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti083', '15509602', 'Gene expression arrays enable measurements of transcription values for a large number or all genes in the genome. In order to better interpret these results and to use them to reconstruct transcription networks, information on location of binding sites for regulatory proteins in the entire genome is needed. In particular, this represents an open problem in Escherichia coli.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71713, 2005, 'bio', 'PDBML: the representation of archival macromolecular structure data in XML', 'Westbrook, John|Ito, Nobutoshi|Nakamura, Haruki|Henrick, Kim|Berman, Helen M', 'Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey 610 Taylor Road, Piscataway, NJ 08854, USA. jwest@rcsb.rutgers.edu|Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey 610 Taylor Road, Piscataway, NJ 08854, USA. jwest@rcsb.rutgers.edu|Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey 610 Taylor Road, Piscataway, NJ 08854, USA. jwest@rcsb.rutgers.edu|Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey 610 Taylor Road, Piscataway, NJ 08854, USA. jwest@rcsb.rutgers.edu|Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey 610 Taylor Road, Piscataway, NJ 08854, USA. jwest@rcsb.rutgers.edu', 'Jersey|Jersey|Jersey|Jersey|Jersey', 109, 'Amino Acid Sequence|Database Management Systems|Databases, Protein|Documentation|Information Storage and Retrieval|Models, Chemical|Molecular Sequence Data|Multiprotein Complexes|Programming Languages|Protein Conformation|Proteins', 'Journal Article', '10.1093/bioinformatics/bti082', '15509603', 'The Protein Data Bank (PDB) has recently released versions of the PDB Exchange dictionary and the PDB archival data files in XML format collectively named PDBML. The automated generation of these XML files is driven by the data dictionary infrastructure in use at the PDB. The correspondences between the PDB dictionary and the XML schema metadata are described as well as the XML representations of PDB dictionaries and data files.'),
(71714, 2005, 'bio', 'A new approach to prediction of short-range conformational propensities in proteins', 'Gront, Dominik|Kolinski, Andrzej', 'Faculty of Chemistry, Warsaw University Pasteura 1, 02-093 Warsaw, Poland. dgront@chem.uw.edu.pl|Faculty of Chemistry, Warsaw University Pasteura 1, 02-093 Warsaw, Poland. dgront@chem.uw.edu.pl', 'Poland|Poland', 0, 'Algorithms|Artificial Intelligence|Computer Simulation|Databases, Protein|Gas Chromatography-Mass Spectrometry|Models, Chemical|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti080', '15509604', 'Knowledge-based potentials are valuable tools for protein structure modeling and evaluation of the quality of the structure prediction obtained by a variety of methods. Potentials of such type could be significantly enhanced by a proper exploitation of the evolutionary information encoded in related protein sequences. The new potentials could be valuable components of threading algorithms, ab-initio protein structure prediction, comparative modeling and structure modeling based on fragmentary experimental data.'),
(71715, 2005, 'bio', 'Implementation of a gene expression index calculation method based on the PDNN model', 'Nielsen, Henrik Bjørn|Gautier, Laurent|Knudsen, Steen', 'Center for Biological Sequence Analysis, BioCentrum-DTU Technical University of Denmark Building 208, DK-2800 Lyngby, Denmark. hbjorn@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU Technical University of Denmark Building 208, DK-2800 Lyngby, Denmark. hbjorn@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU Technical University of Denmark Building 208, DK-2800 Lyngby, Denmark. hbjorn@cbs.dtu.dk', 'Denmark|Denmark|Denmark', 0, 'Algorithms|Computer Simulation|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti078', '15509605', 'Gene expression index calculations from Affymetrix GeneChips have been dominated by the Affymetrix MAS, dChip, and RMA methods. A new method to estimate the gene expression value utilizing the probe sequence information named position-dependent nearest-neighbor (PDNN) has been suggested by Zhang et al. (2003). Here we describe an open source implementation of the PDNN method for the statistical language R.'),
(71716, 2005, 'bio', 'Fast and accurate database homology search using upper bounds of local alignment scores', 'Itoh, Masumi|Goto, Susumu|Akutsu, Tatsuya|Kanehisa, Minoru', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University Gokasho, Uji, Kyoto 611-0011, Japan. itoh@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University Gokasho, Uji, Kyoto 611-0011, Japan. itoh@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University Gokasho, Uji, Kyoto 611-0011, Japan. itoh@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University Gokasho, Uji, Kyoto 611-0011, Japan. itoh@kuicr.kyoto-u.ac.jp', 'Japan|Japan|Japan|Japan', 10, 'Algorithms|Amino Acid Sequence|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti076', '15509606', 'It is widely recognized that homology search and ortholog clustering are very useful for analyzing biological sequences. However, recent growth of sequence database size makes homolog detection difficult, and rapid and accurate methods are required.'),
(71717, 2005, 'bio', 'Local correlation of expression profiles with gene annotations--proof of concept for a general conciliatory method', 'Pinto, F R|Cowart, L Ashley|Hannun, Yusuf A|Rohrer, B|Almeida, J S', 'Biomathematics Group, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa 2781-901 Oeiras, Portugal.|Biomathematics Group, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa 2781-901 Oeiras, Portugal.|Biomathematics Group, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa 2781-901 Oeiras, Portugal.|Biomathematics Group, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa 2781-901 Oeiras, Portugal.|Biomathematics Group, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa 2781-901 Oeiras, Portugal.', 'Portugal|Portugal|Portugal|Portugal|Portugal', 0, 'Algorithms|Animals|Computer Simulation|Feasibility Studies|Gene Expression Profiling|Gene Expression Regulation|Mice|Models, Biological|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae Proteins|Signal Transduction|Software|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/bti074', '15509607', 'Integrated analysis of expression data and gene ontology annotations is a prime example of biological data that need co-explanatory interpretation. This particular application is used to validate a new method for integrated analysis of varied biological information.'),
(71718, 2005, 'bio', 'Profile-based detection of microRNA precursors in animal genomes', 'Legendre, Matthieu|Lambert, André|Gautheret, Daniel', 'INSERM ERM-206 Luminy Case 928, 13288 Marseille Cedex 09, France.|INSERM ERM-206 Luminy Case 928, 13288 Marseille Cedex 09, France.|INSERM ERM-206 Luminy Case 928, 13288 Marseille Cedex 09, France.', 'France|France|France', 0, 'Algorithms|Animals|Base Sequence|Chromosome Mapping|Databases, Genetic|Gene Expression Profiling|MicroRNAs|Molecular Sequence Data|RNA Precursors|Sequence Alignment|Sequence Analysis, RNA', 'Comparative Study', '10.1093/bioinformatics/bti073', '15509608', 'MicroRNAs (miRNA) are essential 21-22 nt regulatory RNAs produced from larger hairpin-like precursors. Local sequence alignment tools such as BLAST are able to identify new members of known miRNA families, but not all of them. We set out to estimate how many new miRNAs could be recovered using a profile-based strategy such as that implemented in the ERPIN program.'),
(71719, 2005, 'bio', 'ColorHOR--novel graphical algorithm for fast scan of alpha satellite higher-order repeats and HOR annotation for GenBank sequence of human genome', 'Paar, Vladimir|Pavin, Nenad|Rosandic, Marija|Gluncic, Matko|Basar, Ivan|Pezer, Robert|Zinic, Sonja Durajlija', 'Faculty of Science, University of Zagreb Bijenicka 32, 10000 Zagreb, Croatia. paar@hazu.hr|Faculty of Science, University of Zagreb Bijenicka 32, 10000 Zagreb, Croatia. paar@hazu.hr|Faculty of Science, University of Zagreb Bijenicka 32, 10000 Zagreb, Croatia. paar@hazu.hr|Faculty of Science, University of Zagreb Bijenicka 32, 10000 Zagreb, Croatia. paar@hazu.hr|Faculty of Science, University of Zagreb Bijenicka 32, 10000 Zagreb, Croatia. paar@hazu.hr|Faculty of Science, University of Zagreb Bijenicka 32, 10000 Zagreb, Croatia. paar@hazu.hr|Faculty of Science, University of Zagreb Bijenicka 32, 10000 Zagreb, Croatia. paar@hazu.hr', 'Croatia|Croatia|Croatia|Croatia|Croatia|Croatia|Croatia', 15, 'Algorithms|Chromosome Mapping|Chromosomes, Human, Pair 1|Color|Computer Graphics|Consensus Sequence|DNA, Satellite|Database Management Systems|Databases, Nucleic Acid|Genome, Human|Humans|Information Storage and Retrieval|Microsatellite Repeats|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti072', '15509609', 'GenBank data are at present lacking alpha satellite higher-order repeat (HOR) annotation. Furthermore, exact HOR consensus lengths have not been reported so far. Given the fast growth of sequence databases in the centromeric region, it is of increasing interest to have efficient tools for computational identification and analysis of HORs from known sequences.'),
(71720, 2005, 'bio', 'The construction of amino acid substitution matrices for the comparison of proteins with non-standard compositions', 'Yu, Yi-Kuo|Altschul, Stephen F', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health Bethesda, MD 20894, USA.', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Amino Acid Substitution|Amino Acids|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bti070', '15509610', 'Amino acid substitution matrices play a central role in protein alignment methods. Standard log-odds matrices, such as those of the PAM and BLOSUM series, are constructed from large sets of protein alignments having implicit background amino acid frequencies. However, these matrices frequently are used to compare proteins with markedly different amino acid compositions, such as transmembrane proteins or proteins from organisms with strongly biased nucleotide compositions. It has been argued elsewhere that standard matrices are not ideal for such comparisons and, furthermore, a rationale has been presented for transforming a standard matrix for use in a non-standard compositional context.'),
(71721, 2005, 'bio', 'Inferring pathways from gene lists using a literature-derived network of biological relationships', 'Rajagopalan, Dilip|Agarwal, Pankaj', 'Bioinformatics Sciences, GlaxoSmithKline Pharmaceuticals R&D, 709 Swedeland Road, UW2230, King of Prussia, PA 19406-0939, USA. dilip_rajagopalan@gsk.com|Bioinformatics Sciences, GlaxoSmithKline Pharmaceuticals R&D, 709 Swedeland Road, UW2230, King of Prussia, PA 19406-0939, USA. dilip_rajagopalan@gsk.com', 'United States|United States', 87, 'Algorithms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Biological|Natural Language Processing|Periodicals as Topic|Proteome|Signal Transduction|Transcription Factors|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/bti069', '15509611', 'A number of omic technologies such as transcriptional profiling, proteomics, literature searches, genetic association, etc. help in the identification of sets of important genes. A subset of these genes may act in a coordinated manner, possibly because they are part of the same biological pathway. Interpreting such gene lists and relating them to pathways is a challenging task. Databases of biological relationships between thousands of mammalian genes can help in deciphering omics data. The relationships between genes can be assembled into a biological network with each protein as a node and each relationship as an edge between two proteins (or nodes). This network may then be searched for subnetworks consisting largely of interesting genes from the omics experiment. The subset of genes in the subnetwork along with the web of relationships between them helps to decipher the underlying pathways. Finding such subnetworks that maximally include all proteins from the query set but few others is the focus for this paper.'),
(71722, 2005, 'bio', 'An enzyme mechanism language for the mathematical modeling of metabolic pathways', 'Yang, Chin-Rang|Shapiro, Bruce E|Mjolsness, Eric D|Hatfield, G Wesley', 'Department of Microbiology and Molecular Genetics, College of Medicine, University of California, Irvine, CA 92697, USA.|Department of Microbiology and Molecular Genetics, College of Medicine, University of California, Irvine, CA 92697, USA.|Department of Microbiology and Molecular Genetics, College of Medicine, University of California, Irvine, CA 92697, USA.|Department of Microbiology and Molecular Genetics, College of Medicine, University of California, Irvine, CA 92697, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|Enzymes|Gene Expression Regulation|Models, Biological|Models, Chemical|Programming Languages|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/bti068', '15509612', 'As a first step toward the elucidation of the systems biology of complex biological systems, it was our goal to mathematically model common enzyme catalytic and regulatory mechanisms that repeatedly appear in biological processes such as signal transduction and metabolic pathways.'),
(71723, 2005, 'bio', 'Relational patterns of gene expression via non-metric multidimensional scaling analysis', 'Taguchi, Y-H|Oono, Y', 'Department of Physics, Faculty of Science and Technology, Chuo University, 1-13-27 Kasuga, Tokyo 112-8551, Japan. tag@granular.com|Department of Physics, Faculty of Science and Technology, Chuo University, 1-13-27 Kasuga, Tokyo 112-8551, Japan. tag@granular.com', 'Japan|Japan', 118, 'Algorithms|Cells, Cultured|Fibroblasts|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Biological|Models, Genetic|Models, Statistical|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Signal Transduction|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti067', '15509613', 'Microarray experiments result in large-scale data sets that require extensive mining and refining to extract useful information. We demonstrate the usefulness of (non-metric) multidimensional scaling (MDS) method in analyzing a large number of genes. Applying MDS to the microarray data is certainly not new, but the existing works are all on small numbers (< 100) of points to be analyzed. We have been developing an efficient novel algorithm for non-metric MDS (nMDS) analysis for very large data sets as a maximally unsupervised data mining device. We wish to demonstrate its usefulness in the context of bioinformatics (unraveling relational patterns among genes from time series data in this paper).'),
(71724, 2005, 'bio', 'Identifying differentially expressed genes from microarray experiments via statistic synthesis', 'Yang, Yee Hwa|Xiao, Yuanyuan|Segal, Mark R', 'Departments of Medicine, Center for Bioinformatics and Molecular Biostatistics, University of California San Francisco, CA 94143, USA.|Departments of Medicine, Center for Bioinformatics and Molecular Biostatistics, University of California San Francisco, CA 94143, USA.|Departments of Medicine, Center for Bioinformatics and Molecular Biostatistics, University of California San Francisco, CA 94143, USA.', 'United States|United States|United States', 0, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bti108', '15513985', 'A common objective of microarray experiments is the detection of differential gene expression between samples obtained under different conditions. The task of identifying differentially expressed genes consists of two aspects: ranking and selection. Numerous statistics have been proposed to rank genes in order of evidence for differential expression. However, no one statistic is universally optimal and there is seldom any basis or guidance that can direct toward a particular statistic of choice.'),
(71725, 2005, 'bio', 'Theoretical and practical advances in genome halving', 'Yin, Peng|Hartemink, Alexander J', 'Department of Computer Science, Duke University Box 90129, Durham, NC 27708-0129, USA. py@cs.duke.edu|Department of Computer Science, Duke University Box 90129, Durham, NC 27708-0129, USA. py@cs.duke.edu', 'United States|United States', 0, 'Algorithms|Chromosome Mapping|Computer Simulation|Evolution, Molecular|Gene Duplication|Genetic Linkage|Genetic Variation|Genome, Fungal|Models, Genetic|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bti107', '15513986', 'Duplication of an organisms entire genome is a rare but spectacular event, enabling the rapid emergence of multiple new gene functions. Over time, the parallel linkage of duplicated genes across chromosomes may be disrupted by reciprocal translocations, while the intra-chromosomal order of genes may be shuffled by inversions and transpositions. Some duplicate genes may evolve unrecognizably or be deleted. As a consequence, the only detectable signature of an ancient duplication event in a modern genome may be the presence of various chromosomal segments containing parallel paralogous genes, with each segment appearing exactly twice in the genome. The problem of reconstructing the linkage structure of an ancestral genome before duplication is known as genome halving with unordered chromosomes.'),
(71726, 2005, 'bio', 'GOChase: correcting errors from Gene Ontology-based annotations for gene products', 'Park, Yu Rang|Park, Chan Hee|Kim, Ju Han', 'Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 110-799, Korea.|Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 110-799, Korea.|Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 110-799, Korea.', '-|-|-', 0, 'Database Management Systems|Databases, Protein|Documentation|Information Storage and Retrieval|Natural Language Processing|Proteins|Quality Control|Software|User-Computer Interface|Vocabulary, Controlled|Word Processing', 'Evaluation Studies', '10.1093/bioinformatics/bti106', '15513987', 'The Gene Ontology (GO) is a controlled biological vocabulary that provides three structured networks of terms to describe biological processes, cellular components and molecular functions. Many databases of gene products are annotated using the GO vocabularies. We found that some GO-updating operations are not easily traceable by the current biological databases and GO browsers. Consequently, numerous annotation errors arise and are propagated throughout biological databases and GO-based high-level analyses. GOChase is a set of web-based utilities to detect and correct the errors in GO-based annotations.'),
(71727, 2005, 'bio', 'Normalization of two-channel microarray experiments: a semiparametric approach', 'Eckel, J E|Gennings, C|Therneau, T M|Burgoon, L D|Boverhof, D R|Zacharewski, T R', 'Department of Health Sciences Research, Mayo Clinic Rochester, MN 55905, USA. eckel@mayo.edu|Department of Health Sciences Research, Mayo Clinic Rochester, MN 55905, USA. eckel@mayo.edu|Department of Health Sciences Research, Mayo Clinic Rochester, MN 55905, USA. eckel@mayo.edu|Department of Health Sciences Research, Mayo Clinic Rochester, MN 55905, USA. eckel@mayo.edu|Department of Health Sciences Research, Mayo Clinic Rochester, MN 55905, USA. eckel@mayo.edu|Department of Health Sciences Research, Mayo Clinic Rochester, MN 55905, USA. eckel@mayo.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Dose-Response Relationship, Drug|Ethinyl Estradiol|Female|Gene Expression Profiling|Gene Expression Regulation|Liver|Mice|Mice, Inbred C57BL|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis', 'Comparative Study', '10.1093/bioinformatics/bti105', '15513988', 'An important underlying assumption of any experiment is that the experimental subjects are similar across levels of the treatment variable, so that changes in the response variable can be attributed to exposure to the treatment under study. This assumption is often not valid in the analysis of a microarray experiment due to systematic biases in the measured expression levels related to experimental factors such as spot location (often referred to as a print-tip effect), arrays, dyes, and various interactions of these effects. Thus, normalization is a critical initial step in the analysis of a microarray experiment, where the objective is to balance the individual signal intensity levels across the experimental factors, while maintaining the effect due to the treatment under investigation.'),
(71728, 2005, 'bio', 'Predicting protein localization in budding yeast', 'Chou, Kuo-Chen|Cai, Yu-Dong', 'Gordon Life Science Institute San Diego, CA 92130, USA. kchou@san.rr.com|Gordon Life Science Institute San Diego, CA 92130, USA. kchou@san.rr.com', 'United States|United States', 103, 'Algorithms|Fungal Proteins|Proteins|Saccharomycetales|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship|Subcellular Fractions|Tissue Distribution', 'Evaluation Studies', '10.1093/bioinformatics/bti104', '15513989', 'Most of the existing methods in predicting protein subcellular location were used to deal with the cases limited within the scope from two to five localizations, and only a few of them can be effectively extended to cover the cases of 12-14 localizations. This is because the more the locations involved are, the poorer the success rate would be. Besides, some proteins may occur in several different subcellular locations, i.e. bear the feature of multiplex locations. So far there is no method that can be used to effectively treat the difficult multiplex location problem. The present study was initiated in an attempt to address (1) how to efficiently identify the localization of a query protein among many possible subcellular locations, and (2) how to deal with the case of multiplex locations.'),
(71729, 2005, 'bio', 'Genetic algorithm optimization for pre-processing and variable selection of spectroscopic data', 'Jarvis, Roger M|Goodacre, Royston', 'Department of Chemistry, UMIST, PO Box 88, Sackville St, Manchester M60 1QD, UK.|Department of Chemistry, UMIST, PO Box 88, Sackville St, Manchester M60 1QD, UK.', 'United Kingdom|United Kingdom', 0, 'Algorithms|Fungal Proteins|Gene Expression Profiling|Gene Expression Regulation, Fungal|Gibberella|Models, Genetic|Proteome|Spectroscopy, Fourier Transform Infrared', 'Comparative Study', '10.1093/bioinformatics/bti102', '15513990', 'The major difficulties relating to mathematical modelling of spectroscopic data are inconsistencies in spectral reproducibility and the black box nature of the modelling techniques. For the analysis of biological samples the first problem is due to biological, experimental and machine variability which can lead to sample size differences and unavoidable baseline shifts. Consequently, there is often a requirement for mathematical correction(s) to be made to the raw data if the best possible model is to be formed. The second problem prevents interpretation of the results since the variables that most contribute to the analysis are not easily revealed, as a result, the opportunity to obtain new knowledge from such data is lost.'),
(71730, 2005, 'bio', 'hp-DPI: Helicobacter pylori database of protein interactomes--embracing experimental and inferred interactions', 'Lin, Chung-Yen|Chen, Chia-Ling|Cho, Chi-Shiang|Wang, Li-Ming|Chang, Chia-Ming|Chen, Pao-Yang|Lo, Chen-Zen|Hsiung, Chao A', 'Division of Biostatistics and Bioinformatics, National Health Research Institutes, #128, Sec. 2 Yaun-Chio-Yun Rd, Taipei 115, Taiwan. cylin@nhri.org.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, #128, Sec. 2 Yaun-Chio-Yun Rd, Taipei 115, Taiwan. cylin@nhri.org.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, #128, Sec. 2 Yaun-Chio-Yun Rd, Taipei 115, Taiwan. cylin@nhri.org.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, #128, Sec. 2 Yaun-Chio-Yun Rd, Taipei 115, Taiwan. cylin@nhri.org.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, #128, Sec. 2 Yaun-Chio-Yun Rd, Taipei 115, Taiwan. cylin@nhri.org.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, #128, Sec. 2 Yaun-Chio-Yun Rd, Taipei 115, Taiwan. cylin@nhri.org.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, #128, Sec. 2 Yaun-Chio-Yun Rd, Taipei 115, Taiwan. cylin@nhri.org.tw|Division of Biostatistics and Bioinformatics, National Health Research Institutes, #128, Sec. 2 Yaun-Chio-Yun Rd, Taipei 115, Taiwan. cylin@nhri.org.tw', '-|-|-|-|-|-|-|-', 9, 'Algorithms|Bacterial Proteins|Computer Graphics|Database Management Systems|Databases, Protein|Documentation|Helicobacter pylori|Information Storage and Retrieval|Online Systems|Protein Interaction Mapping|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti101', '15513991', 'We implemented a statistical model into our protein interaction database for validation of two-hybrid assays of Helicobacter pylori, and prediction of putative protein interactions not yet discovered experimentally. To present the enormous amount of experimental and inferred protein interaction networking maps, the H.pylori Database of Protein Interactomes (hp-DPI) is developed with a succinct yet comprehensive visualization tool integrated with annotation from Genbank, GO, and KEGG. hp-DPI is first built with, but not limited to, H.pylori protein interactions and is expected to naturally include other organisms protein interacting relationships in the future.'),
(71731, 2005, 'bio', 'DPRml: distributed phylogeny reconstruction by maximum likelihood', 'Keane, T M|Naughton, T J|Travers, S A A|McInerney, J O|McCormack, G P', 'Department of Computer Science, National University of Ireland Maynooth, Ireland.|Department of Computer Science, National University of Ireland Maynooth, Ireland.|Department of Computer Science, National University of Ireland Maynooth, Ireland.|Department of Computer Science, National University of Ireland Maynooth, Ireland.|Department of Computer Science, National University of Ireland Maynooth, Ireland.', 'Ireland|Ireland|Ireland|Ireland|Ireland', 40, 'Algorithms|Computer Simulation|Evolution, Molecular|Likelihood Functions|Models, Genetic|Models, Statistical|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bti100', '15513992', 'In recent years there has been increased interest in producing large and accurate phylogenetic trees using statistical approaches. However for a large number of taxa, it is not feasible to construct large and accurate trees using only a single processor. A number of specialized parallel programs have been produced in an attempt to address the huge computational requirements of maximum likelihood. We express a number of concerns about the current set of parallel phylogenetic programs which are currently severely limiting the widespread availability and use of parallel computing in maximum likelihood-based phylogenetic analysis.'),
(71732, 2005, 'bio', 'Evolutionary optimization with data collocation for reverse engineering of biological networks', 'Tsai, Kuan-Yao|Wang, Feng-Sheng', 'Department of Chemical Engineering, National Chung Cheng University, Chia-yi 621-02, Taiwan.|Department of Chemical Engineering, National Chung Cheng University, Chia-yi 621-02, Taiwan.', '-|-', 128, 'Algorithms|Computer Simulation|Databases, Factual|Evolution, Molecular|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Signal Transduction|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bti099', '15513993', 'Modern experimental biology is moving away from analyses of single elements to whole-organism measurements. Such measured time-course data contain a wealth of information about the structure and dynamic of the pathway or network. The dynamic modeling of the whole systems is formulated as a reverse problem that requires a well-suited mathematical model and a very efficient computational method to identify the model structure and parameters. Numerical integration for differential equations and finding global parameter values are still two major challenges in this field of the parameter estimation of nonlinear dynamic biological systems.'),
(71733, 2005, 'bio', 'PDZBase: a protein-protein interaction database for PDZ-domains', 'Beuming, Thijs|Skrabanek, Lucy|Niv, Masha Y|Mukherjee, Piali|Weinstein, Harel', 'Department of Physiology and Biophysics, Weill Medical College of Cornell University, 1300 York Ave., New York, NY 10021, USA.|Department of Physiology and Biophysics, Weill Medical College of Cornell University, 1300 York Ave., New York, NY 10021, USA.|Department of Physiology and Biophysics, Weill Medical College of Cornell University, 1300 York Ave., New York, NY 10021, USA.|Department of Physiology and Biophysics, Weill Medical College of Cornell University, 1300 York Ave., New York, NY 10021, USA.|Department of Physiology and Biophysics, Weill Medical College of Cornell University, 1300 York Ave., New York, NY 10021, USA.', 'United States|United States|United States|United States|United States', 0, 'Database Management Systems|Databases, Protein|Information Storage and Retrieval|Membrane Proteins|Natural Language Processing|Periodicals as Topic|Protein Interaction Mapping|Protein Structure, Tertiary|User-Computer Interface|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/bti098', '15513994', 'PDZBase is a database that aims to contain all known PDZ-domain-mediated protein-protein interactions. Currently, PDZBase contains approximately 300 such interactions, which have been manually extracted from > 200 articles. The database can be queried through both sequence motif and keyword-based searches, and the sequences of interacting proteins can be visually inspected through alignments (for the comparison of several interactions), or as residue-based diagrams including schematic secondary structure information (for individual complexes).'),
(71734, 2005, 'bio', 'COBrA: a bio-ontology editor', 'Aitken, Stuart|Korf, Roman|Webber, Bonnie|Bard, Jonathan', 'School of Informatics, The University of Edinburgh, Edinburgh EH8 9LE, UK. stuart@aiai.ed.ac.uk|School of Informatics, The University of Edinburgh, Edinburgh EH8 9LE, UK. stuart@aiai.ed.ac.uk|School of Informatics, The University of Edinburgh, Edinburgh EH8 9LE, UK. stuart@aiai.ed.ac.uk|School of Informatics, The University of Edinburgh, Edinburgh EH8 9LE, UK. stuart@aiai.ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 13, 'Cell Physiological Phenomena|Computer Graphics|Documentation|Models, Biological|Natural Language Processing|Phylogeny|Software|User-Computer Interface|Vocabulary, Controlled|Word Processing', 'Journal Article', '10.1093/bioinformatics/bti097', '15513995', 'COBrA is a Java-based ontology editor for bio-ontologies that distinguishes itself from other editors by supporting the linking of concepts between two ontologies, and providing sophisticated analysis and verification functions. In addition to the Gene Ontology and Open Biology Ontologies formats, COBrA can import and export ontologies in the Semantic Web formats RDF, RDFS and OWL.'),
(71735, 2005, 'bio', 'Finding regulatory modules through large-scale gene-expression data analysis', 'Kloster, M|Tang, C|Wingreen, N S', 'Department of Physics, Princeton University, Princeton, NJ 08544, USA.|Department of Physics, Princeton University, Princeton, NJ 08544, USA.|Department of Physics, Princeton University, Princeton, NJ 08544, USA.', 'United States|United States|United States', 27, 'Algorithms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Signal Transduction|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bti096', '15513996', 'The use of gene microchips has enabled a rapid accumulation of gene-expression data. One of the major challenges of analyzing this data is the diversity, in both size and signal strength, of the various modules in the gene regulatory networks of organisms.'),
(71736, 2005, 'bio', 'Clustering of gene expression data using a local shape-based similarity measure', 'Balasubramaniyan, Rajarajeswari|Hüllermeier, Eyke|Weskamp, Nils|Kämper, Jörg', 'Max-Planck Institute for Terrestrial Microbiology, Department of Organismic Interactions Karl-von-Frisch-Strasse, 35043 Marburg, Germany.|Max-Planck Institute for Terrestrial Microbiology, Department of Organismic Interactions Karl-von-Frisch-Strasse, 35043 Marburg, Germany.|Max-Planck Institute for Terrestrial Microbiology, Department of Organismic Interactions Karl-von-Frisch-Strasse, 35043 Marburg, Germany.|Max-Planck Institute for Terrestrial Microbiology, Department of Organismic Interactions Karl-von-Frisch-Strasse, 35043 Marburg, Germany.', 'Germany|Germany|Germany|Germany', 87, 'Algorithms|Cell Cycle|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Fungal|Models, Biological|Pattern Recognition, Automated|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Comparative Study', '10.1093/bioinformatics/bti095', '15513997', 'Microarray technology enables the study of gene expression in large scale. The application of methods for data analysis then allows for grouping genes that show a similar expression profile and that are thus likely to be co-regulated. A relationship among genes at the biological level often presents itself by locally similar and potentially time-shifted patterns in their expression profiles.'),
(71737, 2005, 'bio', 'Extracting relations between promoter sequences and their strengths from microarray data', 'Kiryu, Hisanori|Oshima, Taku|Asai, Kiyoshi', 'Graduate School of Information Sciences, Nara Institute of Science and Technology 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan. hisano-k@is.aist-nara.ac.jp|Graduate School of Information Sciences, Nara Institute of Science and Technology 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan. hisano-k@is.aist-nara.ac.jp|Graduate School of Information Sciences, Nara Institute of Science and Technology 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan. hisano-k@is.aist-nara.ac.jp', 'Japan|Japan|Japan', 16, 'Algorithms|Artificial Intelligence|Escherichia coli|Escherichia coli Proteins|Gene Expression Profiling|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Promoter Regions, Genetic|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bti094', '15513998', 'The relations between the promoter sequences and their strengths were extensively studied in the 1980s. Although these studies uncovered strong sequence-strength correlations, the cost of their elaborate experimental methods have been too high to be applied to a large number of promoters. On the contrary, a recent increase in the microarray data allows us to compare thousands of gene expressions with their DNA sequences.'),
(71738, 2005, 'bio', 'Comparison of computational methods for the identification of cell cycle-regulated genes', 'de Lichtenberg, Ulrik|Jensen, Lars Juhl|Fausbøll, Anders|Jensen, Thomas S|Bork, Peer|Brunak, Søren', 'Center for Biological Sequence Analysis, Technical University of Denmark DK-2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Technical University of Denmark DK-2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Technical University of Denmark DK-2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Technical University of Denmark DK-2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Technical University of Denmark DK-2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Technical University of Denmark DK-2800 Lyngby, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 152, 'Algorithms|Cell Cycle Proteins|Computational Biology|Gene Expression Profiling|Gene Expression Regulation, Fungal|Genes, cdc|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bti093', '15513999', 'DNA microarrays have been used extensively to study the cell cycle transcription programme in a number of model organisms. The Saccharomyces cerevisiae data in particular have been subjected to a wide range of bioinformatics analysis methods, aimed at identifying the correct and complete set of periodically expressed genes.'),
(71739, 2005, 'bio', 'A novel means of using gene clusters in a two-step empirical Bayes method for predicting classes of samples', 'Ji, Yuan|Tsui, Kam-Wah|Kim, Kyungmann', 'Department of Biostatistics and Applied Mathematics, The University of Texas M.D. Anderson Cancer Center Houston, TX 77030, USA. yuanji@mdanderson.org|Department of Biostatistics and Applied Mathematics, The University of Texas M.D. Anderson Cancer Center Houston, TX 77030, USA. yuanji@mdanderson.org|Department of Biostatistics and Applied Mathematics, The University of Texas M.D. Anderson Cancer Center Houston, TX 77030, USA. yuanji@mdanderson.org', 'United States|United States|United States', 5, 'Algorithms|Bayes Theorem|Biomarkers, Tumor|Cluster Analysis|Gene Expression Profiling|Gene Expression Regulation|Humans|Leukemia|Models, Biological|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bti092', '15514000', 'The classification of samples using gene expression profiles is an important application in areas such as cancer research and environmental health studies. However, the classification is usually based on a small number of samples, and each sample is a long vector of thousands of gene expression levels. An important issue in parametric modeling for so many gene expression levels is the control of the number of nuisance parameters in the model. Large models often lead to intensive or even intractable computation, while small models may be inadequate for complex data.'),
(71740, 2005, 'bio', 'BACCardI--a tool for the validation of genomic assemblies, assisting genome finishing and intergenome comparison', 'Bartels, Daniela|Kespohl, Sebastian|Albaum, Stefan|Drüke, Tanja|Goesmann, Alexander|Herold, Julia|Kaiser, Olaf|Pühler, Alfred|Pfeiffer, Friedhelm|Raddatz, Günter|Stoye, Jens|Meyer, Folker|Schuster, Stephan C', 'Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.|Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.|Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.|Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.|Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.|Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.|Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.|Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.|Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.|Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.|Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.|Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.|Universität Bielefeld, Center for Biotechnology (CeBiTec) D-33594 Bielefeld, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 29, 'Algorithms|Base Sequence|Benchmarking|Chromosome Mapping|Computer Graphics|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bti091', '15514001', 'We provide the graphical tool BACCardI for the construction of virtual clone maps from standard assembler output files or BLAST based sequence comparisons. This new tool has been applied to numerous genome projects to solve various problems including (a) validation of whole genome shotgun assemblies, (b) support for contig ordering in the finishing phase of a genome project, and (c) intergenome comparison between related strains when only one of the strains has been sequenced and a large insert library is available for the other. The BACCardI software can seamlessly interact with various sequence assembly packages.'),
(71741, 2005, 'bio', 'Relation between weight matrix and substitution matrix: motif search by similarity', 'Zheng, Wei-Mou', 'Institute of Theoretical Physics, Academia Sinica Beijing 100080, China. zheng@itp.ac.cn', 'China', 6, 'Algorithms|Amino Acid Motifs|Computer Simulation|Conserved Sequence|Databases, Protein|Models, Chemical|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bti090', '15514002', 'The discovery of patterns shared by several sequences that differ greatly is a basic task in sequence analysis, and still a challenge. Several methods have been developed for detecting patterns. Methods commonly used for motif search include the Gibbs sampler, Expectation-Maximization (EM) algorithm and some intuitive greedy approaches. One cannot guarantee the optimality of the result produced by the Gibbs sampler in a single run. The deterministic EM methods tend to get trapped by local optima. Solutions found by greedy approaches are rarely sufficiently good.'),
(71742, 2005, 'bio', 'Superior feature-set ranking for small samples using bolstered error estimation', 'Sima, Chao|Braga-Neto, Ulisses|Dougherty, Edward R', 'Department of Electrical Engineering, Texas A&M University College Station, TX, USA.|Department of Electrical Engineering, Texas A&M University College Station, TX, USA.|Department of Electrical Engineering, Texas A&M University College Station, TX, USA.', 'United States|United States|United States', 40, 'Algorithms|Biomarkers, Tumor|Breast Neoplasms|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Biological|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bti081', '15514003', 'Ranking feature sets is a key issue for classification, for instance, phenotype classification based on gene expression. Since ranking is often based on error estimation, and error estimators suffer to differing degrees of imprecision in small-sample settings, it is important to choose a computationally feasible error estimator that yields good feature-set ranking.'),
(71743, 2005, 'bio', 'Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm', 'Kimura, Shuhei|Ide, Kaori|Kashihara, Aiko|Kano, Makoto|Hatakeyama, Mariko|Masui, Ryoji|Nakagawa, Noriko|Yokoyama, Shigeyuki|Kuramitsu, Seiki|Konagaya, Akihiko', 'Bioinformatics Group, RIKEN Genomic Sciences Center 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan. skimura@gsc.riken.jp|Bioinformatics Group, RIKEN Genomic Sciences Center 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan. skimura@gsc.riken.jp|Bioinformatics Group, RIKEN Genomic Sciences Center 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan. skimura@gsc.riken.jp|Bioinformatics Group, RIKEN Genomic Sciences Center 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan. skimura@gsc.riken.jp|Bioinformatics Group, RIKEN Genomic Sciences Center 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan. skimura@gsc.riken.jp|Bioinformatics Group, RIKEN Genomic Sciences Center 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan. skimura@gsc.riken.jp|Bioinformatics Group, RIKEN Genomic Sciences Center 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan. skimura@gsc.riken.jp|Bioinformatics Group, RIKEN Genomic Sciences Center 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan. skimura@gsc.riken.jp|Bioinformatics Group, RIKEN Genomic Sciences Center 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan. skimura@gsc.riken.jp|Bioinformatics Group, RIKEN Genomic Sciences Center 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan. skimura@gsc.riken.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 217, 'Algorithms|Artificial Intelligence|Evolution, Molecular|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Signal Transduction|Software|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bti071', '15514004', 'To resolve the high-dimensionality of the genetic network inference problem in the S-system model, a problem decomposition strategy has been proposed. While this strategy certainly shows promise, it cannot provide a model readily applicable to the computational simulation of the genetic network when the given time-series data contain measurement noise. This is a significant limitation of the problem decomposition, given that our analysis and understanding of the genetic network depend on the computational simulation.'),
(71744, 2005, 'bio', 'Accurate identification of alternatively spliced exons using support vector machine', 'Dror, Gideon|Sorek, Rotem|Shamir, Ron', 'The Academic College of Tel-Aviv-Yaffo, Tel Aviv 4044, Israel. gideon@mta.ac.il|The Academic College of Tel-Aviv-Yaffo, Tel Aviv 4044, Israel. gideon@mta.ac.il|The Academic College of Tel-Aviv-Yaffo, Tel Aviv 4044, Israel. gideon@mta.ac.il', 'Israel|Israel|Israel', 0, 'Algorithms|Alternative Splicing|Animals|Artificial Intelligence|Chromosome Mapping|Conserved Sequence|Evolution, Molecular|Exons|Humans|Mice|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bti132', '15531599', 'Alternative splicing is a major component of the regulatory action on mammalian transcriptomes. It is estimated that over half of all human genes have more than one splice variant. Previous studies have shown that alternatively spliced exons possess several features that distinguish them from constitutively spliced ones. Recently, we have demonstrated that such features can be used to distinguish alternative from constitutive exons. In the current study, we used advanced machine learning methods to generate robust classifier of alternative exons.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71745, 2005, 'bio', 'Intervention in context-sensitive probabilistic Boolean networks', 'Pal, Ranadip|Datta, Aniruddha|Bittner, Michael L|Dougherty, Edward R', 'Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.', 'United States|United States|United States|United States', 147, 'Algorithms|Animals|Cell Line, Tumor|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Logistic Models|Melanoma|Mice|Models, Biological|Models, Statistical|Neoplasm Proteins|Proto-Oncogene Proteins|Signal Transduction|Transcription Factors|Wnt Proteins|Wnt-5a Protein', 'Comparative Study', '10.1093/bioinformatics/bti131', '15531600', 'Intervention in a gene regulatory network is used to help it avoid undesirable states, such as those associated with a disease. Several types of intervention have been studied in the framework of a probabilistic Boolean network (PBN), which is essentially a finite collection of Boolean networks in which at any discrete time point the gene state vector transitions according to the rules of one of the constituent networks. For an instantaneously random PBN, the governing Boolean network is randomly chosen at each time point. For a context-sensitive PBN, the governing Boolean network remains fixed for an interval of time until a binary random variable determines a switch. The theory of automatic control has been previously applied to find optimal strategies for manipulating external (control) variables that affect the transition probabilities of an instantaneously random PBN to desirably affect its dynamic evolution over a finite time horizon. This paper extends the methods of external control to context-sensitive PBNs.'),
(71746, 2005, 'bio', 'Non-sequential structure-based alignments reveal topology-independent core packing arrangements in proteins', 'Yuan, Xin|Bystroff, Christopher', 'Department of Biology, Rensselaer Polytechnic Institute Troy, NY 12180, USA.|Department of Biology, Rensselaer Polytechnic Institute Troy, NY 12180, USA.', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Conserved Sequence|Markov Chains|Models, Chemical|Models, Statistical|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti128', '15531601', 'Proteins of the same class often share a secondary structure packing arrangement but differ in how the secondary structure units are ordered in the sequence. We find that proteins that share a common core also share local sequence-structure similarities, and these can be exploited to align structures with different topologies. In this study, segments from a library of local sequence-structure alignments were assembled hierarchically, enforcing the compactness and conserved inter-residue contacts but not sequential ordering. Previous structure-based alignment methods often ignore sequence similarity, local structural equivalence and compactness.'),
(71747, 2005, 'bio', 'A simple statistical method for discriminating outer membrane proteins with better accuracy', 'Gromiha, M Michael|Suwa, Makiko', 'Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST) Aomi Frontier Building 17F, 2-43 Aomi, Koto-ku, Tokyo 135-0064, Japan. michael-gromiha@aist.go.jp|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST) Aomi Frontier Building 17F, 2-43 Aomi, Koto-ku, Tokyo 135-0064, Japan. michael-gromiha@aist.go.jp', 'Japan|Japan', 82, 'Algorithms|Cell Membrane|Computer Simulation|Membrane Proteins|Models, Biological|Models, Chemical|Models, Statistical|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bti126', '15531602', 'Discriminating outer membrane proteins from other folding types of globular and membrane proteins is an important task both for identifying outer membrane proteins from genomic sequences and for the successful prediction of their secondary and tertiary structures.'),
(71748, 2005, 'bio', 'Protein homology detection by HMM-HMM comparison', 'Söding, Johannes', 'Department of Protein Evolution, Max-Planck-Institute for Developmental Biology Spemannstrasse 35, D-72076 Tübingen, Germany. johannes.soeding@tuebingen.mpg.de', 'Germany', 0, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Computer Simulation|Markov Chains|Models, Chemical|Models, Statistical|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/bti125', '15531603', 'Protein homology detection and sequence alignment are at the basis of protein structure prediction, function prediction and evolution.'),
(71749, 2005, 'bio', 'A Java tool for dynamic web-based 3D visualization of anatomy and overlapping gene or protein expression patterns', 'Gerth, Victor E|Vize, Peter D', 'Department of Biological Science, University of Calgary, Alberta T2N 1N4, Canada.|Department of Biological Science, University of Calgary, Alberta T2N 1N4, Canada.', 'Canada|Canada', 6, 'Computer Graphics|Image Interpretation, Computer-Assisted|Imaging, Three-Dimensional|Internet|Models, Anatomic|Models, Biological|Programming Languages|Proteins|Tissue Distribution|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti120', '15531604', 'The Gene Expression Viewer is a web-launched three-dimensional visualization tool, tailored to compare surface reconstructions of multi-channel image volumes generated by confocal microscopy or micro-CT.'),
(71750, 2005, 'bio', 'OMGProm: a database of orthologous mammalian gene promoters', 'Palaniswamy, Saranyan K|Jin, Victor X|Sun, Hao|Davuluri, Ramana V', 'Human Cancer Genetics Program, Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA.|Human Cancer Genetics Program, Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA.|Human Cancer Genetics Program, Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA.|Human Cancer Genetics Program, Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA.', 'United States|United States|United States|United States', 17, 'Animals|Chromosome Mapping|Conserved Sequence|Database Management Systems|Databases, Nucleic Acid|Evolution, Molecular|Genome, Human|Humans|Information Storage and Retrieval|Internet|Mice|Promoter Regions, Genetic|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti119', '15531605', 'Sequence comparisons between human and rodents are increasingly being used for the identification of gene regulatory regions. The effectiveness of such an approach largely depends on the quality and availability of promoter sequences. We developed OMGProm by integrating three data sources: (1) experimentally supported full-length cDNA, promoter and first exon sequences, (2) homology information from HomoloGene and (3) the human and mouse genomic sequences. The current version of OMGProm contains 8550 promoter pairs of 6373 orthologous human and mouse genes, where supporting experimental evidence for transcription start site annotation exists in at least one species.'),
(71751, 2005, 'bio', 'Sensitivity, principal component and flux analysis applied to signal transduction: the case of epidermal growth factor mediated signaling', 'Liu, Gang|Swihart, Mark T|Neelamegham, Sriram', 'Department of Chemical and Biological Engineering, State University of New York at Buffalo Buffalo, NY 14260, USA.|Department of Chemical and Biological Engineering, State University of New York at Buffalo Buffalo, NY 14260, USA.|Department of Chemical and Biological Engineering, State University of New York at Buffalo Buffalo, NY 14260, USA.', 'United States|United States|United States', 0, 'Algorithms|Animals|Computer Simulation|Databases, Factual|Energy Metabolism|Epidermal Growth Factor|Extracellular Signal-Regulated MAP Kinases|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Biological|Principal Component Analysis|Sensitivity and Specificity|Signal Transduction|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti118', '15531606', 'Novel high-throughput genomic and proteomic tools are allowing the integration of information from a range of biological assays into a single conceptual framework. This framework is often described as a network of biochemical reactions. We present strategies for the analysis of such networks.'),
(71752, 2005, 'bio', 'Extracting multiple structural alignments from pairwise alignments: a comparison of a rigorous and a heuristic approach', 'Sandelin, Erik', 'Stockholm Bioinformatics Center, AlbaNova, Stockholm University, 106 91 Stockholm, Sweden. erik@sbc.su.se', 'Sweden', 5, 'Algorithms|Amino Acid Sequence|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/bti117', '15531607', 'Multiple structural alignments (MSTAs) provide position-specific information on the sequence variability allowed by protein folds. This information can be exploited to better understand the evolution of proteins and the physical chemistry of polypeptide folding. Most MSTA methods rely on a pre-computed library of pairwise alignments. This library will in general contain conflicting residue equivalences not all of which can be realized in the final MSTA. Hence to build a consistent MSTA, these methods have to select a conflict-free subset of equivalences.'),
(71753, 2005, 'bio', 'The MIPS mammalian protein-protein interaction database', 'Pagel, Philipp|Kovac, Stefan|Oesterheld, Matthias|Brauner, Barbara|Dunger-Kaltenbach, Irmtraud|Frishman, Goar|Montrone, Corinna|Mark, Pekka|Stümpflen, Volker|Mewes, Hans-Werner|Ruepp, Andreas|Frishman, Dmitrij', 'Institute for Bioinformatics/MIPS, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.|Institute for Bioinformatics/MIPS, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.|Institute for Bioinformatics/MIPS, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.|Institute for Bioinformatics/MIPS, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.|Institute for Bioinformatics/MIPS, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.|Institute for Bioinformatics/MIPS, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.|Institute for Bioinformatics/MIPS, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.|Institute for Bioinformatics/MIPS, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.|Institute for Bioinformatics/MIPS, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.|Institute for Bioinformatics/MIPS, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.|Institute for Bioinformatics/MIPS, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.|Institute for Bioinformatics/MIPS, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Animals|Database Management Systems|Databases, Protein|Documentation|Information Storage and Retrieval|Internet|Mammals|Natural Language Processing|Periodicals as Topic|Protein Interaction Mapping|Software|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bti115', '15531608', 'The MIPS mammalian protein-protein interaction database (MPPI) is a new resource of high-quality experimental protein interaction data in mammals. The content is based on published experimental evidence that has been processed by human expert curators. We provide the full dataset for download and a flexible and powerful web interface for users with various requirements.'),
(71754, 2005, 'bio', 'Classification using partial least squares with penalized logistic regression', 'Fort, Gersende|Lambert-Lacroix, Sophie', 'CNRS/LMC-IMAG BP 53, 38041 Grenoble cedex 9, France.|CNRS/LMC-IMAG BP 53, 38041 Grenoble cedex 9, France.', 'France|France', 25, 'Algorithms|Biomarkers, Tumor|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Least-Squares Analysis|Models, Genetic|Models, Statistical|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Regression Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bti114', '15531609', 'One important aspect of data-mining of microarray data is to discover the molecular variation among cancers. In microarray studies, the number n of samples is relatively small compared to the number p of genes per sample (usually in thousands). It is known that standard statistical methods in classification are efficient (i.e. in the present case, yield successful classifiers) particularly when n is (far) larger than p. This naturally calls for the use of a dimension reduction procedure together with the classification one.'),
(71755, 2005, 'bio', 'CGH-Explorer: a program for analysis of array-CGH data', 'Lingjaerde, Ole Christian|Baumbusch, Lars O|Liestøl, Knut|Glad, Ingrid K|Børresen-Dale, Anne-Lise', 'Department of Informatics, University of Oslo, PO Box 1080 Blindern, N-0316 Oslo, Norway. ole@ifi.uio.no|Department of Informatics, University of Oslo, PO Box 1080 Blindern, N-0316 Oslo, Norway. ole@ifi.uio.no|Department of Informatics, University of Oslo, PO Box 1080 Blindern, N-0316 Oslo, Norway. ole@ifi.uio.no|Department of Informatics, University of Oslo, PO Box 1080 Blindern, N-0316 Oslo, Norway. ole@ifi.uio.no|Department of Informatics, University of Oslo, PO Box 1080 Blindern, N-0316 Oslo, Norway. ole@ifi.uio.no', 'Norway|Norway|Norway|Norway|Norway', 118, 'Computer Graphics|DNA Mutational Analysis|Gene Dosage|Gene Expression Profiling|Genetic Variation|In Situ Hybridization|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti113', '15531610', 'CGH-Explorer is a program for visualization and statistical analysis of microarray-based comparative genomic hybridization (array-CGH) data. The program has preprocessing facilities, tools for graphical exploration of individual arrays or groups of arrays, and tools for statistical identification of regions of amplification and deletion.'),
(71756, 2005, 'bio', 'GoArrays: highly dynamic and efficient microarray probe design', 'Rimour, Sébastien|Hill, David|Militon, Cécile|Peyret, Pierre', 'LIMOS UMR CNRS 6158, Blaise Pascal University, Clermont-Ferrand II BP 10125, 63177 Aubiere Cedex, France. rimour@isima.fr|LIMOS UMR CNRS 6158, Blaise Pascal University, Clermont-Ferrand II BP 10125, 63177 Aubiere Cedex, France. rimour@isima.fr|LIMOS UMR CNRS 6158, Blaise Pascal University, Clermont-Ferrand II BP 10125, 63177 Aubiere Cedex, France. rimour@isima.fr|LIMOS UMR CNRS 6158, Blaise Pascal University, Clermont-Ferrand II BP 10125, 63177 Aubiere Cedex, France. rimour@isima.fr', 'France|France|France|France', 22, 'Algorithms|Animals|Computer-Aided Design|Encephalitozoon cuniculi|Equipment Design|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Software|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bti112', '15531611', 'The use of oligonucleotide microarray technology requires a very detailed attention to the design of specific probes spotted on the solid phase. These problems are far from being commonplace since they refer to complex physicochemical constraints. Whereas there are more and more publicly available programs for microarray oligonucleotide design, most of them use the same algorithm or criteria to design oligos, with only little variation.'),
(71757, 2005, 'bio', 'In silico gene function prediction using ontology-based pattern identification', 'Zhou, Yingyao|Young, Jason A|Santrosyan, Andrey|Chen, Kaisheng|Yan, S Frank|Winzeler, Elizabeth A', 'Genomics Institute of the Novartis Research Foundation San Diego, CA 92121, USA. zhou@gnf.org|Genomics Institute of the Novartis Research Foundation San Diego, CA 92121, USA. zhou@gnf.org|Genomics Institute of the Novartis Research Foundation San Diego, CA 92121, USA. zhou@gnf.org|Genomics Institute of the Novartis Research Foundation San Diego, CA 92121, USA. zhou@gnf.org|Genomics Institute of the Novartis Research Foundation San Diego, CA 92121, USA. zhou@gnf.org|Genomics Institute of the Novartis Research Foundation San Diego, CA 92121, USA. zhou@gnf.org', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Plasmodium falciparum', 'Evaluation Studies', '10.1093/bioinformatics/bti111', '15531612', 'With the emergence of genome-wide expression profiling data sets, the guilt by association (GBA) principle has been a cornerstone for deriving gene functional interpretations in silico. Given the limited success of traditional methods for producing clusters of genes with great amounts of functional similarity, new data-mining algorithms are required to fully exploit the potential of high-throughput genomic approaches.'),
(71758, 2005, 'bio', 'The SBW-MATLAB interface', 'Wellock, Cameron|Chickarmane, Vijay|Sauro, Herbert M', 'Keck Graduate Institute, Claremont, CA 91711, USA. cwellock@kgi.edu|Keck Graduate Institute, Claremont, CA 91711, USA. cwellock@kgi.edu|Keck Graduate Institute, Claremont, CA 91711, USA. cwellock@kgi.edu', 'United States|United States|United States', 7, 'Computer Communication Networks|Information Storage and Retrieval|Programming Languages|Software|Systems Biology|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti110', '15531613', 'The SBW-MATLAB Interface allows MATLAB users to take advantage of the wide variety of tools available through SBW, the Systems Biology Workbench (Sauro et al. (2003) OMICS, 7, 355-372). It also enables MATLAB users to themselves create SBW-enabled tools which can be freely distributed.'),
(71759, 2005, 'bio', 'An alternative model of amino acid replacement', 'Crooks, Gavin E|Brenner, Steven E', 'Department of Plant and Microbial Biology 111 Koshland Hall #3102 University of California Berkeley, CA 94720-3102, USA. gec@compbio.berkeley.edu|Department of Plant and Microbial Biology 111 Koshland Hall #3102 University of California Berkeley, CA 94720-3102, USA. gec@compbio.berkeley.edu', 'United States|United States', 15, 'Algorithms|Amino Acid Sequence|Amino Acid Substitution|Computer Simulation|Evolution, Molecular|Markov Chains|Models, Chemical|Models, Genetic|Models, Statistical|Molecular Sequence Data|Phylogeny|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Evaluation Studies', '10.1093/bioinformatics/bti109', '15531614', 'The observed correlations between pairs of homologous protein sequences are typically explained in terms of a Markovian dynamic of amino acid substitution. This model assumes that every location on the protein sequence has the same background distribution of amino acids, an assumption that is incompatible with the observed heterogeneity of protein amino acid profiles and with the success of profile multiple sequence alignment.'),
(71760, 2005, 'bio', 'Predicting gene function through systematic analysis and quality assessment of high-throughput data', 'Kemmeren, Patrick|Kockelkorn, Thessa T J P|Bijma, Theo|Donders, Rogier|Holstege, Frank C P', 'Department of Physiological Chemistry, University Medical Center Utrecht, PO Box 85060, 3508 AB Utrecht, The Netherlands.|Department of Physiological Chemistry, University Medical Center Utrecht, PO Box 85060, 3508 AB Utrecht, The Netherlands.|Department of Physiological Chemistry, University Medical Center Utrecht, PO Box 85060, 3508 AB Utrecht, The Netherlands.|Department of Physiological Chemistry, University Medical Center Utrecht, PO Box 85060, 3508 AB Utrecht, The Netherlands.|Department of Physiological Chemistry, University Medical Center Utrecht, PO Box 85060, 3508 AB Utrecht, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 22, 'Computer Simulation|Database Management Systems|Databases, Protein|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Models, Genetic|Periodicals as Topic|Quality Control|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti103', '15531615', 'Determining gene function is an important challenge arising from the availability of whole genome sequences. Until recently, approaches based on sequence homology were the only high-throughput method for predicting gene function. Use of high-throughput generated experimental data sets for determining gene function has been limited for several reasons.'),
(71761, 2005, 'bio', 'ESTminer: a suite of programs for gene and allele identification', 'Nelson, Rex T|Grant, David|Shoemaker, Randy C', 'USDA-ARS, CICGR Ames, IA, USA. nelsonrt@iastate.edu|USDA-ARS, CICGR Ames, IA, USA. nelsonrt@iastate.edu|USDA-ARS, CICGR Ames, IA, USA. nelsonrt@iastate.edu', 'United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|Consensus Sequence|Database Management Systems|Databases, Genetic|Expressed Sequence Tags|Gene Frequency|Haplotypes|Information Storage and Retrieval|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bti075', '15531616', 'ESTminer is a collection of programs that use expressed sequence tag (EST) data from inbred genomes to identify unique genes within gene families. The algorithm utilizes Cap3 to perform an initial clustering of related EST sequences to produce a consensus sequence of a gene family. These consensus sequences are then used to collect all ESTs in the original EST library that are related using BLAST. A redundancy based criterion is applied to each EST to identify reliable unique gene-sequences. Using a highly inbred genome as a source of ESTs eliminates the necessity of computing covariance on each polymorphism to identify alleles of the same gene, thus making this algorithm more streamlined than other alternatives which must computationally attempt to distinguish genes from alleles.'),
(71762, 2005, 'bio', 'ISYMOD: a knowledge warehouse for the identification, assembly and analysis of bacterial integrated systems', 'Chabalier, Julie|Capponi, Cécile|Quentin, Yves|Fichant, Gwennaele', 'Laboratoire dInformatique Fondamentale de Marseille, 39 rue Joliot Curie 13453 Marseille cedex 13, France. julie.chabalier@ibsm.cnrs-mrs.fr|Laboratoire dInformatique Fondamentale de Marseille, 39 rue Joliot Curie 13453 Marseille cedex 13, France. julie.chabalier@ibsm.cnrs-mrs.fr|Laboratoire dInformatique Fondamentale de Marseille, 39 rue Joliot Curie 13453 Marseille cedex 13, France. julie.chabalier@ibsm.cnrs-mrs.fr|Laboratoire dInformatique Fondamentale de Marseille, 39 rue Joliot Curie 13453 Marseille cedex 13, France. julie.chabalier@ibsm.cnrs-mrs.fr', 'France|France|France|France', 0, 'ATP-Binding Cassette Transporters|Algorithms|Artificial Intelligence|Database Management Systems|Databases, Genetic|Escherichia coli|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Information Storage and Retrieval|Models, Biological|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Systems Integration', 'Evaluation Studies', '10.1093/bioinformatics/bti137', '15531617', 'Complex biological functions emerge from interactions between proteins in stable supra-molecular assemblies and/or through transitory contacts. Most of the time protein partners of the assemblies are composed of one or several domains which exhibit different biochemical functions. Thus the study of cellular process requires the identification of different functional units and their integration in an interaction network, such complexes are referred to as integrated systems. In order to exploit with optimum efficiency the increased release of data, automated bioinformatics strategies are needed to identify, reconstruct and model such systems. For that purpose, we have developed a knowledge warehouse dedicated to the representation and acquisition of bacterial integrated systems involved in the exchange of the bacterial cell with its environment.'),
(71763, 2005, 'bio', 'AUG codons at the beginning of protein coding sequences are frequent in eukaryotic mRNAs with a suboptimal start codon context', 'Kochetov, Alex V', 'Institute of Cytology and Genetics Lavrentieva 10, Novosibirsk 630090 Russia. ak@bionet.nsc.ru', '-', 0, 'Adenine|Animals|Arthropods|Base Sequence|Birds|Chromosome Mapping|Codon, Initiator|Eukaryotic Cells|Gene Frequency|Genetic Variation|Guanine|Humans|Mice|Molecular Sequence Data|Peptide Chain Initiation, Translational|Proteins|RNA, Messenger|Sequence Analysis, RNA|Species Specificity|Trinucleotide Repeats|Uracil', 'Journal Article', '10.1093/bioinformatics/bti136', '15531618', 'The translation start site plays an important role in the control of translation efficiency of eukaryotic mRNAs. However, mRNAs with a suboptimal context of start AUG codon are relatively abundant. It is likely that at least some mRNAs with suboptimal start codon context contain the other signals providing additional information for efficient AUG recognition.'),
(71764, 2005, 'bio', 'A simple tool for drawing proteolytic peptide maps', 'Beynon, Robert J', 'Protein Function Group, Faculty of Veterinary Science, University of Liverpool Crown Street, Liverpool L69 7ZJ, UK. r.beynon@liv.ac.uk', 'United Kingdom', 6, 'Computer Graphics|Peptide Mapping|Peptides|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti077', '15539446', 'I describe a simple standalone program that assists in the preparation of peptide digestion maps. These are useful for comparative studies and for locating peptides within a primary sequence. The program creates an output file as scalable vector graphics that can then be viewed in a web browser or imported into a graphics-editing program.'),
(71765, 2005, 'bio', 'Predicting fold novelty based on ProtoNet hierarchical classification', 'Kifer, Ilona|Sasson, Ori|Linial, Michal', 'Department of Biological Chemistry, Institute of Life Sciences Jerusalem 91904, Israel.|Department of Biological Chemistry, Institute of Life Sciences Jerusalem 91904, Israel.|Department of Biological Chemistry, Institute of Life Sciences Jerusalem 91904, Israel.', 'Israel|Israel|Israel', 0, 'Algorithms|Artificial Intelligence|Cluster Analysis|Databases, Protein|Pattern Recognition, Automated|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bti135', '15539447', 'Structural genomics projects aim to solve a large number of protein structures with the ultimate objective of representing the entire protein space. The computational challenge is to identify and prioritize a small set of proteins with new, currently unknown, superfamilies or folds.'),
(71766, 2005, 'bio', 'Primaclade--a flexible tool to find conserved PCR primers across multiple species', 'Gadberry, Michael D|Malcomber, Simon T|Doust, Andrew N|Kellogg, Elizabeth A', 'Department of Biology, University of Missouri-St. Louis, One University Boulevard, St. Louis, MO 63121, USA.|Department of Biology, University of Missouri-St. Louis, One University Boulevard, St. Louis, MO 63121, USA.|Department of Biology, University of Missouri-St. Louis, One University Boulevard, St. Louis, MO 63121, USA.|Department of Biology, University of Missouri-St. Louis, One University Boulevard, St. Louis, MO 63121, USA.', 'United States|United States|United States|United States', 99, 'Algorithms|Base Sequence|Conserved Sequence|DNA Primers|Molecular Sequence Data|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Species Specificity', 'Evaluation Studies', '10.1093/bioinformatics/bti134', '15539448', 'Primaclade is a web-based application that accepts a multiple species nucleotide alignment file as input and identifies a set of polymerase chain reaction (PCR) primers that will bind across the alignment. Primaclade iteratively runs the Primer3 application for each alignment sequence and collates the results. Primaclade creates an HTML results page that recaps the original alignment, provides a consensus sequence and lists primers for each alignment area, with primers color-coded to reflect the level of degeneracy in the primer.'),
(71767, 2005, 'bio', 'Detection of low level genomic alterations by comparative genomic hybridization based on cDNA micro-arrays', 'Bilke, Sven|Chen, Qing-Rong|Whiteford, Craig C|Khan, Javed', 'Oncogenomics Section, Pediatric Oncology Branch, Advanced Technology Center, National Cancer Institute 8717 Grovemont Circle, Gaithersburg, MD 20877, USA. bilkes@mail.nih.gov|Oncogenomics Section, Pediatric Oncology Branch, Advanced Technology Center, National Cancer Institute 8717 Grovemont Circle, Gaithersburg, MD 20877, USA. bilkes@mail.nih.gov|Oncogenomics Section, Pediatric Oncology Branch, Advanced Technology Center, National Cancer Institute 8717 Grovemont Circle, Gaithersburg, MD 20877, USA. bilkes@mail.nih.gov|Oncogenomics Section, Pediatric Oncology Branch, Advanced Technology Center, National Cancer Institute 8717 Grovemont Circle, Gaithersburg, MD 20877, USA. bilkes@mail.nih.gov', 'United States|United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|Gene Dosage|Gene Expression Profiling|Genetic Testing|Humans|In Situ Hybridization|Models, Genetic|Models, Statistical|Neoplasm Proteins|Neuroblastoma|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bti133', '15539449', 'The accumulation of genomic alterations is an important process in tumor formation and progression. Comparative genomic hybridization performed on cDNA arrays (cDNA aCGH) is a common method to investigate the genomic alterations on a genome-wide scale. However, when detecting low-level DNA copy number changes this technology requires the use of noise reduction strategies due to a low signal to noise ratio.'),
(71768, 2005, 'bio', 'NetAcet: prediction of N-terminal acetylation sites', 'Kiemer, Lars|Bendtsen, Jannick Dyrløv|Blom, Nikolaj', 'Center for Biological Sequence Analysis, BioCentrum-DTU Building 208 Technical University of Denmark, DK-2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, BioCentrum-DTU Building 208 Technical University of Denmark, DK-2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, BioCentrum-DTU Building 208 Technical University of Denmark, DK-2800 Lyngby, Denmark.', 'Denmark|Denmark|Denmark', 0, 'Acetylation|Acetyltransferases|Algorithms|Artificial Intelligence|Binding Sites|Protein Binding|Protein Interaction Mapping|Saccharomyces cerevisiae Proteins|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti130', '15539450', 'We present here a neural network based method for prediction of N-terminal acetylation-by far the most abundant post-translational modification in eukaryotes. The method was developed on a yeast dataset for N-acetyltransferase A (NatA) acetylation, which is the type of N-acetylation for which most examples are known and for which orthologs have been found in several eukaryotes. We obtain correlation coefficients close to 0.7 on yeast data and a sensitivity up to 74% on mammalian data, suggesting that the method is valid for eukaryotic NatA orthologs.'),
(71769, 2005, 'bio', 'A parallel graph decomposition algorithm for DNA sequencing with nanopores', 'Bokhari, Shahid H|Sauer, Jon R', 'Department of Electrical Engineering, UET Lahore-54890, Pakistan. shb@acm.org|Department of Electrical Engineering, UET Lahore-54890, Pakistan. shb@acm.org', 'Pakistan|Pakistan', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Computing Methodologies|DNA, Bacterial|Genome, Bacterial|Molecular Sequence Data|Mycoplasma pneumoniae|Nanotechnology|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bti129', '15539451', 'With the potential availability of nanopore devices that can sense the bases of translocating single-stranded DNA (ssDNA), it is likely that reads of length approximately 10(5) will be available in large numbers and at high speed. We address the problem of complete DNA sequencing using such reads. We assume that approximately 10(2) copies of a DNA sequence are split into single strands that break into randomly sized pieces as they translocate the nanopore in arbitrary orientations. The nanopore senses and reports each individual base that passes through, but all information about orientation and complementarity of the ssDNA subsequences is lost. Random errors (both biological and transduction) in the reads create further complications.'),
(71770, 2005, 'bio', 'An improved algorithm for stoichiometric network analysis: theory and applications', 'Urbanczik, R|Wagner, C', 'Institute of Pharmacology, University of Bern, Friedbuehlstrasse 49, CH-3010 Bern, Switzerland. robert.urbanczik@pki.unibe.ch|Institute of Pharmacology, University of Bern, Friedbuehlstrasse 49, CH-3010 Bern, Switzerland. robert.urbanczik@pki.unibe.ch', 'Switzerland|Switzerland', 81, 'Algorithms|Combinatorial Chemistry Techniques|Computer Simulation|Databases, Factual|Energy Metabolism|Escherichia coli|Escherichia coli Proteins|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Models, Biological|Protein Interaction Mapping|Signal Transduction|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bti127', '15539452', 'Genome scale analysis of the metabolic network of a microorganism is a major challenge in bioinformatics. The combinatorial explosion, which occurs during the construction of elementary fluxes (non-redundant pathways) requires sophisticated and efficient algorithms to tackle the problem.'),
(71771, 2005, 'bio', 'Operon prediction without a training set', 'Westover, B P|Buhler, J D|Sonnenburg, J L|Gordon, J I', 'Department of Computer Science and Engineering, Washington University St. Louis, MO 63130, USA.|Department of Computer Science and Engineering, Washington University St. Louis, MO 63130, USA.|Department of Computer Science and Engineering, Washington University St. Louis, MO 63130, USA.|Department of Computer Science and Engineering, Washington University St. Louis, MO 63130, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Bacteroides|Chromosome Mapping|Escherichia coli|Genome, Bacterial|Models, Genetic|Models, Statistical|Operon|Pattern Recognition, Automated|Software', 'Comparative Study', '10.1093/bioinformatics/bti123', '15539453', 'Annotation of operons in a bacterial genome is an important step in determining an organisms transcriptional regulatory program. While extensive studies of operon structure have been carried out in a few species such as Escherichia coli, fewer resources exist to inform operon prediction in newly sequenced genomes. In particular, many extant operon finders require a large body of training examples to learn the properties of operons in the target organism. For newly sequenced genomes, such examples are generally not available, moreover, a model of operons trained on one species may not reflect the properties of other, distantly related organisms. We encountered these issues in the course of predicting operons in the genome of Bacteroides thetaiotaomicron (B.theta), a common anaerobe that is a prominent component of the normal adult human intestinal microbial community.'),
(71772, 2005, 'bio', 'TMDET: web server for detecting transmembrane regions of proteins by using their 3D coordinates', 'Tusnády, Gábor E|Dosztányi, Zsuzsanna|Simon, István', 'Institute of Enzymology, BRC, Hungarian Academy of Sciences, H-1518 Budapest, PO Box 7, Hungary.|Institute of Enzymology, BRC, Hungarian Academy of Sciences, H-1518 Budapest, PO Box 7, Hungary.|Institute of Enzymology, BRC, Hungarian Academy of Sciences, H-1518 Budapest, PO Box 7, Hungary.', 'Hungary|Hungary|Hungary', 104, 'Algorithms|Computer Simulation|Internet|Membrane Proteins|Models, Chemical|Protein Conformation|Protein Structure, Tertiary|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bti121', '15539454', 'The structure of integral membrane proteins is determined in the absence of the lipid bilayer, consequently the membrane localization of the protein is usually not specified in the corresponding PDB file. Recently, we have developed a new method called TMDET which determines the most possible localization of the membrane relative to the protein structure, and gives the annotation of the membrane embedded parts of the sequence. The entire Protein Data Bank has been scanned by the new TMDET algorithm resulting in the database of structurally determined transmembrane proteins (PDB_TM). Here we present the web interface of the TMDET algorithm to allow scientists to determine the membrane localization of structural data prior to deposition or to analyze model structures.'),
(71773, 2005, 'bio', 'CyDAS: a cytogenetic data analysis system', 'Hiller, Bernhard|Bradtke, Jutta|Balz, Harald|Rieder, Harald', 'Institut für Klinische Genetik der Phillipps-Universität Marburg, Bahnhofstrasse 7, 35037 Marburg, Germany.|Institut für Klinische Genetik der Phillipps-Universität Marburg, Bahnhofstrasse 7, 35037 Marburg, Germany.|Institut für Klinische Genetik der Phillipps-Universität Marburg, Bahnhofstrasse 7, 35037 Marburg, Germany.|Institut für Klinische Genetik der Phillipps-Universität Marburg, Bahnhofstrasse 7, 35037 Marburg, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Chromosome Aberrations|Chromosome Mapping|Cytogenetic Analysis|DNA Mutational Analysis|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti146', '15546933', 'For statistical analyses in cancer cytogenetics, the genomic changes encoded by the karyotype must be translated into numerical codes. We developed a program, which extracts chromosomal gains and losses as well as breakpoints from the karyotype. The changes are compiled in tables according to the chromosome bands involved and/or depicted in projection to the respective chromosome ideogram. The data are ready to be integrated into further statistical analyses. The program may be run as desktop or Internet application.'),
(71774, 2005, 'bio', 'Application of Petri net theory for modelling and validation of the sucrose breakdown pathway in the potato tuber', 'Koch, Ina|Junker, Björn H|Heiner, Monika', 'Department of Bioinformatics, Technical University of Applied Sciences Berlin, Seestrasse 64, Berlin, 13347, Germany. Ina.Koch@tfh-berlin.de|Department of Bioinformatics, Technical University of Applied Sciences Berlin, Seestrasse 64, Berlin, 13347, Germany. Ina.Koch@tfh-berlin.de|Department of Bioinformatics, Technical University of Applied Sciences Berlin, Seestrasse 64, Berlin, 13347, Germany. Ina.Koch@tfh-berlin.de', 'Germany|Germany|Germany', 0, 'Algorithms|Computer Simulation|Databases, Factual|Energy Metabolism|Gene Expression Profiling|Gene Expression Regulation, Plant|Models, Biological|Models, Statistical|Multienzyme Complexes|Neural Networks (Computer)|Plant Proteins|Signal Transduction|Solanum tuberosum|Sucrose|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti145', '15546934', 'Because of the complexity of metabolic networks and their regulation, formal modelling is a useful method to improve the understanding of these systems. An essential step in network modelling is to validate the network model. Petri net theory provides algorithms and methods, which can be applied directly to metabolic network modelling and analysis in order to validate the model. The metabolism between sucrose and starch in the potato tuber is of great research interest. Even if the metabolism is one of the best studied in sink organs, it is not yet fully understood.'),
(71775, 2005, 'bio', 'Solving and analyzing side-chain positioning problems using linear and integer programming', 'Kingsford, Carleton L|Chazelle, Bernard|Singh, Mona', 'Department of Computer Science and the Lewis-Sigler Institute for Integrative Genomics, Princeton University Princeton, NJ 08544, USA.|Department of Computer Science and the Lewis-Sigler Institute for Integrative Genomics, Princeton University Princeton, NJ 08544, USA.|Department of Computer Science and the Lewis-Sigler Institute for Integrative Genomics, Princeton University Princeton, NJ 08544, USA.', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Models, Chemical|Molecular Sequence Data|Numerical Analysis, Computer-Assisted|Programming, Linear|Protein Folding|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti144', '15546935', 'Side-chain positioning is a central component of homology modeling and protein design. In a common formulation of the problem, the backbone is fixed, side-chain conformations come from a rotamer library, and a pairwise energy function is optimized. It is NP-complete to find even a reasonable approximate solution to this problem. We seek to put this hardness result into practical context.'),
(71776, 2005, 'bio', 'Grid cellware: the first grid-enabled tool for modelling and simulating cellular processes', 'Dhar, Pawan K|Meng, Tan Chee|Somani, Sandeep|Ye, Li|Sakharkar, Kishore|Krishnan, Arun|Ridwan, Azmi B M|Wah, Sebastian Ho Kok|Chitre, Mandar|Hao, Zhu', 'Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671. pk@bii-sg.org|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671. pk@bii-sg.org|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671. pk@bii-sg.org|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671. pk@bii-sg.org|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671. pk@bii-sg.org|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671. pk@bii-sg.org|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671. pk@bii-sg.org|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671. pk@bii-sg.org|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671. pk@bii-sg.org|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671. pk@bii-sg.org', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 0, 'Algorithms|Cell Physiological Phenomena|Computer Graphics|Computer Simulation|Gene Expression Regulation|Models, Biological|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti143', '15546936', 'Modelling and simulation of complex cellular transactions involve development of platforms that understand diverse mathematical representations and are capable of handling large backend computations. Grid Cellware, an integrated modelling and simulation tool, has been developed to precisely address these niche requirements of the modelling community. Grid Cellware implements various pathway simulation algorithms along with adaptive Swarm algorithm for parameter estimation. For enchanced computational productivity Grid Cellware uses grid technology with Globus as the middleware.'),
(71777, 2005, 'bio', 'Multiple sequence alignment with user-defined constraints at GOBICS', 'Morgenstern, Burkhard|Werner, Nadine|Prohaska, Sonja J|Steinkamp, Rasmus|Schneider, Isabelle|Subramanian, Amarendran R|Stadler, Peter F|Weyer-Menkhoff, Jan', 'Institut für Mikrobiologie und Genetik, Universität Göttingen, Abteilung für Bioinformatik Goldschmidtstrasse 1, D-37077 Göttingen, Germany. burkhard@gobics.de|Institut für Mikrobiologie und Genetik, Universität Göttingen, Abteilung für Bioinformatik Goldschmidtstrasse 1, D-37077 Göttingen, Germany. burkhard@gobics.de|Institut für Mikrobiologie und Genetik, Universität Göttingen, Abteilung für Bioinformatik Goldschmidtstrasse 1, D-37077 Göttingen, Germany. burkhard@gobics.de|Institut für Mikrobiologie und Genetik, Universität Göttingen, Abteilung für Bioinformatik Goldschmidtstrasse 1, D-37077 Göttingen, Germany. burkhard@gobics.de|Institut für Mikrobiologie und Genetik, Universität Göttingen, Abteilung für Bioinformatik Goldschmidtstrasse 1, D-37077 Göttingen, Germany. burkhard@gobics.de|Institut für Mikrobiologie und Genetik, Universität Göttingen, Abteilung für Bioinformatik Goldschmidtstrasse 1, D-37077 Göttingen, Germany. burkhard@gobics.de|Institut für Mikrobiologie und Genetik, Universität Göttingen, Abteilung für Bioinformatik Goldschmidtstrasse 1, D-37077 Göttingen, Germany. burkhard@gobics.de|Institut für Mikrobiologie und Genetik, Universität Göttingen, Abteilung für Bioinformatik Goldschmidtstrasse 1, D-37077 Göttingen, Germany. burkhard@gobics.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 23, 'Algorithms|Amino Acid Sequence|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti142', '15546937', 'Most multi-alignment methods are fully automated, i.e. they are based on a fixed set of mathematical rules. For various reasons, such methods may fail to produce biologically meaningful alignments. Herein, we describe a semi-automatic approach to multiple sequence alignment where biological expert knowledge can be used to influence the alignment procedure. The user can specify parts of the sequences that are biologically related to each other, our software program uses these sites as anchor points and creates a multiple alignment respecting these user-defined constraints. By using known functionally, structurally or evolutionarily related positions of the input sequences as anchor points, our method can produce alignments that reflect the true biological relationships among the input sequences more accurately than fully automated procedures can do.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71778, 2005, 'bio', 'PermutMatrix: a graphical environment to arrange gene expression profiles in optimal linear order', 'Caraux, Gilles|Pinloche, Sylvie', 'Laboratoire dInformatique de Robotique et de Microélectronique de Montpellier, 161 rue Ada, 34392 Montpellier cedex 5, France. caraux@lirmm.fr|Laboratoire dInformatique de Robotique et de Microélectronique de Montpellier, 161 rue Ada, 34392 Montpellier cedex 5, France. caraux@lirmm.fr', 'France|France', 0, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Linear Models|Models, Biological|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti141', '15546938', 'PermutMatrix is a work space designed to graphically explore gene expression data. It relies on the graphical approach introduced by Eisen and also offers several methods for the optimal reorganization of rows and columns of a numerical dataset. For example, several methods are proposed for optimal reorganization of the leaves of a hierarchical clustering tree, along with several seriation or unidimensional scaling methods that do not require any preliminary hierarchical clustering. This program, developed for MS Windows, with MS-Visual C++, has a clear and efficient graphical interface. Large datasets can be thoroughly and quickly analyzed.'),
(71779, 2005, 'bio', 'Probabilities of spurious connections in gene networks: application to expression time series', 'Bickel, David R', 'Office of Biostatistics and Bioinformatics, Medical College of Georgia, Augusta, GA 30912-4900, USA. bickel@prueba.info', 'Georgia', 22, 'Algorithms|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Signal Transduction|Software|Time Factors|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bti140', '15546939', 'The reconstruction of gene networks from gene-expression microarrays is gaining popularity as methods improve and as more data become available. The reliability of such networks could be judged by the probability that a connection between genes is spurious, resulting from chance fluctuations rather than from a true biological relationship.'),
(71780, 2005, 'bio', 'SlidingBayes: exploring recombination using a sliding window approach based on Bayesian phylogenetic inference', 'Paraskevis, D|Deforche, K|Lemey, P|Magiorkinis, G|Hatzakis, A|Vandamme, A-M', 'Laboratory for Clinical and Epidemiological Virology, Rega Institute for Medical Research, Katholieke Universiteit Leuven, Minderbroedersstraat 10, B-3000 Leuven, Belgium. dparask@cc.uoa.gr|Laboratory for Clinical and Epidemiological Virology, Rega Institute for Medical Research, Katholieke Universiteit Leuven, Minderbroedersstraat 10, B-3000 Leuven, Belgium. dparask@cc.uoa.gr|Laboratory for Clinical and Epidemiological Virology, Rega Institute for Medical Research, Katholieke Universiteit Leuven, Minderbroedersstraat 10, B-3000 Leuven, Belgium. dparask@cc.uoa.gr|Laboratory for Clinical and Epidemiological Virology, Rega Institute for Medical Research, Katholieke Universiteit Leuven, Minderbroedersstraat 10, B-3000 Leuven, Belgium. dparask@cc.uoa.gr|Laboratory for Clinical and Epidemiological Virology, Rega Institute for Medical Research, Katholieke Universiteit Leuven, Minderbroedersstraat 10, B-3000 Leuven, Belgium. dparask@cc.uoa.gr|Laboratory for Clinical and Epidemiological Virology, Rega Institute for Medical Research, Katholieke Universiteit Leuven, Minderbroedersstraat 10, B-3000 Leuven, Belgium. dparask@cc.uoa.gr', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 6, 'Algorithms|Bayes Theorem|Chromosome Mapping|DNA, Viral|HIV-1|Models, Genetic|Models, Statistical|Phylogeny|Recombination, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti139', '15546940', 'We developed a software tool (SlidingBayes) for recombination analysis based on Bayesian phylogenetic inference. Sliding-Bayes provides a powerful approach for detecting potential recombination, especially between highly divergent sequences and complex HIV-1 recombinants for which simpler methods like neighbor joining (NJ) may be less powerful. SlidingBayes guides Markov Chain Monte Carlo (MCMC) sampling performed by MrBayes in a sliding window across the alignment (Bayesian scanning). The tool can be used for nucleotide and amino acid sequences and combines all the modeling possibilities of MrBayes with the ability to plot the posterior probability support for clustering of various combinations of taxa.'),
(71781, 2005, 'bio', 'BRAGI: linking and visualization of database information in a 3D viewer and modeling tool', 'Reichelt, Joachim|Dieterich, Guido|Kvesic, Marsel|Schomburg, Dietmar|Heinz, Dirk W', 'Division of Structural Biology, German Research Centre for Biotechnology (GBF) Mascheroder Weg 1, D-38124, Braunschweig, Germany. Reichelt@gbf.de|Division of Structural Biology, German Research Centre for Biotechnology (GBF) Mascheroder Weg 1, D-38124, Braunschweig, Germany. Reichelt@gbf.de|Division of Structural Biology, German Research Centre for Biotechnology (GBF) Mascheroder Weg 1, D-38124, Braunschweig, Germany. Reichelt@gbf.de|Division of Structural Biology, German Research Centre for Biotechnology (GBF) Mascheroder Weg 1, D-38124, Braunschweig, Germany. Reichelt@gbf.de|Division of Structural Biology, German Research Centre for Biotechnology (GBF) Mascheroder Weg 1, D-38124, Braunschweig, Germany. Reichelt@gbf.de', 'Germany|Germany|Germany|Germany|Germany', 9, 'Amino Acid Sequence|Computer Graphics|Computer Simulation|Database Management Systems|Databases, Protein|Imaging, Three-Dimensional|Information Storage and Retrieval|Models, Chemical|Models, Molecular|Molecular Sequence Data|Proteins|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti138', '15546941', 'BRAGI is a well-established package for viewing and modeling of three-dimensional (3D) structures of biological macromolecules. A new version of BRAGI has been developed that is supported on Windows, Linux and SGI. The user interface has been rewritten to give the standard look and feel of the chosen operating system and to provide a more intuitive, easier usage. A large number of new features have been added. Information from public databases such as SWISS-PROT, InterPro, DALI and OMIM can be displayed in the 3D viewer. Structures can be searched for homologous sequences using the NCBI BLAST server.'),
(71782, 2005, 'bio', 'Identifying subtle interrelated changes in functional gene categories using continuous measures of gene expression', 'Ben-Shaul, Yoram|Bergman, Hagai|Soreq, Hermona', 'Department of Biological Chemistry, The Life Sciences Institute Jerusalem, 91904, Israel.|Department of Biological Chemistry, The Life Sciences Institute Jerusalem, 91904, Israel.|Department of Biological Chemistry, The Life Sciences Institute Jerusalem, 91904, Israel.', 'Israel|Israel|Israel', 25, 'Algorithms|Animals|Computer Simulation|Female|Gene Expression Profiling|Gene Expression Regulation|Genetic Variation|Male|Mice|Models, Genetic|Models, Statistical|Nerve Tissue Proteins|Oligonucleotide Array Sequence Analysis|Parkinson Disease|Pattern Recognition, Automated|Protein Interaction Mapping|Signal Transduction|Software|Time Factors|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bti149', '15550480', 'Analysis of large-scale expression data is greatly facilitated by the availability of gene ontologies (GOs). Many current methods test whether sets of transcripts annotated with specific ontology terms contain an excess of changed transcripts. This approach suffers from two main limitations. First, since gene expression is continuous rather than discrete, designating a gene as changed or unchanged is arbitrary and oblivious to the actual magnitude of the change. Second, by considering only the number of changed genes, finer changes in expression patterns associated with the category may be ignored. Since genes generally participate in multiple networks, widespread and subtle modifications in expression patterns are at least as important as extreme increases/decreases of a few genes.'),
(71783, 2005, 'bio', 'CRAVE: a database, middleware and visualization system for phenotype ontologies', 'Gkoutos, Georgios V|Green, Eain C J|Greenaway, Simon|Blake, Andrew|Mallon, Ann-Marie|Hancock, John M', 'Bioinformatics Group, MRC Mammalian Genetics Unit, Harwell, Oxfordshire OX11 0RD, UK. g.gkoutos@har.mrc.ac.uk|Bioinformatics Group, MRC Mammalian Genetics Unit, Harwell, Oxfordshire OX11 0RD, UK. g.gkoutos@har.mrc.ac.uk|Bioinformatics Group, MRC Mammalian Genetics Unit, Harwell, Oxfordshire OX11 0RD, UK. g.gkoutos@har.mrc.ac.uk|Bioinformatics Group, MRC Mammalian Genetics Unit, Harwell, Oxfordshire OX11 0RD, UK. g.gkoutos@har.mrc.ac.uk|Bioinformatics Group, MRC Mammalian Genetics Unit, Harwell, Oxfordshire OX11 0RD, UK. g.gkoutos@har.mrc.ac.uk|Bioinformatics Group, MRC Mammalian Genetics Unit, Harwell, Oxfordshire OX11 0RD, UK. g.gkoutos@har.mrc.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 8, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Phenotype|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti147', '15550481', 'A major challenge in modern biology is to link genome sequence information to organismal function. In many organisms this is being done by characterizing phenotypes resulting from mutations. Efficiently expressing phenotypic information requires combinatorial use of ontologies. However tools are not currently available to visualize combinations of ontologies. Here we describe CRAVE (Concept Relation Assay Value Explorer), a package allowing storage, active updating and visualization of multiple ontologies.'),
(71784, 2005, 'bio', 'Validation of alternative methods of data normalization in gene co-expression studies', 'Reverter, Antonio|Barris, Wes|McWilliam, Sean|Byrne, Keren A|Wang, Yong H|Tan, Siok H|Hudson, Nick|Dalrymple, Brian P', 'Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, St Lucia, QLD 4067, Australia. tony.reverter-gomez@csiro.au|Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, St Lucia, QLD 4067, Australia. tony.reverter-gomez@csiro.au|Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, St Lucia, QLD 4067, Australia. tony.reverter-gomez@csiro.au|Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, St Lucia, QLD 4067, Australia. tony.reverter-gomez@csiro.au|Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, St Lucia, QLD 4067, Australia. tony.reverter-gomez@csiro.au|Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, St Lucia, QLD 4067, Australia. tony.reverter-gomez@csiro.au|Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, St Lucia, QLD 4067, Australia. tony.reverter-gomez@csiro.au|Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, St Lucia, QLD 4067, Australia. tony.reverter-gomez@csiro.au', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Algorithms|Benchmarking|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Software', 'Comparative Study', '10.1093/bioinformatics/bti124', '15564293', 'Clusters of genes encoding proteins with related functions, or in the same regulatory network, often exhibit expression patterns that are correlated over a large number of conditions. Protein associations and gene regulatory networks can be modelled from expression data. We address the question of which of several normalization methods is optimal prior to computing the correlation of the expression profiles between every pair of genes.'),
(71785, 2005, 'bio', 'SpliceMachine: predicting splice sites from high-dimensional local context representations', 'Degroeve, Sven|Saeys, Yvan|De Baets, Bernard|Rouzé, Pierre|Van de Peer, Yves', 'Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, Gent 9052, Belgium. sven.degroeve@psb.ugent.be|Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, Gent 9052, Belgium. sven.degroeve@psb.ugent.be|Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, Gent 9052, Belgium. sven.degroeve@psb.ugent.be|Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, Gent 9052, Belgium. sven.degroeve@psb.ugent.be|Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, Gent 9052, Belgium. sven.degroeve@psb.ugent.be', 'Belgium|Belgium|Belgium|Belgium|Belgium', 76, 'Algorithms|Arabidopsis|Artificial Intelligence|Chromosome Mapping|Databases, Genetic|Genome, Human|Humans|Models, Genetic|Models, Statistical|RNA Splice Sites|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bti166', '15564294', 'In this age of complete genome sequencing, finding the location and structure of genes is crucial for further molecular research. The accurate prediction of intron boundaries largely facilitates the correct prediction of gene structure in nuclear genomes. Many tools for localizing these boundaries on DNA sequences have been developed and are available to researchers through the internet. Nevertheless, these tools still make many false positive predictions.'),
(71786, 2005, 'bio', 'Wnt pathway curation using automated natural language processing: combining statistical methods with partial and full parse for knowledge extraction', 'Santos, Carlos|Eggle, Daniela|States, David J', 'Bioinformatics Program, The University of Michigan, Ann Arbor, MI 48109, USA.|Bioinformatics Program, The University of Michigan, Ann Arbor, MI 48109, USA.|Bioinformatics Program, The University of Michigan, Ann Arbor, MI 48109, USA.', 'United States|United States|United States', 23, 'Animals|Artificial Intelligence|Database Management Systems|Documentation|Humans|Information Storage and Retrieval|Intercellular Signaling Peptides and Proteins|MEDLINE|Models, Biological|Models, Statistical|Natural Language Processing|Periodicals as Topic|Signal Transduction|Wnt Proteins', 'Journal Article', '10.1093/bioinformatics/bti165', '15564295', 'Wnt signaling is a very active area of research with highly relevant publications appearing at a rate of more than one per day. Building and maintaining databases describing signal transduction networks is a time-consuming and demanding task that requires careful literature analysis and extensive domain-specific knowledge. For instance, more than 50 factors involved in Wnt signal transduction have been identified as of late 2003. In this work we describe a natural language processing (NLP) system that is able to identify references to biological interaction networks in free text and automatically assembles a protein association and interaction map.'),
(71787, 2005, 'bio', 'A nearest-neighboring-end algorithm for genetic mapping', 'Crane, Charles F|Crane, Yan M', 'USDA-ARS and Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907, USA. ccrane@purdue.edu|USDA-ARS and Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907, USA. ccrane@purdue.edu', 'United States|United States', 0, 'Algorithms|Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Gene Deletion|Genetic Linkage|Genetic Markers|Genetics, Population|Humans|Models, Genetic|Models, Statistical|Software', 'Comparative Study', '10.1093/bioinformatics/bti164', '15564296', 'High-throughput methods are beginning to make possible the genotyping of thousands of loci in thousands of individuals, which could be useful for tightly associating phenotypes to candidate loci. Current mapping algorithms cannot handle so many data without building hierarchies of framework maps.'),
(71788, 2005, 'bio', 'DSEARCH: sensitive database searching using distributed computing', 'Keane, T M|Naughton, T J', 'Department of Computer Science, National University of Ireland, Maynooth, Ireland.|Department of Computer Science, National University of Ireland, Maynooth, Ireland.', 'Ireland|Ireland', 5, 'Algorithms|Computer Communication Networks|Computing Methodologies|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Software', 'Comparative Study', '10.1093/bioinformatics/bti163', '15564297', 'We present a distributed and fully cross-platform database search program that allows the user to utilize the idle clock cycles of machines to perform large searches using the most sensitive algorithms. For those in an academic or corporate environment with hundreds of idle desktop machines, DSEARCH can deliver a free database search supercomputer.'),
(71789, 2005, 'bio', 'Sample size for gene expression microarray experiments', 'Tsai, Chen-An|Wang, Sue-Jane|Chen, Dung-Tsa|Chen, James J', 'Division of Biometry and Risk Assessment, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR 72079, USA.|Division of Biometry and Risk Assessment, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR 72079, USA.|Division of Biometry and Risk Assessment, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR 72079, USA.|Division of Biometry and Risk Assessment, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR 72079, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|DNA|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sample Size|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bti162', '15564298', 'Microarray experiments often involve hundreds or thousands of genes. In a typical experiment, only a fraction of genes are expected to be differentially expressed, in addition, the measured intensities among different genes may be correlated. Depending on the experimental objectives, sample size calculations can be based on one of the three specified measures: sensitivity, true discovery and accuracy rates. The sample size problem is formulated as: the number of arrays needed in order to achieve the desired fraction of the specified measure at the desired family-wise power at the given type I error and (standardized) effect size.'),
(71790, 2005, 'bio', 'Procom: a web-based tool to compare multiple eukaryotic proteomes', 'Li, Jin Billy|Zhang, Miao|Dutcher, Susan K|Stormo, Gary D', 'Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA. billy@ural.wustl.edu|Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA. billy@ural.wustl.edu|Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA. billy@ural.wustl.edu|Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA. billy@ural.wustl.edu', 'United States|United States|United States|United States', 0, 'Animals|Chromosome Mapping|Eukaryotic Cells|Gene Expression Profiling|Humans|Internet|Linkage Disequilibrium|Proteome|Software|Species Specificity', 'Journal Article', '10.1093/bioinformatics/bti161', '15564299', 'Each organism has traits that are shared with some, but not all, organisms. Identification of genes needed for a particular trait can be accomplished by a comparative genomics approach using three or more organisms. Genes that occur in organisms without the trait are removed from the set of genes in common among organisms with the trait. To facilitate these comparisons, a web-based server, Procom, was developed to identify the subset of genes that may be needed for a trait.'),
(71791, 2005, 'bio', 'Evaluation of iterative alignment algorithms for multiple alignment', 'Wallace, Iain M|OSullivan, Orla|Higgins, Desmond G', 'The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Ireland. iain.wallace@ucd.ie|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Ireland. iain.wallace@ucd.ie|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Ireland. iain.wallace@ucd.ie', 'Ireland|Ireland|Ireland', 0, 'Algorithms|Feedback|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis|Software|Software Validation', 'Comparative Study', '10.1093/bioinformatics/bti159', '15564300', 'Iteration has been used a number of times as an optimization method to produce multiple alignments, either alone or in combination with other methods. Iteration has a great advantage in that it is often very simple both in terms of coding the algorithms and the complexity of the time and memory requirements. In this paper, we systematically test several different iteration strategies by comparing the results on sets of alignment test cases.'),
(71792, 2005, 'bio', 'Constructing ontology-driven protein family databases', 'Wolstencroft, K|McEntire, R|Stevens, R|Tabernero, L|Brass, A', 'School of Biological Sciences, Michael Smith Building, University of Manchester, Oxford Road, Manchester, M13 9PT, UK. kwolstencroft@cs.man.ac.uk|School of Biological Sciences, Michael Smith Building, University of Manchester, Oxford Road, Manchester, M13 9PT, UK. kwolstencroft@cs.man.ac.uk|School of Biological Sciences, Michael Smith Building, University of Manchester, Oxford Road, Manchester, M13 9PT, UK. kwolstencroft@cs.man.ac.uk|School of Biological Sciences, Michael Smith Building, University of Manchester, Oxford Road, Manchester, M13 9PT, UK. kwolstencroft@cs.man.ac.uk|School of Biological Sciences, Michael Smith Building, University of Manchester, Oxford Road, Manchester, M13 9PT, UK. kwolstencroft@cs.man.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'ATP-Binding Cassette Transporters|Computer Graphics|Database Management Systems|Databases, Protein|Documentation|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Phosphoric Monoester Hydrolases|Phylogeny|Proteins|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti158', '15564301', 'Protein family databases provide a central focus for scientific communities as well as providing useful resources to aide research. However, such resources require constant curation and often become outdated and discontinued. We have developed an ontology-driven system for capturing and managing protein family data that addresses the problems of maintenance and sustainability.'),
(71793, 2005, 'bio', 'The ArrayExpress gene expression database: a software engineering and implementation perspective', 'Sarkans, Ugis|Parkinson, Helen|Lara, Gonzalo Garcia|Oezcimen, Ahmet|Sharma, Anjan|Abeygunawardena, Niran|Contrino, Sergio|Holloway, Ele|Rocca-Serra, Philippe|Mukherjee, Gaurab|Shojatalab, Mohammadreza|Kapushesky, Misha|Sansone, Susanna-Assunta|Farne, Anna|Rayner, Tim|Brazma, Alvis', 'EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk|EMBL Outstation-Hinxton, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. ugis@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 28, 'Algorithms|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Dissemination|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bti157', '15564302', 'The lack of microarray data management systems and databases is still one of the major problems faced by many life sciences laboratories. While developing the public repository for microarray data ArrayExpress we had to find novel solutions to many non-trivial software engineering problems. Our experience will be both relevant and useful for most bioinformaticians involved in developing information systems for a wide range of high-throughput technologies.'),
(71794, 2005, 'bio', 'A fuzzy guided genetic algorithm for operon prediction', 'Jacob, E|Sasikumar, R|Nair, K N R', 'Department of Computational Modeling and Simulation, Regional Research Laboratory (CSIR), Trivandrum 695019, India.|Department of Computational Modeling and Simulation, Regional Research Laboratory (CSIR), Trivandrum 695019, India.|Department of Computational Modeling and Simulation, Regional Research Laboratory (CSIR), Trivandrum 695019, India.', 'India|India|India', 0, 'Algorithms|Bacillus subtilis|Bacterial Proteins|Chromosome Mapping|Escherichia coli|Fuzzy Logic|Gene Expression Regulation, Bacterial|Models, Genetic|Models, Statistical|Operon|Sequence Alignment|Sequence Analysis, DNA|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/bti156', '15564303', 'The operon structure of the prokaryotic genome is a critical input for the reconstruction of regulatory networks at the whole genome level. As experimental methods for the detection of operons are difficult and time-consuming, efforts are being put into developing computational methods that can use available biological information to predict operons.'),
(71795, 2005, 'bio', 'Accelerated off-target search algorithm for siRNA', 'Yamada, Tomoyuki|Morishita, Shinichi', 'Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, Japan. yamada@cb.k.u-tokyo.ac.jp|Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, Japan. yamada@cb.k.u-tokyo.ac.jp', 'Japan|Japan', 0, 'Algorithms|Base Pair Mismatch|Chromosome Mapping|Gene Targeting|Pattern Recognition, Automated|RNA Interference|RNA, Small Interfering|Sequence Alignment|Sequence Analysis, RNA', 'Comparative Study', '10.1093/bioinformatics/bti155', '15564304', 'Designing highly effective short interfering RNA (siRNA) sequences with maximum target-specificity for mammalian RNA interference (RNAi) is one of the hottest topics in molecular biology. The relationship between siRNA sequences and RNAi activity has been studied extensively to establish rules for selecting highly effective sequences. However, there is a pressing need to compute siRNA sequences that minimize off-target silencing effects efficiently and to match any non-targeted sequences with mismatches.'),
(71796, 2005, 'bio', 'Serial SimCoal: a population genetics model for data from multiple populations and points in time', 'Anderson, Christian N K|Ramakrishnan, Uma|Chan, Yvonne L|Hadly, Elizabeth A', 'Department of Biological Sciences, Stanford University, Stanford, CA 94305, USA.|Department of Biological Sciences, Stanford University, Stanford, CA 94305, USA.|Department of Biological Sciences, Stanford University, Stanford, CA 94305, USA.|Department of Biological Sciences, Stanford University, Stanford, CA 94305, USA.', 'United States|United States|United States|United States', 173, 'Biological Evolution|Chromosome Mapping|Computer Graphics|Computer Simulation|DNA Mutational Analysis|Genetic Variation|Genetics, Population|Models, Genetic|Models, Statistical|Sample Size|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti154', '15564305', 'We present Serial SimCoal, a program that models population genetic data from multiple time points, as with ancient DNA data. An extension of SIMCOAL, it also allows simultaneous modeling of complex demographic histories, and migration between multiple populations. Further, we incorporate a statistical package to calculate relevant summary statistics, which, for the first time allows users to investigate the statistical power provided by, conduct hypothesis-testing with, and explore sample size limitations of ancient DNA data.'),
(71797, 2005, 'bio', 'VitaPad: visualization tools for the analysis of pathway data', 'Holford, Matthew|Li, Naixin|Nadkarni, Prakash|Zhao, Hongyu', 'Center for Statistical Genomics and Proteomics, Yale University, New Haven, CT 06520, USA. matthew.holford@yale.edu|Center for Statistical Genomics and Proteomics, Yale University, New Haven, CT 06520, USA. matthew.holford@yale.edu|Center for Statistical Genomics and Proteomics, Yale University, New Haven, CT 06520, USA. matthew.holford@yale.edu|Center for Statistical Genomics and Proteomics, Yale University, New Haven, CT 06520, USA. matthew.holford@yale.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Cell Physiological Phenomena|Computer Graphics|Computer Simulation|Database Management Systems|Databases, Factual|Documentation|Gene Expression Regulation|Information Storage and Retrieval|Models, Biological|Signal Transduction|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti153', '15564306', 'Packages that support the creation of pathway diagrams are limited by their inability to be readily extended to new classes of pathway-related data.'),
(71798, 2005, 'bio', 'The carbohydrate sequence markup language (CabosML): an XML description of carbohydrate structures', 'Kikuchi, Norihiro|Kameyama, Akihiko|Nakaya, Shuuichi|Ito, Hiromi|Sato, Takashi|Shikanai, Toshihide|Takahashi, Yoriko|Narimatsu, Hisashi', 'Mitsui Knowledge Industry Co., Ltd., Nakano-ku, Tokyo, Japan. kikuchi@hydra.mki.co.jp|Mitsui Knowledge Industry Co., Ltd., Nakano-ku, Tokyo, Japan. kikuchi@hydra.mki.co.jp|Mitsui Knowledge Industry Co., Ltd., Nakano-ku, Tokyo, Japan. kikuchi@hydra.mki.co.jp|Mitsui Knowledge Industry Co., Ltd., Nakano-ku, Tokyo, Japan. kikuchi@hydra.mki.co.jp|Mitsui Knowledge Industry Co., Ltd., Nakano-ku, Tokyo, Japan. kikuchi@hydra.mki.co.jp|Mitsui Knowledge Industry Co., Ltd., Nakano-ku, Tokyo, Japan. kikuchi@hydra.mki.co.jp|Mitsui Knowledge Industry Co., Ltd., Nakano-ku, Tokyo, Japan. kikuchi@hydra.mki.co.jp|Mitsui Knowledge Industry Co., Ltd., Nakano-ku, Tokyo, Japan. kikuchi@hydra.mki.co.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Carbohydrate Sequence|Carbohydrates|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Molecular Sequence Data|Programming Languages', 'Journal Article', '10.1093/bioinformatics/bti152', '15564307', 'Bioinformatics resources for glycomics are very poor as compared with those for genomics and proteomics. The complexity of carbohydrate sequences makes it difficult to define a common language to represent them, and the development of bioinformatics tools for glycomics has not progressed. In this study, we developed a carbohydrate sequence markup language (CabosML), an XML description of carbohydrate structures.'),
(71799, 2005, 'bio', 'A graph based algorithm for generating EST consensus sequences', 'Malde, Ketil|Coward, Eivind|Jonassen, Inge', 'Department of Informatics, University of Bergen, Norway. ketil@ii.uib.no|Department of Informatics, University of Bergen, Norway. ketil@ii.uib.no|Department of Informatics, University of Bergen, Norway. ketil@ii.uib.no', 'Norway|Norway|Norway', 15, 'Algorithms|Computer Graphics|Consensus Sequence|Conserved Sequence|Contig Mapping|Expressed Sequence Tags|Numerical Analysis, Computer-Assisted|Sequence Alignment|Sequence Analysis, DNA|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bti184', '15572463', 'EST sequences constitute an abundant, yet error prone resource for computational biology. Expressed sequences are important in gene discovery and identification, and they are also crucial for the discovery and classification of alternative splicing. An important challenge when processing EST sequences is the reconstruction of mRNA by assembling EST clusters into consensus sequences.'),
(71800, 2005, 'bio', 'MACAT--microarray chromosome analysis tool', 'Toedling, Joern|Schmeier, Sebastian|Heinig, Matthias|Georgi, Benjamin|Roepcke, Stefan', 'Freie Universitaet Berlin, Bioinformatics programme and Max Planck Institute for Molecular Genetics, Germany.|Freie Universitaet Berlin, Bioinformatics programme and Max Planck Institute for Molecular Genetics, Germany.|Freie Universitaet Berlin, Bioinformatics programme and Max Planck Institute for Molecular Genetics, Germany.|Freie Universitaet Berlin, Bioinformatics programme and Max Planck Institute for Molecular Genetics, Germany.|Freie Universitaet Berlin, Bioinformatics programme and Max Planck Institute for Molecular Genetics, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Chromosome Mapping|Computer Simulation|Gene Expression Profiling|Gene Frequency|Linkage Disequilibrium|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti183', '15572464', 'By linking differential gene expression to the chromosomal localization of genes, one can investigate microarray data for characteristic patterns of expression phenomena involving sizeable parts of specific chromosomes. We have implemented a statistical approach for identifying significantly differentially expressed chromosome regions. We demonstrate the applicability of the approach on a publicly available data set on acute lymphocytic leukemia.'),
(71801, 2005, 'bio', 'YODA: selecting signature oligonucleotides', 'Nordberg, Eric K', 'Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA. enordber@vbi.vt.edu', 'United States', 67, 'Algorithms|Base Sequence|Chromosome Mapping|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti182', '15572465', 'Selecting oligonucleotide probes for use in microarray design, and other applications requiring signature sequences, involves identifying sequences which will bind strongly to their intended target, while binding only weakly (or preferably, not at all) to non-target sequences which may be present in the hybridization reaction. While many tools to assist in selection of such sequences exist, all the ones we examined lack important oligo design and software features.'),
(71802, 2005, 'bio', 'SYMMETREE: whole-tree analysis of differential diversification rates', 'Chan, Kai M A|Moore, Brian R', 'Department of Biological Sciences, Stanford University, Stanford, CA 94305-5020, USA.|Department of Biological Sciences, Stanford University, Stanford, CA 94305-5020, USA.', 'United States|United States', 0, 'Algorithms|Animals|Biological Evolution|Computer Simulation|Genetic Variation|Humans|Kinetics|Models, Genetic|Models, Statistical|Phylogeny|Software|Species Specificity', 'Journal Article', '10.1093/bioinformatics/bti175', '15572466', 'SymmeTREE implements several tests of differential diversification rates that exploit information on the topological distribution of species diversity throughout entire trees to address two general questions: (1) Has a given tree experienced significant variation in diversification rates among its branches? and (2) If so, along which branches have significant shifts in diversification rate occurred? These explicitly model-based methods are robust to uncertainty in estimates of branch length/duration and can accommodate incompletely resolved trees and other forms of phylogenetic uncertainty.'),
(71803, 2005, 'bio', 'Correlation of amino acid preference and mammalian viral genome type', 'Rose, John R|Turkett, William H|Oroian, Iulia C|Laegreid, William W|Keele, John', 'Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA. rose@cse.sc.edu|Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA. rose@cse.sc.edu|Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA. rose@cse.sc.edu|Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA. rose@cse.sc.edu|Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA. rose@cse.sc.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Animals|Base Sequence|Chromosome Mapping|DNA, Viral|Genome, Viral|Mammals|Models, Genetic|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Species Specificity|Statistics as Topic|Viral Proteins', 'Comparative Study', '10.1093/bioinformatics/bti174', '15572467', 'In the event of an outbreak of a disease caused by an initially unknown pathogen, the ability to characterize anonymous sequences prior to isolation and culturing of the pathogen will be helpful. We show that it is possible to classify viral sequences by genome type (dsDNA, ssDNA, ssRNA positive strand, ssRNA negative strand, retroid) using amino acid distribution.'),
(71804, 2005, 'bio', 'Drosophila DNase I footprint database: a systematic genome annotation of transcription factor binding sites in the fruitfly, Drosophila melanogaster', 'Bergman, Casey M|Carlson, Joseph W|Celniker, Susan E', 'Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK. cbergman@gen.cam.ac.uk|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK. cbergman@gen.cam.ac.uk|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK. cbergman@gen.cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 131, 'Binding Sites|Chromosome Mapping|DNA Footprinting|Databases, Genetic|Drosophila Proteins|Protein Binding|Protein Footprinting|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bti173', '15572468', 'Despite increasing numbers of computational tools developed to predict cis-regulatory sequences, the availability of high-quality datasets of transcription factor binding sites limits advances in the bioinformatics of gene regulation. Here we present such a dataset based on a systematic literature curation and genome annotation of DNase I footprints for the fruitfly, Drosophila melanogaster. Using the experimental results of 201 primary references, we annotated 1367 binding sites from 87 transcription factors and 101 target genes in the D.melanogaster genome sequence. These data will provide a rich resource for future bioinformatics analyses of transcriptional regulation in Drosophila such as constructing motif models, training cis-regulatory module detectors, benchmarking alignment tools and continued text mining of the extensive literature on transcriptional regulation in this important model organism.'),
(71805, 2005, 'bio', 'Synergy of human Pol II core promoter elements revealed by statistical sequence analysis', 'Gershenzon, Naum I|Ioshikhes, Ilya P', 'Department of Biomedical Informatics, The Ohio State University, 3184 Graves Hall, 333 W. 10th Avenue, Columbus, OH 43210, USA.|Department of Biomedical Informatics, The Ohio State University, 3184 Graves Hall, 333 W. 10th Avenue, Columbus, OH 43210, USA.', 'United States|United States', 0, 'DNA Polymerase II|Databases, Genetic|Humans|Models, Genetic|Models, Statistical|Promoter Regions, Genetic|Response Elements|Sequence Alignment|Sequence Analysis, DNA|Transcription Initiation Site|Transcriptional Activation', 'Evaluation Studies', '10.1093/bioinformatics/bti172', '15572469', 'The subject of our paper is bioinformatics analysis of the distinguishing features of human promoter DNA sequences, in particular of synergetic combinations of core promoter elements therein. We suppose that specific scenarios of transcription initiation are essentially related to various particular implementations of the interaction of basal transcription machinery with promoter DNA, depending on the presence and mutual positioning of core promoter elements.'),
(71806, 2005, 'bio', 'Optimal number of features as a function of sample size for various classification rules', 'Hua, Jianping|Xiong, Zixiang|Lowey, James|Suh, Edward|Dougherty, Edward R', 'Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Computer Simulation|DNA|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sample Size|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bti171', '15572470', 'Given the joint feature-label distribution, increasing the number of features always results in decreased classification error, however, this is not the case when a classifier is designed via a classification rule from sample data. Typically (but not always), for fixed sample size, the error of a designed classifier decreases and then increases as the number of features grows. The potential downside of using too many features is most critical for small samples, which are commonplace for gene-expression-based classifiers for phenotype discrimination. For fixed sample size and feature-label distribution, the issue is to find an optimal number of features.'),
(71807, 2005, 'bio', 'BIAS: Bioinformatics Integrated Application Software', 'Finak, G|Godin, N|Hallett, M|Pepin, F|Rajabi, Z|Srivastava, V|Tang, Z', 'McGill Centre for Bioinformatics, 3775 University Street, McGill University, Montreal, Canada H3A 2B4.|McGill Centre for Bioinformatics, 3775 University Street, McGill University, Montreal, Canada H3A 2B4.|McGill Centre for Bioinformatics, 3775 University Street, McGill University, Montreal, Canada H3A 2B4.|McGill Centre for Bioinformatics, 3775 University Street, McGill University, Montreal, Canada H3A 2B4.|McGill Centre for Bioinformatics, 3775 University Street, McGill University, Montreal, Canada H3A 2B4.|McGill Centre for Bioinformatics, 3775 University Street, McGill University, Montreal, Canada H3A 2B4.|McGill Centre for Bioinformatics, 3775 University Street, McGill University, Montreal, Canada H3A 2B4.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 8, 'Computational Biology|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Internet|Programming Languages|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti170', '15572471', 'We introduce a development platform especially tailored to Bioinformatics research and software development. BIAS (Bioinformatics Integrated Application Software) provides the tools necessary for carrying out integrative Bioinformatics research requiring multiple datasets and analysis tools. It follows an object-relational strategy for providing persistent objects, allows third-party tools to be easily incorporated within the system and supports standards and data-exchange protocols common to Bioinformatics.'),
(71808, 2005, 'bio', 'Generalized Venn diagrams: a new method of visualizing complex genetic set relations', 'Kestler, Hans A|Müller, André|Gress, Thomas M|Buchholz, Malte', 'Neuroinformatics, University of Ulm, 89069 Ulm, Germany. hans.kestler@medizin.uni-ulm.de|Neuroinformatics, University of Ulm, 89069 Ulm, Germany. hans.kestler@medizin.uni-ulm.de|Neuroinformatics, University of Ulm, 89069 Ulm, Germany. hans.kestler@medizin.uni-ulm.de|Neuroinformatics, University of Ulm, 89069 Ulm, Germany. hans.kestler@medizin.uni-ulm.de', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Computer Graphics|Evolution, Molecular|Gene Expression Profiling|Logistic Models|Models, Genetic|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti169', '15572472', 'Microarray experiments generate vast amounts of data. The unknown or only partially known functional context of differentially expressed genes may be assessed by querying the Gene Ontology database via GOMiner. Resulting tree representations are difficult to interpret and are not suited for visualization of this type of data. Methods are needed to effectively visualize these complex set relationships.'),
(71809, 2005, 'bio', 'Detecting interspecific recombination with a pruned probabilistic divergence measure', 'Husmeier, Dirk|Wright, Frank|Milne, Iain', 'Biomathematics and Statistics Scotland, JCMB The Kings Buildings, Edinburgh, UK. dirk@bioss.ac.uk|Biomathematics and Statistics Scotland, JCMB The Kings Buildings, Edinburgh, UK. dirk@bioss.ac.uk|Biomathematics and Statistics Scotland, JCMB The Kings Buildings, Edinburgh, UK. dirk@bioss.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 12, 'Algorithms|Cluster Analysis|DNA Mutational Analysis|Evolution, Molecular|Genetic Variation|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Phylogeny|Recombination, Genetic|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bti151', '15572473', 'A promising sliding-window method for the detection of interspecific recombination in DNA sequence alignments is based on the monitoring of changes in the posterior distribution of tree topologies with a probabilistic divergence measure. However, as the number of taxa in the alignment increases or the sliding-window size decreases, the posterior distribution becomes increasingly diffuse. This diffusion blurs the probabilistic divergence signal and adversely affects the detection accuracy. The present study investigates how this shortcoming can be redeemed with a pruning method based on post-processing clustering, using the Robinson-Foulds distance as a metric in tree topology space.');
