INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70489, 2003, 'bio', 'InterPreTS: protein interaction prediction through tertiary structure', 'Aloy, Patrick|Russell, Robert B', 'EMBL, Meyerhofstrasse, 1, D-69117, Heidelberg, Germany. aloy@embl.de|EMBL, Meyerhofstrasse, 1, D-69117, Heidelberg, Germany. aloy@embl.de', 'Germany|Germany', 178, 'Databases, Protein|Imaging, Three-Dimensional|Macromolecular Substances|Protein Binding|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Homology, Amino Acid|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.1.161', '12499311', 'InterPreTS (Interaction Prediction through Tertiary Structure) is a web-based version of our method for predicting protein-protein interactions (Aloy and Russell, 2002, PROC: Natl Acad. Sci. USA, 99, 5896-5901). Given a pair of query sequences, we first search for homologues in a database of interacting domains (DBID) of known three-dimensional complex structures. Pairs of sequences homologous to a known interacting pair are scored for how well they preserve the atomic contacts at the interaction interface. InterPreTS includes a useful interface for visualising molecular details of any predicted interaction.'),
(70490, 2003, 'bio', 'ConSurf: identification of functional regions in proteins by surface-mapping of phylogenetic information', 'Glaser, Fabian|Pupko, Tal|Paz, Inbal|Bell, Rachel E|Bechor-Shental, Dalit|Martz, Eric|Ben-Tal, Nir', 'The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel. fabian@ashtoret.tau.ac.il|The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel. fabian@ashtoret.tau.ac.il|The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel. fabian@ashtoret.tau.ac.il|The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel. fabian@ashtoret.tau.ac.il|The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel. fabian@ashtoret.tau.ac.il|The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel. fabian@ashtoret.tau.ac.il|The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel. fabian@ashtoret.tau.ac.il', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel', 805, 'Amino Acids|Conserved Sequence|Databases, Protein|Evolution, Molecular|Internet|Phylogeny|Protein Conformation|Proteins|Proto-Oncogene Proteins c-bcl-2|Sequence Alignment|Sequence Analysis, Protein|User-Computer Interface|bcl-X Protein', 'Journal Article', '10.1093/bioinformatics/19.1.163', '12499312', 'We recently developed algorithmic tools for the identification of functionally important regions in proteins of known three dimensional structure by estimating the degree of conservation of the amino-acid sites among their close sequence homologues. Projecting the conservation grades onto the molecular surface of these proteins reveals patches of highly conserved (or occasionally highly variable) residues that are often of important biological function. We present a new web server, ConSurf, which automates these algorithmic tools. ConSurf may be used for high-throughput characterization of functional regions in proteins.'),
(70491, 2003, 'bio', 'ModView, visualization of multiple protein sequences and structures', 'Ilyin, Valentin A|Pieper, Ursula|Stuart, Ashley C|Marti-Renom, Marc A|McMahan, Linda|Sali, Andrej', 'The Rockefeller University, 1230 York Avenue, New York, NY 10021, USA. ilyin@neu.edu|The Rockefeller University, 1230 York Avenue, New York, NY 10021, USA. ilyin@neu.edu|The Rockefeller University, 1230 York Avenue, New York, NY 10021, USA. ilyin@neu.edu|The Rockefeller University, 1230 York Avenue, New York, NY 10021, USA. ilyin@neu.edu|The Rockefeller University, 1230 York Avenue, New York, NY 10021, USA. ilyin@neu.edu|The Rockefeller University, 1230 York Avenue, New York, NY 10021, USA. ilyin@neu.edu', 'United States|United States|United States|United States|United States|United States', 10, 'Database Management Systems|Documentation|Imaging, Three-Dimensional|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.1.165', '12499313', 'We describe ModView, a web application for visualization of multiple protein sequences and structures. ModView integrates a multiple structure viewer, a multiple sequence alignment editor, and a database querying engine. It is possible to interactively manipulate hundreds of proteins, to visualize conservative and variable residues, active and binding sites, fragments, and domains in protein families, as well as to display large macromolecular complexes such as ribosomes or viruses. As a Netscape plug-in, ModView can be included in HTML pages along with text and figures, which makes it useful for teaching and presentations. ModView is also suitable as a graphical interface to various databases because it can be controlled through JavaScript commands and called from CGI scripts.'),
(70492, 2003, 'bio', 'Detection of hydrogen-bond signature patterns in protein families', 'Prasad, Tejasvini|Prathima, M N|Chandra, Nagasuma', 'Bioinformatics Centre, Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560012, India.|Bioinformatics Centre, Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560012, India.|Bioinformatics Centre, Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560012, India.', 'India|India|India', 8, 'Algorithms|Conserved Sequence|Garlic|Hydrogen Bonding|Internet|Plant Lectins|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.1.167', '12499314', 'We have developed a WWW server, HBPRINT, for the identification of hydrogen-bond signature patterns in protein families from their structures. The server calculates (a) common hydrogen bonds between two structures (b) a hydrogen-bond fingerprint in a set of structural neighbours and (c) details of conserved hydrogen bonds. The server also enables the visualization of the hydrogen bond network comprising the signature pattern.'),
(70493, 2003, 'bio', 'Computational and experimental analysis reveals a novel Src family kinase in the C elegans genome', 'Pandey, Akhilesh|Peri, Suraj|Thacker, Colin|Whipple, Chery A|Collins, John J|Mann, Matthias', 'Center for Experimental Bioinformatics, University of Southern Denmark, Odense M, DK-5230, Denmark. pandey@cebi.sdu.dk|Center for Experimental Bioinformatics, University of Southern Denmark, Odense M, DK-5230, Denmark. pandey@cebi.sdu.dk|Center for Experimental Bioinformatics, University of Southern Denmark, Odense M, DK-5230, Denmark. pandey@cebi.sdu.dk|Center for Experimental Bioinformatics, University of Southern Denmark, Odense M, DK-5230, Denmark. pandey@cebi.sdu.dk|Center for Experimental Bioinformatics, University of Southern Denmark, Odense M, DK-5230, Denmark. pandey@cebi.sdu.dk|Center for Experimental Bioinformatics, University of Southern Denmark, Odense M, DK-5230, Denmark. pandey@cebi.sdu.dk', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 1, 'Amino Acid Sequence|Animals|Caenorhabditis elegans|Cells, Cultured|Chickens|Cyprinodontiformes|Drosophila|Gene Expression Regulation|Genome|Mice|Molecular Sequence Data|Phylogeny|Protein Structure, Tertiary|Rats|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Species Specificity|Xenopus laevis|src Homology Domains|src-Family Kinases', 'Comparative Study', '10.1093/bioinformatics/19.2.169', '12538235', 'The complete genomes of a number of organisms have already been sequenced. However, the vast majority of annotated genes are derived by gene prediction methods. It is important to not only validate the predicted coding regions but also to identify genes that may have been missed by these programs.'),
(70494, 2003, 'bio', 'Chemometric modelling based on 2D-fluorescence spectra without a calibration measurement', 'Solle, D|Geissler, D|Stärk, E|Scheper, T|Hitzmann, B', 'Institut für Technische Chemie, University of Hannover, Callinstr. 3, 30559 Hannover, Germany.|Institut für Technische Chemie, University of Hannover, Callinstr. 3, 30559 Hannover, Germany.|Institut für Technische Chemie, University of Hannover, Callinstr. 3, 30559 Hannover, Germany.|Institut für Technische Chemie, University of Hannover, Callinstr. 3, 30559 Hannover, Germany.|Institut für Technische Chemie, University of Hannover, Callinstr. 3, 30559 Hannover, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Calibration|Computer Simulation|Ethanol|Glucose|Models, Biological|Models, Chemical|Quality Control|Reproducibility of Results|Saccharomyces cerevisiae|Sensitivity and Specificity|Spectrometry, Fluorescence', 'Comparative Study', '10.1093/bioinformatics/19.2.173', '12538236', '2D fluorescence spectra provide information from intracellular compounds. Fluorophores like trytophan, tyrosine and phenylalanin as well as NADH and flavins make the corresponding measurement systems very important for bioprocess supervision and control. The evaluation is usually based on chemometric modelling using for their calibration procedure off-line measurements of the desired process variables. Due to the data driven approach lots of off-line measurements are required. Here a methodology is presented, which enables to perform a calibration procedure of chemometric models without any further measurement.'),
(70495, 2003, 'bio', 'A study of accuracy and precision in oligonucleotide arrays: extracting more signal at large concentrations', 'Naef, Felix|Socci, Nicholas D|Magnasco, Marcelo', 'Center for Studies in Physics and Biology, Rockefeller University, 1230 York Avenue, NY 10021, USA. felix@funes.rockefeller.edu|Center for Studies in Physics and Biology, Rockefeller University, 1230 York Avenue, NY 10021, USA. felix@funes.rockefeller.edu|Center for Studies in Physics and Biology, Rockefeller University, 1230 York Avenue, NY 10021, USA. felix@funes.rockefeller.edu', 'United States|United States|United States', 37, 'Algorithms|Calibration|Equipment Failure Analysis|Molecular Probes|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Stochastic Processes|Yeasts', 'Comparative Study', '10.1093/bioinformatics/19.2.178', '12538237', 'Despite the success and popularity of oligonucleotide arrays as a high-throughput technique for measuring mRNA expression levels, quantitative calibration studies have until now been limited. The main reason is that suitable data was not available. However, calibration data recently produced by Affymetrix now permits detailed studies of the intensity dependent sensitivity. Given a certain transcript concentration, it is of particular interest to know whether current analysis methods are capable of detecting differential expression ratios of 2 or higher.'),
(70496, 2003, 'bio', 'A comparison of normalization methods for high density oligonucleotide array data based on variance and bias', 'Bolstad, B M|Irizarry, R A|Astrand, M|Speed, T P', 'Group in Biostatistics, University of California, Berkeley, CA 94720, USA. bolstad@stat.berkeley.edu|Group in Biostatistics, University of California, Berkeley, CA 94720, USA. bolstad@stat.berkeley.edu|Group in Biostatistics, University of California, Berkeley, CA 94720, USA. bolstad@stat.berkeley.edu|Group in Biostatistics, University of California, Berkeley, CA 94720, USA. bolstad@stat.berkeley.edu', 'United States|United States|United States|United States', 5830, 'Algorithms|Calibration|Models, Genetic|Molecular Probes|Nonlinear Dynamics|Oligonucleotide Array Sequence Analysis|Quality Control|Sequence Analysis, DNA|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/19.2.185', '12538238', 'When running experiments that involve multiple high density oligonucleotide arrays, it is important to remove sources of variation between arrays of non-biological origin. Normalization is a process for reducing this variation. It is common to see non-linear relations between arrays and the standard normalization provided by Affymetrix does not perform well in these situations.'),
(70497, 2003, 'bio', 'Combinatorial image analysis of DNA microarray features', 'Glasbey, C A|Ghazal, P', 'Biomathematics and Statistics Scotland, JCMB, Kings Buildings, Edinburgh EH9 3JZ, Scotland, UK. chris@bioss.ac.uk|Biomathematics and Statistics Scotland, JCMB, Kings Buildings, Edinburgh EH9 3JZ, Scotland, UK. chris@bioss.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Cluster Analysis|Cytomegalovirus|Fluorometry|Gene Expression Profiling|Humans|Image Enhancement|Models, Statistical|Oligonucleotide Array Sequence Analysis|Quality Control|Sequence Analysis, DNA|Signal Processing, Computer-Assisted', 'Comparative Study', '10.1093/bioinformatics/19.2.194', '12538239', 'DNA and protein microarrays have become an established leading-edge technology for large-scale analysis of gene and protein content and activity. Contact-printed microarrays has emerged as a relatively simple and cost effective method of choice but its reliability is especially susceptible to quality of pixel information obtained from digital scans of spotted features in the microarray image.'),
(70498, 2003, 'bio', 'An associative analysis of gene expression array data', 'Dozmorov, Igor|Centola, Michael', 'Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK 73105, USA. igor-dozmorov@omrf.ouhsc.edu|Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK 73105, USA. igor-dozmorov@omrf.ouhsc.edu', 'United States|United States', 97, 'Algorithms|Animals|Dwarfism|False Negative Reactions|False Positive Reactions|Gene Expression Profiling|Gene Expression Regulation|Liver|Male|Mice|Mice, Inbred C3H|Mice, Mutant Strains|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|RNA, Messenger|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/19.2.204', '12538240', 'We face the absence of optimized standards to guide normalization, comparative analysis, and interpretation of data sets. One aspect of this is that current methods of statistical analysis do not adequately utilize the information inherent in the large data sets generated in a microarray experiment and require a tradeoff between detection sensitivity and specificity.'),
(70499, 2003, 'bio', 'Rank order metrics for quantifying the association of sequence features with gene regulation', 'Clarke, Neil D|Granek, Joshua A', 'Department of Biophysics and Biophysical Chemistry, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA. nclarke@jhmi.edu|Department of Biophysics and Biophysical Chemistry, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA. nclarke@jhmi.edu', 'United States|United States', 0, 'Algorithms|Consensus Sequence|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|ROC Curve|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, DNA|Statistics as Topic|Transcription Factors|Transcription, Genetic', 'Comparative Study', '10.1093/bioinformatics/19.2.212', '12538241', 'Genome sequences and transcriptome analyses allow the correlation between gene regulation and DNA sequence features to be studied at the whole-genome level. To quantify these correlations, metrics are needed that can be applied to any sequence feature, regardless of its statistical distribution. It is also desirable for the metric values to be determined objectively, that is, without the use of subjective threshold values.'),
(70500, 2003, 'bio', 'Gene finding with a hidden Markov model of genome structure and evolution', 'Pedersen, Jakob Skou|Hein, Jotun', 'Bioinformatics Research Center, Department of Genetics and Ecology, The Institute of Biological Sciences, University of Aarhus, Building 550, Ny Munkegade, 8000 Aarhus C, Denmark. jsp@daimi.au.dk|Bioinformatics Research Center, Department of Genetics and Ecology, The Institute of Biological Sciences, University of Aarhus, Building 550, Ny Munkegade, 8000 Aarhus C, Denmark. jsp@daimi.au.dk', 'Denmark|Denmark', 71, 'Algorithms|Animals|Computer Simulation|Evolution, Molecular|Genome|Humans|Markov Chains|Mice|Models, Genetic|Models, Statistical|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology|Stochastic Processes', 'Evaluation Studies', '10.1093/bioinformatics/19.2.219', '12538242', 'A growing number of genomes are sequenced. The differences in evolutionary pattern between functional regions can thus be observed genome-wide in a whole set of organisms. The diverse evolutionary pattern of different functional regions can be exploited in the process of genomic annotation. The modelling of evolution by the existing comparative gene finders leaves room for improvement.'),
(70501, 2003, 'bio', 'A generalized global alignment algorithm', 'Huang, Xiaoqiu|Chao, Kun-Mao', 'Department of Computer Science, Iowa State University, 226 Atanasoff Hall, Ames, IA 50011-1040, USA. xqhuang@cs.iastate.edu|Department of Computer Science, Iowa State University, 226 Atanasoff Hall, Ames, IA 50011-1040, USA. xqhuang@cs.iastate.edu', 'United States|United States', 0, 'Algorithms|Animals|Base Sequence|DNA|Endopeptidases|Escherichia coli|Haemophilus influenzae|Humans|Mice|Molecular Sequence Data|Quality Control|Sequence Alignment', 'Evaluation Studies', '10.1093/bioinformatics/19.2.228', '12538243', 'Homologous sequences are sometimes similar over some regions but different over other regions. Homologous sequences have a much lower global similarity if the different regions are much longer than the similar regions.'),
(70502, 2003, 'bio', 'A naive Bayes model to predict coupling between seven transmembrane domain receptors and G-proteins', 'Cao, Jack|Panetta, Rosemarie|Yue, Shiyi|Steyaert, Alain|Young-Bellido, Michele|Ahmad, Sultan', 'Department of Molecular Sciences, AstraZeneca R&D Montreal, 7171 Frederick-Banting Street, St-Laurent, Quebec H4S 1Z9, Canada. jack.cao@astrazeneca.com|Department of Molecular Sciences, AstraZeneca R&D Montreal, 7171 Frederick-Banting Street, St-Laurent, Quebec H4S 1Z9, Canada. jack.cao@astrazeneca.com|Department of Molecular Sciences, AstraZeneca R&D Montreal, 7171 Frederick-Banting Street, St-Laurent, Quebec H4S 1Z9, Canada. jack.cao@astrazeneca.com|Department of Molecular Sciences, AstraZeneca R&D Montreal, 7171 Frederick-Banting Street, St-Laurent, Quebec H4S 1Z9, Canada. jack.cao@astrazeneca.com|Department of Molecular Sciences, AstraZeneca R&D Montreal, 7171 Frederick-Banting Street, St-Laurent, Quebec H4S 1Z9, Canada. jack.cao@astrazeneca.com|Department of Molecular Sciences, AstraZeneca R&D Montreal, 7171 Frederick-Banting Street, St-Laurent, Quebec H4S 1Z9, Canada. jack.cao@astrazeneca.com', 'Canada|Canada|Canada|Canada|Canada|Canada', 41, 'Algorithms|Amino Acid Sequence|Bayes Theorem|Binding Sites|Cluster Analysis|Databases, Protein|Feasibility Studies|GTP-Binding Proteins|Humans|Models, Chemical|Models, Genetic|Models, Statistical|Molecular Sequence Data|Neuropeptides|Pattern Recognition, Automated|Protein Binding|Protein Conformation|Protein Structure, Tertiary|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Evaluation Studies', '10.1093/bioinformatics/19.2.234', '12538244', 'An understanding of the coupling between a G-protein coupled receptor (GPCR) and a specific class of heterotrimeric GTP-binding proteins (G-proteins) is vital for further comprehending the function of the receptor within a cell. However, predicting G-protein coupling based on the amino acid sequence of a receptor has been a daunting task. While experimental data for G-protein coupling exist, published models that rely on sequence based prediction are few. In this study, we have developed a Naive Bayes model to successfully predict G-protein coupling specificity by training over 80 GPCRs with known coupling. Each intracellular domain of GPCRs was treated as a discrete random variable, conditionally independent of one another. In order to determine the conditional probability distributions of these variables, ClustalW-generated phylogenetic trees were used as an approximation for the clustering of the intracellular domain sequences. The sampling of an intracellular domain sequence was achieved by identifying the cluster containing the homologue with the highest sequence similarity.'),
(70503, 2003, 'bio', 'Knowledge acquisition, consistency checking and concurrency control for Gene Ontology (GO)', 'Yeh, Iwei|Karp, Peter D|Noy, Natalya F|Altman, Russ B', 'Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA.|Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA.|Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA.|Department of Genetics, Stanford University, Stanford, CA 94305-5120, USA.', 'United States|United States|United States|United States', 0, 'Artificial Intelligence|Database Management Systems|Databases, Factual|Databases, Genetic|Documentation|Hypermedia|Information Storage and Retrieval|Natural Language Processing|Programming Languages|Quality Control|Software|Terminology as Topic|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/19.2.241', '12538245', 'A critical element of the computational infrastructure required for functional genomics is a shared language for communicating biological data and knowledge. The Gene Ontology (GO, http://www.geneontology.org) provides a taxonomy of concepts and their attributes for annotating gene products. As GO increases in size, its ongoing construction and maintenance becomes more challenging. In this paper, we assess the applicability of a Knowledge Base Management System (KBMS), Protégé-2000, to the maintenance and development of GO.'),
(70504, 2003, 'bio', 'Positional candidate gene selection from livestock EST databases using Gene Ontology', 'Harhay, Gregory P|Keele, John W', 'US Department of Agriculture, ARS, Roman L. Hruska US Meat Animal Research Center, Production Systems, Clay Center, NE 68933, USA. harhay@email.marc.usda.gov|US Department of Agriculture, ARS, Roman L. Hruska US Meat Animal Research Center, Production Systems, Clay Center, NE 68933, USA. harhay@email.marc.usda.gov', 'United States|United States', 19, 'Animals|Animals, Domestic|Database Management Systems|Databases, Factual|Databases, Nucleic Acid|Expressed Sequence Tags|Gene Expression Profiling|Information Storage and Retrieval|Natural Language Processing|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Species Specificity|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/19.2.249', '12538246', 'The number of expressed sequence tags (ESTs) in GenBank has now surpassed 200,000 for cattle and 100,000 for swine. The Institute of Genome Research (TIGR) has organized these sequences into approximately 60,000 non-redundant consensus sequences (identified by TIGR Gene Indices) for cattle and 40,000 for swine. Anonymous ESTs are of limited value unless they are connected to function. Functional information is difficult to manage electronically because of heterogeneity of meaning and form among databases. The Gene Ontology (GO) Consortium has produced ontologies for gene function with consistent meaning and form across species. Linking livestock EST to gene function through similarity with sequences from other annotation-rich mammals could accelerate: (1) the discovery of positional candidate genes underlying a livestock quantitative trait locus (QTL) and (2) comparative mapping between livestock and other mammals (e.g. humans, mouse and rat). We initiated this investigation to determine if incorporation of the GO into the annotation process could accelerate livestock positional candidate gene discovery.'),
(70505, 2003, 'bio', 'Fractional populations in multiple gene inheritance', 'Chung, Myung-Hoon|Kim, Chul Koo|Nahm, Kyun', 'Department of Physics, Hong-Ik University, Chochiwon, Choongnam 339-800, Korea. mhchung@hongik.ac.kr|Department of Physics, Hong-Ik University, Chochiwon, Choongnam 339-800, Korea. mhchung@hongik.ac.kr|Department of Physics, Hong-Ik University, Chochiwon, Choongnam 339-800, Korea. mhchung@hongik.ac.kr', '-|-|-', 0, 'Alleles|Computer Simulation|Gene Frequency|Genetic Diseases, Inborn|Genetic Drift|Humans|Infant|Infant Mortality|Infant, Newborn|Models, Genetic|Models, Statistical|Multifactorial Inheritance|Mutation|Population Dynamics|Selection, Genetic', 'Comparative Study', '10.1093/bioinformatics/19.2.256', '12538247', 'With complete knowledge of the human genome sequence, one of the most interesting tasks remaining is to understand the functions of individual genes and how they communicate. Using the information about genes (locus, allele, mutation rate, fitness, etc.), we attempt to explain population demographic data. This population evolution study could complement and enhance biologists understanding about genes.'),
(70506, 2003, 'bio', 'FluxAnalyzer: exploring structure, pathways, and flux distributions in metabolic networks on interactive flux maps', 'Klamt, Steffen|Stelling, Jörg|Ginkel, Martin|Gilles, Ernst Dieter', 'Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, D-39106 Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de|Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, D-39106 Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de|Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, D-39106 Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de|Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, D-39106 Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de', 'Germany|Germany|Germany|Germany', 153, 'Combinatorial Chemistry Techniques|Computer Simulation|Energy Metabolism|Metabolism|Models, Biological|Models, Chemical|Signal Transduction|Software|Software Design|Systems Integration|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/19.2.261', '12538248', 'The analysis of structure, pathways and flux distributions in metabolic networks has become an important approach for understanding the functionality of metabolic systems. The need of a user-friendly platform for stoichiometric modeling of metabolic networks in silico is evident.'),
(70507, 2003, 'bio', 'Reconstruction of metabolic networks from genome data and analysis of their global structure for various organisms', 'Ma, Hongwu|Zeng, An-Ping', 'GBF-German Research Center for Biotechnology, Microbial Systems, Mascheroder Weg 1, 38124 Braunschweig, Germany.|GBF-German Research Center for Biotechnology, Microbial Systems, Mascheroder Weg 1, 38124 Braunschweig, Germany.', 'Germany|Germany', 0, 'Archaea|Bacteria|Computer Simulation|Databases, Factual|Databases, Nucleic Acid|Energy Metabolism|Glucose|Glycolysis|Humans|Metabolism|Models, Biological|Models, Chemical|Multienzyme Complexes|Signal Transduction|Software|Software Design|Species Specificity|Systems Integration|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/19.2.270', '12538249', 'Information from fully sequenced genomes makes it possible to reconstruct strain-specific global metabolic network for structural and functional studies. These networks are often very large and complex. To properly understand and analyze the global properties of metabolic networks, methods for rationally representing and quantitatively analyzing their structure are needed.'),
(70508, 2003, 'bio', 'A task framework for the web interface W2H', 'Ernst, Peter|Glatting, Karl-Heinz|Suhai, Sándor', 'DKFZ-German Cancer Research Center, Department of Molecular Biophysics, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. P.Ernst@dkfz.de|DKFZ-German Cancer Research Center, Department of Molecular Biophysics, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. P.Ernst@dkfz.de|DKFZ-German Cancer Research Center, Department of Molecular Biophysics, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. P.Ernst@dkfz.de', 'Germany|Germany|Germany', 18, 'Database Management Systems|Databases, Factual|Databases, Genetic|Hypermedia|Information Storage and Retrieval|Internet|Meta-Analysis as Topic|Programming Languages|Sequence Analysis|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.2.278', '12538250', 'The W3H task framework allows the execution of compound jobs utilizing the description of work and data flows in a heterogeneous bioinformatics environment using meta-data information. By means of these descriptions, the task system can schedule the necessary execution of applications available in the environment, depending on rules specified in the meta-data. By integrating this task framework into the publicly available web interface W2H, similarly based on meta-data, web access and data management are immediately available for each task description. Authors of task descriptions can base their work on the underlying classes and objects to be able to describe dependency rules between previously independent applications. The result of a compound task is given as XML data that is translated according to XSLT data into web pages or plain text to report the result of the task to the user.'),
(70509, 2003, 'bio', 'QuickLIMS: facilitating the data management for DNA-microarray fabrication', 'Kokocinski, Felix|Wrobel, Gunnar|Hahn, Meinhard|Lichter, Peter', 'Department of Molecular Genetics, Deutsches Krebsforschungszentrum INF 280, D-69120 Heidelberg, Germany. f.kokocinski@dkfz.de|Department of Molecular Genetics, Deutsches Krebsforschungszentrum INF 280, D-69120 Heidelberg, Germany. f.kokocinski@dkfz.de|Department of Molecular Genetics, Deutsches Krebsforschungszentrum INF 280, D-69120 Heidelberg, Germany. f.kokocinski@dkfz.de|Department of Molecular Genetics, Deutsches Krebsforschungszentrum INF 280, D-69120 Heidelberg, Germany. f.kokocinski@dkfz.de', 'Germany|Germany|Germany|Germany', 0, 'Computer Communication Networks|Computer-Aided Design|Database Management Systems|Databases, Factual|Databases, Genetic|Equipment Design|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Quality Control|Robotics|Software', 'Journal Article', '10.1093/bioinformatics/19.2.283', '12538251', 'QuickLIMS is a Microsoft Access-based laboratory information and management system, capable of processing all information for microarray production. The programs operational flow is protocol-based, dynamically adapting to changes of the process. It interacts with the laboratory robot and with other database systems over the network, and it represents a complete solution for the management of the entire manufacturing process.'),
(70510, 2003, 'bio', 'An efficient algorithm for minimal primer set selection', 'Hsieh, Ming-Hua|Hsu, Wei-Che|Chiu, Sung-Kay|Tzeng, Chi-Meng', 'Department of Research and Development, U-Vision Biotech Inc., 3F 132, Ln 235, Pao-Chiao Rd, Hsin-Tien City 231 Taipei, Taiwan.|Department of Research and Development, U-Vision Biotech Inc., 3F 132, Ln 235, Pao-Chiao Rd, Hsin-Tien City 231 Taipei, Taiwan.|Department of Research and Development, U-Vision Biotech Inc., 3F 132, Ln 235, Pao-Chiao Rd, Hsin-Tien City 231 Taipei, Taiwan.|Department of Research and Development, U-Vision Biotech Inc., 3F 132, Ln 235, Pao-Chiao Rd, Hsin-Tien City 231 Taipei, Taiwan.', '-|-|-|-', 12, 'Adipocytes|Algorithms|Cell Differentiation|DNA Primers|Mycobacterium tuberculosis|Oligonucleotide Array Sequence Analysis|Quality Control|Reverse Transcriptase Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/19.2.285', '12538252', 'We have developed U-PRIMER, a primer design program, to compute a minimal primer set (MPS) for any given set of DNA sequences. The U-PRIMER algorithm, which uses automatic variable fixing and automatic redundant constraint elimination to tackle the binary integer programming problem associated with the MPS selection problem. The program has been tested successfully with 32 adipocyte development-related genes and 9 TB-specific genes to obtain their respective MPSs.'),
(70511, 2003, 'bio', 'Efficient selective screening of haplotype tag SNPs', 'Ke, Xiayi|Cardon, Lon R', 'Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK. xiayi@well.ox.ac.uk|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK. xiayi@well.ox.ac.uk', 'United Kingdom|United Kingdom', 42, 'Algorithms|Base Sequence|Databases, Genetic|Gene Frequency|Genetic Markers|Haplotypes|Linkage Disequilibrium|Molecular Sequence Data|Polymorphism, Single Nucleotide|Quality Control|Sequence Homology, Nucleic Acid|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.2.287', '12538253', 'Haplotypes defined by common single nucleotide polymorphisms (SNPs) have important implications for mapping of disease genes and human traits. Often only a small subset of the SNPs is sufficient to capture the full haplotype information. Such subsets of markers are called haplotype tagging SNPs (htSNPs). Although htSNPs can be identified by eye, efficient computer algorithms and flexible interactive software tools are required for large datasets such as the human genome haplotype map. We describe a java-based program, SNPtagger, which screens for minimal sets of SNP markers to represent given haplotypes according to various user requirements. The program offers several options for inclusion/exclusion of specific markers and presents alternative panels for final selection.'),
(70512, 2003, 'bio', 'Simulating haplotype blocks in the human genome', 'Posada, David|Wiuf, Carsten', 'Variagenics Inc., 60 Hampshire St, Cambridge, MA 02139-1548, USA. dposada@evolgenics.com|Variagenics Inc., 60 Hampshire St, Cambridge, MA 02139-1548, USA. dposada@evolgenics.com', 'United States|United States', 19, 'Algorithms|Base Sequence|Computer Simulation|Databases, Genetic|Gene Frequency|Genome, Human|Haplotypes|Humans|Linkage Disequilibrium|Models, Genetic|Molecular Sequence Data|Polymorphism, Single Nucleotide|Quality Control|Recombination, Genetic|Sequence Homology, Nucleic Acid|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.2.289', '12538254', 'A bioinformatic tool was written to simulate haplotypes and SNPs under a modified coalescent with recombination. The most important feature of this program is that it allows for the specification of non-homogeneous recombination rates, which results in the formation of the so-called haplotype blocks of the human genome. The program also implements different mutation models and flexible demographic histories. The samples generated can be very useful to better understand the architecture of the human genome and to investigate its impact in association studies searching for disease genes.'),
(70513, 2003, 'bio', 'Pedstrip: extracting a maximal subset of available, unrelated individuals from a pedigree', 'Martin, Jeremy M R|Mackay, Lan J|Rawlings, Christopher J', 'Oxagen Ltd, 91 Milton Park, Abingdon, Oxon OX14 4RY, UK. SD@oxagen.co.uk|Oxagen Ltd, 91 Milton Park, Abingdon, Oxon OX14 4RY, UK. SD@oxagen.co.uk|Oxagen Ltd, 91 Milton Park, Abingdon, Oxon OX14 4RY, UK. SD@oxagen.co.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Humans|Hypermedia|Pedigree|Phylogeny|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.2.291', '12538255', 'Certain types of genetic analysis are simplified by assembling a collection of unrelated individuals, e.g. case-control experiments. If a family study is being performed then it will be necessary to extract subsets of unrelated, available individuals from pedigress. Our program provides an optimal method for performing this task.'),
(70514, 2003, 'bio', 'AVA: visual analysis of gene expression microarray data', 'Zhou, Yihua|Liu, Jingdong', 'Bioinformatics, Monsanto Company, 800 North Lindbergh Blvd, St. Louis, MO 63167, USA. yihua-zhou2@monsanto.com|Bioinformatics, Monsanto Company, 800 North Lindbergh Blvd, St. Louis, MO 63167, USA. yihua-zhou2@monsanto.com', 'United States|United States', 0, 'Algorithms|Database Management Systems|Gene Expression Profiling|Image Enhancement|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.2.293', '12538256', 'AVA (Array Visual Analyzer) is a Java program that provides a graphical environment for visualization and analysis of gene expression microarray data. Together with its interactive visualization tools and a variety of built-in data analysis and filtration methods, AVA effectively integrates microarray data normalization, quality assessment, and data mining into one application.'),
(70515, 2003, 'bio', 'Matrix2png: a utility for visualizing matrix data', 'Pavlidis, Paul|Noble, William Stafford', 'Columbia Genome Center, Columbia University, New York, USA. pp175@columbia.edu|Columbia Genome Center, Columbia University, New York, USA. pp175@columbia.edu', 'United States|United States', 0, 'Color|Computer Graphics|Databases, Factual|Databases, Genetic|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface|Word Processing', 'Journal Article', '10.1093/bioinformatics/19.2.295', '12538257', 'We describe a simple software tool, matrix2png, for creating color images of matrix data. Originally designed with the display of microarray data sets in mind, it is a general tool that can be used to make simple visualizations of matrices for use in figures, web pages, slide presentations and the like. It can also be used to generate images on the fly in web applications. Both continuous-valued and discrete-valued (categorical) data sets can be displayed. Many options are available to the user, including the colors used, the display of row and column labels, and scale bars. In this note we describe some of matrix2pngs features and describe some places it has been useful in the authors work.'),
(70516, 2003, 'bio', 'SEGID: identifying interesting segments in (multiple) sequence alignments', 'Wang, Lusheng|Xu, Ying', 'Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong. cswangl@cityu.edu.hk|Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong. cswangl@cityu.edu.hk', 'Hong Kong|Hong Kong', 0, 'Algorithms|Conserved Sequence|Hypermedia|Sequence Alignment|Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/19.2.297', '12538258', 'SEGID is a tool for finding conserved regions (regions of high scores) for a given (multiple) sequence alignment. It takes a (multiple) sequence alignment as its input and converts the alignment into a sequence of numbers, where each number is the alignment score of a column. Three algorithms are used to identify regions of high scores. A graphical interface is provided to present those identified regions.'),
(70517, 2003, 'bio', 'RnaViz 2: an improved representation of RNA secondary structure', 'De Rijk, Peter|Wuyts, Jan|De Wachter, Rupert', 'Departement Biomedische Wetenschappen, Universiteit Antwerpen (UIA), Universiteitsplein 1, B-2610 Antwerpen, Belgium. derijkp@uia.ua.ac.be|Departement Biomedische Wetenschappen, Universiteit Antwerpen (UIA), Universiteitsplein 1, B-2610 Antwerpen, Belgium. derijkp@uia.ua.ac.be|Departement Biomedische Wetenschappen, Universiteit Antwerpen (UIA), Universiteitsplein 1, B-2610 Antwerpen, Belgium. derijkp@uia.ua.ac.be', 'Belgium|Belgium|Belgium', 231, 'Base Sequence|Database Management Systems|Databases, Nucleic Acid|Documentation|Imaging, Three-Dimensional|Information Storage and Retrieval|Molecular Sequence Data|Nucleic Acid Conformation|RNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.2.299', '12538259', 'RnaViz has been developed to easily create nice, publication quality drawings of RNA secondary structure. RnaViz 2 supports CT, DCSE, and RNAML input formats and improves on many aspects of the first version, notably portability and structure annotation. RnaViz is written using a hybrid programming approach combining pieces written in C and in the scripting language Tcl/Tk, making the program very portable and extensible.'),
(70518, 2003, 'bio', 'r8s: inferring absolute rates of molecular evolution and divergence times in the absence of a molecular clock', 'Sanderson, Michael J', 'Section of Evolution and Ecology, One Shields Avenue, University of California, Davis, CA 95616, USA. mjsanderson@ucdavis.edu', 'United States', 346, 'Algorithms|Database Management Systems|Databases, Genetic|Evolution, Molecular|Genetic Drift|Genetic Variation|Phylogeny|Sequence Analysis, DNA|Software|Time Factors', 'Journal Article', '10.1093/bioinformatics/19.2.301', '12538260', 'Estimating divergence times and rates of substitution from sequence data is plagued by the problem of rate variation between lineages. R8s version 1.5 is a program which uses parametric, nonparametric and semiparametric methods to relax the assumption of constant rates of evolution to obtain better estimates of rates and times. Unlike most programs for rate inference or phylogenetics, r8s permits users to convert results to absolute rates and ages by constraining one or more node times to be fixed, minimum or maximum ages (using fossil or other evidence). Version 1.5 uses truncated Newton nonlinear optimization code with bound constraints, offering superior performance over previous versions.'),
(70519, 2003, 'bio', 'Chimera: construction of chimeric sequences for phylogenetic analysis', 'Leunissen, Jack A M', 'Dalicon BV, Toernooiveld 218, 6525 EC Nijmegen (NL). jackl@dalicon.com', '-', 0, 'Amino Acid Sequence|Base Sequence|Biological Evolution|Chimera|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Molecular Sequence Data|Phylogeny|Sequence Alignment|Sequence Analysis|Software|Species Specificity|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.2.303', '12538261', 'Chimera allows the construction of chimeric protein or nucleic acid sequence files by concatenating sequences from two or more sequence files in PHYLIP formats. It allows the user to interactively select genes and species from the input files. The concatenated result is stored to one single output file in PHYLIP or NEXUS formats.'),
(70520, 2003, 'bio', 'G-language Genome Analysis Environment: a workbench for nucleotide sequence data mining', 'Arakawa, K|Mori, K|Ikeda, K|Matsuzaki, T|Kobayashi, Y|Tomita, M', 'Institute for Advanced Biosciences, Keio University, Fujisawa, 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa, 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa, 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa, 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa, 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa, 252-8520, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 67, 'Database Management Systems|Databases, Nucleic Acid|Genome|Hypermedia|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.2.305', '12538262', 'G-language Genome Analysis Environment (G-language GAE) is an open source generic software package aimed for higher efficiency in bioinformatics analysis. G-language GAE has an interface as a set of Perl libraries for software development, and a graphical user interface for easy manipulation. Both Windows and Linux versions are available.'),
(70521, 2003, 'bio', 'A profile hidden Markov model for signal peptides generated by HMMER', 'Zhang, Zemin|Wood, William I', 'Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA. zemin@gene.com|Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA. zemin@gene.com', 'United States|United States', 0, 'Amino Acid Sequence|Animals|False Positive Reactions|Humans|Markov Chains|Mice|Models, Chemical|Models, Genetic|Models, Statistical|Molecular Sequence Data|Peptides|Protein Conformation|Protein Sorting Signals|Protein Structure, Tertiary|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/19.2.307', '12538263', 'Although the HMMER package is widely used to produce profile hidden Markov models (profile HMMs) for protein domains, it has been difficult to create a profile HMM for signal peptides. Here we describe an approach for building a complex model of eukaryotic signal peptides by the standard HMMER package. Signal peptide prediction with this model gives a 95.6% sensitivity and 95.7% specificity.'),
(70522, 2003, 'bio', 'MPID: MHC-Peptide Interaction Database for sequence-structure-function information on peptides binding to MHC molecules', 'Govindarajan, Kunde Ramamoorthy|Kangueane, Pandjassarame|Tan, Tin Wee|Ranganathan, Shoba', 'Department of Biochemistry, National University of Singapore, Singapore 119260.|Department of Biochemistry, National University of Singapore, Singapore 119260.|Department of Biochemistry, National University of Singapore, Singapore 119260.|Department of Biochemistry, National University of Singapore, Singapore 119260.', 'Singapore|Singapore|Singapore|Singapore', 0, 'Binding Sites|Database Management Systems|Databases, Protein|Histocompatibility Antigens|Information Storage and Retrieval|Macromolecular Substances|Major Histocompatibility Complex|Peptide Fragments|Peptides|Protein Binding|Protein Conformation|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.2.309', '12538264', 'Binding of short antigenic peptides to Major histocompatibility complex (MHC) proteins is the first step in T-cell mediated immune response. To understand the structural principles governing MHC-specific peptide recognition and binding, we have developed the MHC-Peptide Interaction Database (MPID), containing sequence-structure-function information. MPID (version 1.2) contains curated x-ray crystallographic data on 86 MHC peptide complexes, with precomputed interaction parameters (solvent accessibility, hydrogen bonds, gap volume and gap index). A user-friendly web interface and query tools will facilitate the development of predictive algorithms for MHC-peptide binding from a structural viewpoint.'),
(70523, 2003, 'bio', 'TopDraw: a sketchpad for protein structure topology cartoons', 'Bond, Charles S', 'Division of Biological Chemistry and Molecular Microbiology, School of Life Sciences, University of Dundee, Dundee, DD1 5EH, Scotland. C.S.Bond@dundee.ac.uk', '-', 0, 'Amino Acid Sequence|Cartoons as Topic|Computer Graphics|Imaging, Three-Dimensional|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/19.2.311', '12538265', 'Protein topology cartoons are a representation of structural data commonly used by structural biologists to illustrate the relationship between one-dimensional sequence and three-dimensional structural data in a convenient two-dimensional format. TopDraw is a simple, freely available TCL/Tk based drawing program designed specifically for the production of publication quality topology cartoons in a style commonly presented by structural biologists.'),
(70524, 2003, 'bio', 'DPX: for the analysis of the protein core', 'Pintar, Alessandro|Carugo, Oliviero|Pongor, Sándor', 'Protein Structure and Bioinformatics Group, International Center for Genetic Engineering and Biotechnology, AREA Science Park, Padriciano 99, 34012 Trieste, Italy. pintar@icgeb.org|Protein Structure and Bioinformatics Group, International Center for Genetic Engineering and Biotechnology, AREA Science Park, Padriciano 99, 34012 Trieste, Italy. pintar@icgeb.org|Protein Structure and Bioinformatics Group, International Center for Genetic Engineering and Biotechnology, AREA Science Park, Padriciano 99, 34012 Trieste, Italy. pintar@icgeb.org', 'Italy|Italy|Italy', 0, 'Algorithms|Crystallography|Databases, Protein|Humans|Information Storage and Retrieval|Interferon alpha-2|Interferon-alpha|Models, Molecular|Protein Conformation|Proteins|Recombinant Proteins|Software', 'Evaluation Studies', '10.1093/bioinformatics/19.2.313', '12538266', 'In order to obtain an accurate description of the protein interior, we describe a simple and fast algorithm that measures the depth of each atom in a protein (dpx), defined as its distance (A) from the closest solvent accessible atom. The program reads a PDB file containing the atomic solvent accessibility in the B-factor field, and writes a file in the same format, where the B-factor field now contains the dpx value. Output structure files can be thus directly displayed with molecular graphics programs like RASMOL, MOLMOL, Swiss-PDB View and colored according to dpx values.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70525, 2003, 'bio', 'ARIA: automated NOE assignment and NMR structure calculation', 'Linge, Jens P|Habeck, Michael|Rieping, Wolfgang|Nilges, Michael', 'Unité de Bio-Informatique Structurale, Institut Pasteur, 25-28 rue du docteur Roux, F-75015 Paris, France. linge@pasteur.fr|Unité de Bio-Informatique Structurale, Institut Pasteur, 25-28 rue du docteur Roux, F-75015 Paris, France. linge@pasteur.fr|Unité de Bio-Informatique Structurale, Institut Pasteur, 25-28 rue du docteur Roux, F-75015 Paris, France. linge@pasteur.fr|Unité de Bio-Informatique Structurale, Institut Pasteur, 25-28 rue du docteur Roux, F-75015 Paris, France. linge@pasteur.fr', 'France|France|France|France', 0, 'Algorithms|Crystallography|Information Storage and Retrieval|Nuclear Magnetic Resonance, Biomolecular|Protein Conformation|Proteins|Quality Control|Solvents', 'Journal Article', '10.1093/bioinformatics/19.2.315', '12538267', 'In the light of several ongoing structural genomics projects, faster and more reliable methods for structure calculation from NMR data are in great demand. The major bottleneck in the determination of solution NMR structures is the assignment of NOE peaks (nuclear Overhauser effect). Due to the high complexity of the assignment problem, most NOEs cannot be directly converted into unambiguous inter-proton distance restraints.'),
(70526, 2003, 'bio', 'Visualization and analysis of protein interactions', 'Ju, Byong-Hyon|Park, Byungkyu|Park, Jong H|Han, Kyungsook', 'Department of Computer Science & Engineering, Inha University, Inchon, 402-751, South Korea.|Department of Computer Science & Engineering, Inha University, Inchon, 402-751, South Korea.|Department of Computer Science & Engineering, Inha University, Inchon, 402-751, South Korea.|Department of Computer Science & Engineering, Inha University, Inchon, 402-751, South Korea.', '-|-|-|-', 24, 'Algorithms|Amino Acid Sequence|Computer Graphics|Database Management Systems|Databases, Protein|Imaging, Three-Dimensional|Information Storage and Retrieval|Macromolecular Substances|Models, Molecular|Molecular Sequence Data|Protein Binding|Proteins|Sequence Analysis, Protein|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/19.2.317', '12538268', 'We have developed a new program called InterViewer for drawing large-scale protein interaction networks in three-dimensional space. Unique features of InterViewer include (1) it is much faster than other recent implementations of drawing algorithms, (2) it can be used not only for visualizing protein interactions but also for analyzing them interactively, and (3) it provides an integrated framework for querying protein interaction databases and directly visualizes the query results.'),
(70527, 2003, 'bio', 'FORRepeats: detects repeats on entire chromosomes and between genomes', 'Lefebvre, A|Lecroq, T|Dauchel, H|Alexandre, J', 'ABISS-Université de Rouen, 76821 Mont Saint-Aignan Cedex, France. arnaud.lefebvre@univ-rouen.fr|ABISS-Université de Rouen, 76821 Mont Saint-Aignan Cedex, France. arnaud.lefebvre@univ-rouen.fr|ABISS-Université de Rouen, 76821 Mont Saint-Aignan Cedex, France. arnaud.lefebvre@univ-rouen.fr|ABISS-Université de Rouen, 76821 Mont Saint-Aignan Cedex, France. arnaud.lefebvre@univ-rouen.fr', 'France|France|France|France', 0, 'Algorithms|Arabidopsis|Chromosomes|Chromosomes, Plant|Database Management Systems|Genome|Genome, Plant|Humans|Information Storage and Retrieval|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btf843', '12584116', 'As more and more whole genomes are available, there is a need for new methods to compare large sequences and transfer biological knowledge from annotated genomes to related new ones. BLAST is not suitable to compare multimegabase DNA sequences. MegaBLAST is designed to compare closely related large sequences. Some tools to detect repeats in large sequences have already been developed such as MUMmer or REPuter. They also have time or space restrictions. Moreover, in terms of applications, REPuter only computes repeats and MUMmer works better with related genomes.'),
(70528, 2003, 'bio', 'Towards a computational model for -1 eukaryotic frameshifting sites', 'Bekaert, Michaël|Bidou, Laure|Denise, Alain|Duchateau-Nguyen, Guillemette|Forest, Jean-Paul|Froidevaux, Christine|Hatin, Isabelle|Rousset, Jean-Pierre|Termier, Michel', 'Génétique Moléculaire de la Traduction, UMR CNRS 8623, Université Paris-Sud, 91405 Orsay Cedex, France. bekaert@igmors.u-psud.fr|Génétique Moléculaire de la Traduction, UMR CNRS 8623, Université Paris-Sud, 91405 Orsay Cedex, France. bekaert@igmors.u-psud.fr|Génétique Moléculaire de la Traduction, UMR CNRS 8623, Université Paris-Sud, 91405 Orsay Cedex, France. bekaert@igmors.u-psud.fr|Génétique Moléculaire de la Traduction, UMR CNRS 8623, Université Paris-Sud, 91405 Orsay Cedex, France. bekaert@igmors.u-psud.fr|Génétique Moléculaire de la Traduction, UMR CNRS 8623, Université Paris-Sud, 91405 Orsay Cedex, France. bekaert@igmors.u-psud.fr|Génétique Moléculaire de la Traduction, UMR CNRS 8623, Université Paris-Sud, 91405 Orsay Cedex, France. bekaert@igmors.u-psud.fr|Génétique Moléculaire de la Traduction, UMR CNRS 8623, Université Paris-Sud, 91405 Orsay Cedex, France. bekaert@igmors.u-psud.fr|Génétique Moléculaire de la Traduction, UMR CNRS 8623, Université Paris-Sud, 91405 Orsay Cedex, France. bekaert@igmors.u-psud.fr|Génétique Moléculaire de la Traduction, UMR CNRS 8623, Université Paris-Sud, 91405 Orsay Cedex, France. bekaert@igmors.u-psud.fr', 'France|France|France|France|France|France|France|France|France', 0, 'Algorithms|Animals|Artificial Intelligence|Base Sequence|Birds|Computer Simulation|DNA, Ribosomal Spacer|Eukaryotic Cells|Frameshifting, Ribosomal|Gene Expression Regulation|Gene Expression Regulation, Viral|Haplorhini|Humans|Models, Genetic|Molecular Sequence Data|Sequence Analysis, RNA|Viruses', 'Evaluation Studies', '10.1093/bioinformatics/btf868', '12584117', 'Unconventional decoding events are now well acknowledged, but not yet well formalized. In this study, we present a bioinformatics analysis of eukaryotic -1 frameshifting, in order to model this event.'),
(70529, 2003, 'bio', 'Genetic Network Analyzer: qualitative simulation of genetic regulatory networks', 'de Jong, Hidde|Geiselmann, Johannes|Hernandez, Céline|Page, Michel', 'INRIA Rhône-Alpes, 655 avenue de lEurope, Montbonnot, 38334 Saint Ismier CEDEX, France. Hidde.de-Jong@inrialpes.fr|INRIA Rhône-Alpes, 655 avenue de lEurope, Montbonnot, 38334 Saint Ismier CEDEX, France. Hidde.de-Jong@inrialpes.fr|INRIA Rhône-Alpes, 655 avenue de lEurope, Montbonnot, 38334 Saint Ismier CEDEX, France. Hidde.de-Jong@inrialpes.fr|INRIA Rhône-Alpes, 655 avenue de lEurope, Montbonnot, 38334 Saint Ismier CEDEX, France. Hidde.de-Jong@inrialpes.fr', 'France|France|France|France', 192, 'Bacillus subtilis|Bacterial Proteins|Computer Simulation|Gene Expression Regulation|Genes|Genomics|Models, Genetic|Software|Spores, Bacterial', 'Evaluation Studies', '10.1093/bioinformatics/btf851', '12584118', 'The study of genetic regulatory networks has received a major impetus from the recent development of experimental techniques allowing the measurement of patterns of gene expression in a massively parallel way. This experimental progress calls for the development of appropriate computer tools for the modeling and simulation of gene regulation processes.'),
(70530, 2003, 'bio', 'Hybrid protein model for optimally defining 3D protein structure fragments', 'de Brevern, A G|Hazout, S', 'Equipe de Bioinformatique Génomique et Moléculaire, INSERM U436, Université Paris 7, case 7113, 2, place Jussieu, 75251 Paris cedex 05, France. debrevern@urbb.jussieu.fr|Equipe de Bioinformatique Génomique et Moléculaire, INSERM U436, Université Paris 7, case 7113, 2, place Jussieu, 75251 Paris cedex 05, France. debrevern@urbb.jussieu.fr', 'France|France', 39, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Databases, Protein|Models, Molecular|Molecular Sequence Data|Peptide Fragments|Protein Conformation|Protein Folding|Proteins|Quality Control', 'Journal Article', '10.1093/bioinformatics/btf859', '12584119', 'Our aim is to develop a process that automatically defines a repertory of contiguous 3D protein structure fragments and can be used in homology modeling. We present here improvements to the method we introduced previously: the hybrid protein model (de Brevern and Hazout, THEOR: Chem. Acc., 106, 36-47, (2001)) The hybrid protein learns a non-redundant databank encoded in a structural alphabet composed of 16 Protein Blocks (PBs, de Brevern et al., Proteins, 41, 271-287, (2000)). Every local fold is learned by looking for the most similar pattern present in the hybrid protein and modifying it slightly. Finally each position corresponds to a cluster of similar 3D local folds.'),
(70531, 2003, 'bio', 'Discovering well-ordered folding patterns in nucleotide sequences', 'Le, Shu-Yun|Chen, Jih-H|Konings, Danielle|Maizel, Jacob V', 'Laboratory of Experimental and Computational Biology, NCI Center for Cancer Research, National Cancer Institute, NIH, Bldg 469, Room 151, Frederick, MD 21702, USA. shuyun@orleans.ncifcrf.gov|Laboratory of Experimental and Computational Biology, NCI Center for Cancer Research, National Cancer Institute, NIH, Bldg 469, Room 151, Frederick, MD 21702, USA. shuyun@orleans.ncifcrf.gov|Laboratory of Experimental and Computational Biology, NCI Center for Cancer Research, National Cancer Institute, NIH, Bldg 469, Room 151, Frederick, MD 21702, USA. shuyun@orleans.ncifcrf.gov|Laboratory of Experimental and Computational Biology, NCI Center for Cancer Research, National Cancer Institute, NIH, Bldg 469, Room 151, Frederick, MD 21702, USA. shuyun@orleans.ncifcrf.gov', 'United States|United States|United States|United States', 6, 'Algorithms|Base Sequence|Ferritins|Gene Expression Regulation|HIV-1|Humans|Molecular Sequence Data|Nucleic Acid Conformation|RNA, Messenger|Regulatory Sequences, Nucleic Acid|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btf826', '12584120', 'Growing evidence demonstrates that local well-ordered structures are closely correlated with cis-acting elements in the post-transcriptional regulation of gene expression. The prediction of a well-ordered folding sequence (WFS) in genomic sequences is very helpful in the determination of local RNA elements with structure-dependent functions in mRNAs.'),
(70532, 2003, 'bio', 'LTR_STRUC: a novel search and identification program for LTR retrotransposons', 'McCarthy, Eugene M|McDonald, John F', 'Department of Genetics, University of Georgia, Athens, GA 30602, USA. gm@uga.edu|Department of Genetics, University of Georgia, Athens, GA 30602, USA. gm@uga.edu', 'Georgia|Georgia', 230, 'Algorithms|Database Management Systems|Databases, Nucleic Acid|Information Storage and Retrieval|Retroelements|Sequence Alignment|Sequence Analysis, DNA|Software|Terminal Repeat Sequences', 'Journal Article', '10.1093/bioinformatics/btf878', '12584121', 'Long terminal repeat (LTR) retrotransposons constitute a substantial fraction of most eukaryotic genomes and are believed to have a significant impact on genome structure and function. Conventional methods used to search for LTR retrotransposons in genome databases are labor intensive. We present an efficient, reliable and automated method to identify and analyze members of this important class of transposable elements.'),
(70533, 2003, 'bio', 'Identifying differentially expressed genes using false discovery rate controlling procedures', 'Reiner, Anat|Yekutieli, Daniel|Benjamini, Yoav', 'Department of Statistics and Operations Research, The Sackler Faculty of Exact Sciences, Tel-Aviv University, Tel-Aviv 69978, Israel. anatr@post.tau.ac.il|Department of Statistics and Operations Research, The Sackler Faculty of Exact Sciences, Tel-Aviv University, Tel-Aviv 69978, Israel. anatr@post.tau.ac.il|Department of Statistics and Operations Research, The Sackler Faculty of Exact Sciences, Tel-Aviv University, Tel-Aviv 69978, Israel. anatr@post.tau.ac.il', 'Israel|Israel|Israel', 0, 'Algorithms|Animals|Cholesterol, HDL|Computer Simulation|DNA, Complementary|Gene Expression Profiling|Gene Expression Regulation|Liver|Mice|Mice, Inbred C57BL|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size', 'Comparative Study', '10.1093/bioinformatics/btf877', '12584122', 'DNA microarrays have recently been used for the purpose of monitoring expression levels of thousands of genes simultaneously and identifying those genes that are differentially expressed. The probability that a false identification (type I error) is committed can increase sharply when the number of tested genes gets large. Correlation between the test statistics attributed to gene co-regulation and dependency in the measurement errors of the gene expression levels further complicates the problem. In this paper we address this very large multiplicity problem by adopting the false discovery rate (FDR) controlling approach. In order to address the dependency problem, we present three resampling-based FDR controlling procedures, that account for the test statistics distribution, and compare their performance to that of the naïve application of the linear step-up procedure in Benjamini and Hochberg (1995). The procedures are studied using simulated microarray data, and their performance is examined relative to their ease of implementation.'),
(70534, 2003, 'bio', 'Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions', 'Hahn, Lance W|Ritchie, Marylyn D|Moore, Jason H', 'Program in Human Genetics and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN 37232-0700, USA.|Program in Human Genetics and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN 37232-0700, USA.|Program in Human Genetics and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN 37232-0700, USA.', 'United States|United States|United States', 917, 'Algorithms|DNA Mutational Analysis|Environment|Epistasis, Genetic|Genetic Linkage|Genetic Predisposition to Disease|Genetic Variation|Genetics, Population|Genotype|Humans|Multifactorial Inheritance|Polymorphism, Genetic|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btf869', '12584123', 'Polymorphisms in human genes are being described in remarkable numbers. Determining which polymorphisms and which environmental factors are associated with common, complex diseases has become a daunting task. This is partly because the effect of any single genetic variation will likely be dependent on other genetic variations (gene-gene interaction or epistasis) and environmental factors (gene-environment interaction). Detecting and characterizing interactions among multiple factors is both a statistical and a computational challenge. To address this problem, we have developed a multifactor dimensionality reduction (MDR) method for collapsing high-dimensional genetic data into a single dimension thus permitting interactions to be detected in relatively small sample sizes. In this paper, we describe the MDR approach and an MDR software package.'),
(70535, 2003, 'bio', 'GenePath: a system for automated construction of genetic networks from mutant data', 'Zupan, Blaz|Demsar, Janez|Bratko, Ivan|Juvan, Peter|Halter, John A|Kuspa, Adam|Shaulsky, Gad', 'University of Ljubljana, Faculty of Computer and Information Science Jozef Stefan Institute, Ljubljana, Slovenia.|University of Ljubljana, Faculty of Computer and Information Science Jozef Stefan Institute, Ljubljana, Slovenia.|University of Ljubljana, Faculty of Computer and Information Science Jozef Stefan Institute, Ljubljana, Slovenia.|University of Ljubljana, Faculty of Computer and Information Science Jozef Stefan Institute, Ljubljana, Slovenia.|University of Ljubljana, Faculty of Computer and Information Science Jozef Stefan Institute, Ljubljana, Slovenia.|University of Ljubljana, Faculty of Computer and Information Science Jozef Stefan Institute, Ljubljana, Slovenia.|University of Ljubljana, Faculty of Computer and Information Science Jozef Stefan Institute, Ljubljana, Slovenia.', 'Slovenia|Slovenia|Slovenia|Slovenia|Slovenia|Slovenia|Slovenia', 0, 'Animals|Caenorhabditis elegans|DNA Mutational Analysis|Dictyostelium|Expert Systems|Gene Expression Regulation|Larva|Models, Genetic|Sequence Analysis, DNA|Single-Blind Method|Software', 'Evaluation Studies', '10.1093/bioinformatics/btf871', '12584124', 'Genetic networks are often used in the analysis of biological phenomena. In classical genetics, they are constructed manually from experimental data on mutants. The field lacks formalism to guide such analysis, and accounting for all the data becomes complicated when large amounts of data are considered.'),
(70536, 2003, 'bio', 'SimiTri--visualizing similarity relationships for groups of sequences', 'Parkinson, John|Blaxter, Mark', 'Institute of Cell, Animal and Population Biology, University of Edinburgh, Edinburgh EH9 3JT, UK. john.parkinson@ed.ac.uk|Institute of Cell, Animal and Population Biology, University of Edinburgh, Edinburgh EH9 3JT, UK. john.parkinson@ed.ac.uk', 'United Kingdom|United Kingdom', 50, 'Animals|Caenorhabditis elegans|Caenorhabditis elegans Proteins|Database Management Systems|Databases, Protein|Drosophila|Drosophila Proteins|Gene Transfer, Horizontal|Humans|Phylogeny|Proteins|Saccharomyces cerevisiae|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Amino Acid|Species Specificity|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btf870', '12584125', 'Global sequence comparisons between large datasets, such as those arising from genome projects, can be problematic to display and analyze. We have developed SimiTri, a Java/Perl-based application, which allows simultaneous display and analysis of relative similarity relationships of the dataset of interest to three different databases. We illustrate its utility in identifying Caenorhabditis elegans genes that have distinct patterns of phylogenetic affinity suggestive of horizontal gene transfer. SimiTri is freely downloadable from http://www.nematodes.org/SimiTri/ and the source code is freely available from the authors.'),
(70537, 2003, 'bio', 'A literature-based method for assessing the functional coherence of a gene group', 'Raychaudhuri, Soumya|Altman, Russ B', 'Department of Genetics, Stanford Medical Informatics, 251 Campus Drive, MSOB X-215, Stanford University, Stanford, CA 94305-5479, USA.|Department of Genetics, Stanford Medical Informatics, 251 Campus Drive, MSOB X-215, Stanford University, Stanford, CA 94305-5479, USA.', 'United States|United States', 0, 'Abstracting and Indexing as Topic|Animals|Caenorhabditis elegans|Cluster Analysis|Databases, Genetic|Drosophila|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Mice|Natural Language Processing|PubMed|Saccharomyces cerevisiae|Sequence Alignment', 'Evaluation Studies', '10.1093/bioinformatics/btg002', '12584126', 'Many experimental and algorithmic approaches in biology generate groups of genes that need to be examined for related functional properties. For example, gene expression profiles are frequently organized into clusters of genes that may share functional properties. We evaluate a method, neighbor divergence per gene (NDPG), that uses scientific literature to assess whether a group of genes are functionally related. The method requires only a corpus of documents and an index connecting the documents to genes.'),
(70538, 2003, 'bio', 'Identification of key concepts in biomedical literature using a modified Markov heuristic', 'Majoros, W H|Subramanian, G M|Yandell, M D', 'The Institute for Genomic Research, Rockville, MD 20850, USA. bmajoros@tigr.org|The Institute for Genomic Research, Rockville, MD 20850, USA. bmajoros@tigr.org|The Institute for Genomic Research, Rockville, MD 20850, USA. bmajoros@tigr.org', 'United States|United States|United States', 14, 'Abstracting and Indexing as Topic|Algorithms|Database Management Systems|Information Storage and Retrieval|MEDLINE|Markov Chains|Models, Statistical|Natural Language Processing|Pattern Recognition, Automated|Unified Medical Language System', 'Evaluation Studies', '10.1093/bioinformatics/btg010', '12584127', 'The recent explosion of interest in mining the biomedical literature for associations between defined entities such as genes, diseases and drugs has made apparent the need for robust methods of identifying occurrences of these entities in biomedical text. Such concept-based indexing is strongly dependent on the availability of a comprehensive ontology or lexicon of biomedical terms. However, such ontologies are very difficult and expensive to construct, and often require extensive manual curation to render them suitable for use by automatic indexing programs. Furthermore, the use of statistically salient noun phrases as surrogates for curated terminology is not without difficulties, due to the lack of high-quality part-of-speech taggers specific to medical nomenclature.'),
(70539, 2003, 'bio', 'The Database of Quantitative Cellular Signaling: management and analysis of chemical kinetic models of signaling networks', 'Sivakumaran, Sudhir|Hariharaputran, Sridhar|Mishra, Jyoti|Bhalla, Upinder S', 'National Centre for Biological Sciences, GKVK Campus, Bangalore 560065, India.|National Centre for Biological Sciences, GKVK Campus, Bangalore 560065, India.|National Centre for Biological Sciences, GKVK Campus, Bangalore 560065, India.|National Centre for Biological Sciences, GKVK Campus, Bangalore 560065, India.', 'India|India|India|India', 92, 'Abstracting and Indexing as Topic|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Kinetics|Models, Biological|Models, Chemical|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btf860', '12584128', 'Analysis of cellular signaling interactions is expected to pose an enormous informatics challenge, perhaps even larger than analyzing the genome. The complex networks arising from signaling processes are traditionally represented as block diagrams. A key step in the evolution toward a more quantitative understanding of signaling is to explicitly specify the kinetics of all chemical reaction steps in a pathway. Technical advances in proteomics and high-throughput protein interaction assays promise a flood of such quantitative data. While annotations, molecular information and pathway connectivity have been compiled in several databases, and there are several proposals for general cell model description languages, there is currently little experience with databases of chemical kinetics and reaction level models of signaling networks.'),
(70540, 2003, 'bio', 'cMap: the comparative genetic map viewer', 'Fang, Z|Polacco, M|Chen, S|Schroeder, S|Hancock, D|Sanchez, H|Coe, E', 'Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Database Management Systems|Databases, Nucleic Acid|Genome, Plant|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg012', '12584129', 'cMap, a www comparative genetic map graphical utility, has a search capability and provides comparison of two genetic maps within or between species with dynamic links to data resources and text lists of the shared loci, running in a relational database environment. Currently, maps from three species (maize Zea mays L., rice Oryza sativa L., and sorghum Sorghum bicolor L.), representing over 13,800 distinct loci, are available for comparison at http://www.agron.missouri.edu/cMapDB/cMap.html.'),
(70541, 2003, 'bio', 'IslandPath: aiding detection of genomic islands in prokaryotes', 'Hsiao, William|Wan, Ivan|Jones, Steven J|Brinkman, Fiona 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.', 'Canada|Canada|Canada|Canada', 212, 'Archaea|Bacteria|CpG Islands|Database Management Systems|Gene Transfer, Horizontal|Genome, Archaeal|Genome, Bacterial|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btg004', '12584130', 'Genomic islands (clusters of genes of potential horizontal origin in a prokaryotic genome) are frequently associated with a particular adaptation of a microbe that is of medical, agricultural or environmental importance, such as antibiotic resistance, pathogen virulence, or metal resistance. While many sequence features associated with such islands have been adopted separately in applications for analysis of genomic islands, including pathogenicity islands, there is no single application that integrates multiple features for island detection. IslandPath is a network service which incorporates multiple DNA signals and genome annotation features into a graphical display of a bacterial or archaeal genome, to aid the detection of genomic islands.'),
(70542, 2003, 'bio', 'Redundancy based detection of sequence polymorphisms in expressed sequence tag data using autoSNP', 'Barker, Gary|Batley, Jacqueline|O Sullivan, Helen|Edwards, Keith J|Edwards, David', 'Institute of Arable Crop Research, Long Ashton, Bristol, BS41 9AF, UK.|Institute of Arable Crop Research, Long Ashton, Bristol, BS41 9AF, UK.|Institute of Arable Crop Research, Long Ashton, Bristol, BS41 9AF, UK.|Institute of Arable Crop Research, Long Ashton, Bristol, BS41 9AF, UK.|Institute of Arable Crop Research, Long Ashton, Bristol, BS41 9AF, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 130, 'Cluster Analysis|Expressed Sequence Tags|Genetic Markers|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software|Zea mays', 'Evaluation Studies', '10.1093/bioinformatics/btf881', '12584131', 'AutoSNP is a program to detect single nucleotide polymorphisms (SNPs) and insertion/deletion polymorphisms (indels) in expressed sequence tag (EST) data. The program uses d2cluster and cap3 to cluster and align EST sequences, and uses redundancy to differentiate between candidate SNPs and sequence errors. Candidate polymorphisms are identified as occurring in multiple reads within an alignment. For each candidate SNP, two measures of confidence are calculated, the redundancy of the polymorphism at a SNP locus and the co segregation of the candidate SNP with other SNPs in the alignment.'),
(70543, 2003, 'bio', 'Melina: motif extraction from promoter regions of potentially co-regulated genes', 'Poluliakh, Natalia|Takagi, Toshihisa|Nakai, Kenta', 'Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan.|Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan.|Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan.', 'Japan|Japan|Japan', 0, 'Amino Acid Motifs|Database Management Systems|Information Storage and Retrieval|Promoter Regions, Genetic|Proteins|Quality Control|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btf872', '12584132', 'Melina assists users to compare the results of four public softwares for DNA motif extraction in order to both confirm the reliability of each finding and avoid missing important motifs. It is also useful to optimize the sensitivity of software with a series of different parameter settings.'),
(70544, 2003, 'bio', 'AltAVisT: comparing alternative multiple sequence alignments', 'Morgenstern, Burkhard|Goel, Sachin|Sczyrba, Alexander|Dress, Andreas', 'International Graduate School in Bioinformatics and Genome Research, University of Bielefeld, Postfach 10 01 31, 33501 Bielefeld, Germany. burkhard@TechFak.Uni-Bielefeld.DE|International Graduate School in Bioinformatics and Genome Research, University of Bielefeld, Postfach 10 01 31, 33501 Bielefeld, Germany. burkhard@TechFak.Uni-Bielefeld.DE|International Graduate School in Bioinformatics and Genome Research, University of Bielefeld, Postfach 10 01 31, 33501 Bielefeld, Germany. burkhard@TechFak.Uni-Bielefeld.DE|International Graduate School in Bioinformatics and Genome Research, University of Bielefeld, Postfach 10 01 31, 33501 Bielefeld, Germany. burkhard@TechFak.Uni-Bielefeld.DE', 'Germany|Germany|Germany|Germany', 22, 'Color|Database Management Systems|Quality Control|Sequence Alignment|Sequence Analysis|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btf882', '12584133', 'We introduce a WWW-based tool that is able to compare two alternative multiple alignments of a given sequence set. Regions where both alignments coincide are color-coded to visualize the local agreement between the two alignments and to identify those regions that can be considered to be reliably aligned.'),
(70545, 2003, 'bio', 'PCMA: fast and accurate multiple sequence alignment based on profile consistency', 'Pei, Jimin|Sadreyev, Ruslan|Grishin, Nick V', 'Howard Hughes Medical Institute, and Department of Biochemistry, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-9050, USA. jpei@mednet.swmed.edu|Howard Hughes Medical Institute, and Department of Biochemistry, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-9050, USA. jpei@mednet.swmed.edu|Howard Hughes Medical Institute, and Department of Biochemistry, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-9050, USA. jpei@mednet.swmed.edu', 'United States|United States|United States', 169, 'Algorithms|Database Management Systems|Quality Control|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btg008', '12584134', 'PCMA (profile consistency multiple sequence alignment) is a progressive multiple sequence alignment program that combines two different alignment strategies. Highly similar sequences are aligned in a fast way as in ClustalW, forming pre-aligned groups. The T-Coffee strategy is applied to align the relatively divergent groups based on profile-profile comparison and consistency. The scoring function for local alignments of pre-aligned groups is based on a novel profile-profile comparison method that is a generalization of the PSI-BLAST approach to profile-sequence comparison. PCMA balances speed and accuracy in a flexible way and is suitable for aligning large numbers of sequences.'),
(70546, 2003, 'bio', 'PDP: protein domain parser', 'Alexandrov, Nickolai|Shindyalov, Ilya', 'Ceres Inc, 3007 Malibu Canyon Road, Malibu, CA 90265, USA. nicka@ceres-inc.com|Ceres Inc, 3007 Malibu Canyon Road, Malibu, CA 90265, USA. nicka@ceres-inc.com', 'Mali|Mali', 48, 'Algorithms|Databases, Protein|Information Storage and Retrieval|Protein Conformation|Protein Folding|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/btg006', '12584135', 'We have developed a program for automatic identification of domains in protein three-dimensional structures. Performance of the program was assessed by three different benchmarks: (i) by comparison with the expert-curated SCOP database of structural domains, (ii) by comparison with a collection of manual domain assignments, and (iii) by comparison with a set of 55 proteins, frequently used as a benchmark for automatic domain assignment. In all these benchmarks PDP identified domains correctly in more than 80% of proteins.'),
(70547, 2003, 'bio', 'pathSCOUT: exploration and analysis of biochemical pathways', 'Minch, E|de Rinaldis, M|Weiss, S', 'LION bioscience AG, 69123, Heidelberg, Germany. eric.minch@lionbioscience.com|LION bioscience AG, 69123, Heidelberg, Germany. eric.minch@lionbioscience.com|LION bioscience AG, 69123, Heidelberg, Germany. eric.minch@lionbioscience.com', 'Germany|Germany|Germany', 1, 'Biochemical Phenomena|Database Management Systems|Enzymes|Information Storage and Retrieval|Internet|Models, Biological|Models, Chemical|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btf880', '12584136', 'pathSCOUT provides access, display and exploration of data relevant to biochemical pathways, and enables analysis of pathway model structure and behavior.'),
(70548, 2003, 'bio', 'KnowledgeEditor: a new tool for interactive modeling and analyzing biological pathways based on microarray data', 'Toyoda, Tetsuro|Konagaya, Akihiko', 'Bioinformatics Group, Genomic Sciences Center, RIKEN, 1-7-22 Suehiro, Tsurumi, Yokohama, Kanagawa, 230-0045, Japan. bioinfo@gsc.riken.go.jp|Bioinformatics Group, Genomic Sciences Center, RIKEN, 1-7-22 Suehiro, Tsurumi, Yokohama, Kanagawa, 230-0045, Japan. bioinfo@gsc.riken.go.jp', 'Japan|Japan', 13, 'Cluster Analysis|Database Management Systems|Documentation|Gene Expression Regulation|Information Storage and Retrieval|Models, Biological|Models, Chemical|Oligonucleotide Array Sequence Analysis|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btf874', '12584137', 'KnowledgeEditor is a graphical workbench for biological experts to model biomolecular network graphs. The modeled network data are represented by SRML, and can be published via the internet with the help of plug-in module GSCope. KnowledgeEditor helps us to model and analyze biological pathways based on microarray data. It is possible to analyze the drawn networks by simulating up-down regulatory cascade in molecular interactions.'),
(70549, 2003, 'bio', 'Modeling biological systems using Dynetica--a simulator of dynamic networks', 'You, Lingchong|Hoonlor, Apirak|Yin, John', 'Division of Chemistry and Chemical Engineering, California Institute of Technology, USA.|Division of Chemistry and Chemical Engineering, California Institute of Technology, USA.|Division of Chemistry and Chemical Engineering, California Institute of Technology, USA.', 'United States|United States|United States', 10, 'Algorithms|Computer Simulation|Kinetics|Models, Biological|Models, Chemical|Models, Genetic|Software|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btg009', '12584138', 'We present Dynetica, a user-friendly simulator of dynamic networks for constructing, visualizing, and analyzing kinetic models of biological systems. In addition to generic reaction networks, Dynetica facilitates construction of models of genetic networks, where many reactions are gene expression and interactions among gene products. Further, it integrates the capability of conducting both deterministic and stochastic simulations.'),
(70550, 2003, 'bio', 'GSCope: a clipped fisheye viewer effective for highly complicated biomolecular network graphs', 'Toyoda, Tetsuro|Mochizuki, Yoshiki|Konagaya, Akihiko', 'Bioinformatics Group, Genomic Sciences Center, RIKEN, 1-7-22, Suehiro, Tsurumi, Yokohama, Kanagawa 230-0045, Japan. gscope@gsc.riken.go.jp|Bioinformatics Group, Genomic Sciences Center, RIKEN, 1-7-22, Suehiro, Tsurumi, Yokohama, Kanagawa 230-0045, Japan. gscope@gsc.riken.go.jp|Bioinformatics Group, Genomic Sciences Center, RIKEN, 1-7-22, Suehiro, Tsurumi, Yokohama, Kanagawa 230-0045, Japan. gscope@gsc.riken.go.jp', 'Japan|Japan|Japan', 3, 'Computer Graphics|Data Display|Models, Biological|Models, Chemical|Models, Molecular|Proteins|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg001', '12584139', 'A graphical tool to visualize highly complicated biomolecular network graphs is described. It helps us to understand the graphs from macroscopic and microscopic viewpoints by incorporating continuous transition from global to clipped hyperbolic projection. GSCope also helps us to find a molecule in the graphs by offering several searching functions. It is useful to publish biomolecular network graphs on the internet.'),
(70551, 2003, 'bio', 'WiGID: wireless genome information database', 'Ursing, Björn M', 'Center for Genomics and Bioinformatics, Karolinska Institute, SE-171 77 Stockholm, Sweden. bjorn.ursing@cgb.ki.se', 'Sweden', 1, 'Database Management Systems|Databases, Nucleic Acid|Genome|Information Storage and Retrieval|Internet|Telecommunications', 'Journal Article', '10.1093/bioinformatics/btf873', '12584140', 'WiGID, wireless genome information database, is a new application for mobile internet and can be reached through wireless application protocol (WAP). The main purpose of WiGID is to give easy access to information on completely sequenced genomes. Genome entries in WiGID can be queried by the number of open reading frames (ORFs), genus and species name and year published. Initial search results are linked to information on the full entry.'),
(70552, 2003, 'bio', 'Wrapping up BLAST and other applications for use on Unix clusters', 'Hokamp, Karsten|Shields, Denis C|Wolfe, Kenneth H|Caffrey, Daniel R', 'Department of Genetics, University of Dublin, Trinity College, Dublin 2, Ireland. karsten@oscar.gen.tcd.ie|Department of Genetics, University of Dublin, Trinity College, Dublin 2, Ireland. karsten@oscar.gen.tcd.ie|Department of Genetics, University of Dublin, Trinity College, Dublin 2, Ireland. karsten@oscar.gen.tcd.ie|Department of Genetics, University of Dublin, Trinity College, Dublin 2, Ireland. karsten@oscar.gen.tcd.ie', 'Ireland|Ireland|Ireland|Ireland', 2, 'Computer Communication Networks|Computer Systems|Computing Methodologies|Database Management Systems|Information Storage and Retrieval|Quality Control|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btg007', '12584141', 'We have developed two programs that speed up common bioinformatic applications by spreading them across a UNIX cluster.(1) BLAST.pm, a new module for the MOLLUSC package. (2) WRAPID, a simple tool for parallelizing large numbers of small instances of programs such as BLAST, FASTA and CLUSTALW.'),
(70553, 2003, 'bio', 'Can transcriptome size be estimated from SAGE catalogs?', 'Stern, Michael D|Anisimov, Sergey V|Boheler, Kenneth R', 'Laboratory of Cardiovascular Science, Gerontology Research Center, National Institute on Aging, NIH, 5600 Nathan Shock Drive, Baltimore, MD 21224, USA.|Laboratory of Cardiovascular Science, Gerontology Research Center, National Institute on Aging, NIH, 5600 Nathan Shock Drive, Baltimore, MD 21224, USA.|Laboratory of Cardiovascular Science, Gerontology Research Center, National Institute on Aging, NIH, 5600 Nathan Shock Drive, Baltimore, MD 21224, USA.', 'United States|United States|United States', 23, 'Algorithms|Animals|Expressed Sequence Tags|Gene Dosage|Gene Expression Profiling|Gene Expression Regulation, Developmental|Genome|Mice|Models, Genetic|Models, Statistical|Monte Carlo Method|Proteins|RNA, Messenger|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software|Stem Cells|Transcription, Genetic', 'Evaluation Studies', '10.1093/bioinformatics/btg018', '12611798', 'SAGE (Serial Analysis of Gene Expression) can be used to estimate the number of unique transcripts in a transcriptome. A simple estimator that corrects for sequencing and sampling errors was applied to a SAGE library (137 832 tags) obtained from mouse embryonic stem cells, and also to Monte Carlo simulated libraries generated using assumed distributions of true expression levels consistent with the data.'),
(70554, 2003, 'bio', 'An information theoretic approach for analyzing temporal patterns of gene expression', 'Kasturi, Jyotsna|Acharya, Raj|Ramanathan, Murali', 'Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA 16802, USA. jkasturi@cse.psu.edu|Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA 16802, USA. jkasturi@cse.psu.edu|Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA 16802, USA. jkasturi@cse.psu.edu', 'United States|United States|United States', 66, 'Algorithms|Cell Cycle|Cluster Analysis|Fibroblasts|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Software|Time Factors|Yeasts', 'Evaluation Studies', '10.1093/bioinformatics/btg020', '12611799', 'Arrays allow measurements of the expression levels of thousands of mRNAs to be made simultaneously. The resulting data sets are information rich but require extensive mining to enhance their usefulness. Information theoretic methods are capable of assessing similarities and dissimilarities between data distributions and may be suited to the analysis of gene expression experiments. The purpose of this study was to investigate information theoretic data mining approaches to discover temporal patterns of gene expression from array-derived gene expression data.'),
(70555, 2003, 'bio', 'Comparisons and validation of statistical clustering techniques for microarray gene expression data', 'Datta, Susmita|Datta, Somnath', 'Department of Mathematics and Statistics and Department of Biology, Georgia State University, Atlanta, GA 30303, USA. sdatta@mathstat.gsu.edu|Department of Mathematics and Statistics and Department of Biology, Georgia State University, Atlanta, GA 30303, USA. sdatta@mathstat.gsu.edu', 'Georgia|Georgia', 61, 'Algorithms|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software|Spores, Fungal|Yeasts', 'Comparative Study', '10.1093/bioinformatics/btg025', '12611800', 'With the advent of microarray chip technology, large data sets are emerging containing the simultaneous expression levels of thousands of genes at various time points during a biological process. Biologists are attempting to group genes based on the temporal pattern of their expression levels. While the use of hierarchical clustering (UPGMA) with correlation distance has been the most common in the microarray studies, there are many more choices of clustering algorithms in pattern recognition and statistics literature. At the moment there do not seem to be any clear-cut guidelines regarding the choice of a clustering algorithm to be used for grouping genes based on their expression profiles.'),
(70556, 2003, 'bio', 'A multivariate approach applied to microarray data for identification of genes with cell cycle-coupled transcription', 'Johansson, Daniel|Lindgren, Petter|Berglund, Anders', 'Research group for Chemometrics, Organic Chemistry, Department of Chemistry, Umeå University, Sweden.|Research group for Chemometrics, Organic Chemistry, Department of Chemistry, Umeå University, Sweden.|Research group for Chemometrics, Organic Chemistry, Department of Chemistry, Umeå University, Sweden.', 'Sweden|Sweden|Sweden', 30, 'Algorithms|Cell Cycle|Gene Expression Profiling|Gene Expression Regulation|Least-Squares Analysis|Models, Genetic|Models, Statistical|Multivariate Analysis|Oligonucleotide Array Sequence Analysis|Periodicity|Regression Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Transcription, Genetic|Yeasts', 'Comparative Study', '10.1093/bioinformatics/btg017', '12611801', 'We have analyzed microarray data using a modeling approach based on the multivariate statistical method partial least squares (PLS) regression to identify genes with periodic fluctuations in expression levels coupled to the cell cycle in the budding yeast, Saccharomyces cerevisiae. PLS has major advantages for analyzing microarray data since it can model data sets with large numbers of variables and with few observations. A response model was derived describing the expression profile over time expected for periodically transcribed genes, and was used to identify budding yeast transcripts with similar profiles. PLS was then used to interpret the importance of the variables (genes) for the model, yielding a ranking list of how well the genes fitted the generated model. Application of an appropriate cutoff value, calculated from randomized data, allows the identification of genes whose expression appears to be synchronized with cell cycling. Our approach also provides information about the stage in the cell cycle where their transcription peaks. Three synchronized yeast cell microarray data sets were analyzed, both separately and combined. Cell cycle-coupled periodicity was suggested for 455 of the 6,178 transcripts monitored in the combined data set, at a significance level of 0.5%. Among the candidates, 85% of the known periodic transcripts were included. Analysis of the three data sets separately yielded similar ranking lists, showing that the method is robust.'),
(70557, 2003, 'bio', 'Clustering of time-course gene expression data using a mixed-effects model with B-splines', 'Luan, Yihui|Li, Hongzhe', 'Rowe Program in Human Genetics, Department of Medicine, University of California, Davis, CA 95616-8500, USA.|Rowe Program in Human Genetics, Department of Medicine, University of California, Davis, CA 95616-8500, USA.', 'United States|United States', 225, 'Algorithms|Blood|Cell Cycle|Cluster Analysis|Computer Simulation|Fibroblasts|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Periodicity|Sequence Alignment|Sequence Analysis, DNA|Time Factors|Transcription, Genetic|Yeasts', 'Journal Article', '10.1093/bioinformatics/btg014', '12611802', 'Time-course gene expression data are often measured to study dynamic biological systems and gene regulatory networks. To account for time dependency of the gene expression measurements over time and the noisy nature of the microarray data, the mixed-effects model using B-splines was introduced. This paper further explores such mixed-effects model in analyzing the time-course gene expression data and in performing clustering of genes in a mixture model framework.'),
(70558, 2003, 'bio', 'Estimating the diversity of peptide populations from limited sequence data', 'Makowski, Lee|Soares, Alexei', 'Bioscience Division, Argonne National Laboratory, 9700 S. Cass Avenue Argonne, Illinois 60439, USA. lmakowski@anl.gov|Bioscience Division, Argonne National Laboratory, 9700 S. Cass Avenue Argonne, Illinois 60439, USA. lmakowski@anl.gov', 'United States|United States', 30, 'Algorithms|Amino Acid Sequence|Bacteriophages|Codon|Computer Simulation|Escherichia coli|Genetic Variation|Humans|Models, Genetic|Models, Statistical|Molecular Sequence Data|Peptide Library|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg013', '12611803', 'Combinatorial libraries of peptides such as those displayed on the surface of a bacteriophage particle have become widely used tools for characterizing protein-protein and protein-small molecule interactions. The quality of a library frequently depends on its completeness, or diversity-the proportion of possible sequences actually present in the library. The diversity of these libraries is frequently quoted on the basis of phage titers that provide little information about their completeness.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70559, 2003, 'bio', 'Statistical alignment based on fragment insertion and deletion models', 'Metzler, Dirk', 'Johann Wolfgang Goethe-Universität, Fachbereich Mathematik, Frankfurt am Main, Germany. dmetzler@math.uni-frankfurt.de', 'Germany', 12, 'Algorithms|Animals|Base Sequence|Computer Simulation|DNA Mutational Analysis|DNA Transposable Elements|Evolution, Molecular|Gene Deletion|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Genetic|Models, Statistical|Molecular Sequence Data|Oligodeoxyribonucleotides|Pongo pygmaeus|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Stochastic Processes|Viral Proteins', 'Comparative Study', '10.1093/bioinformatics/btg026', '12611804', 'The topic of this paper is the estimation of alignments and mutation rates based on stochastic sequence-evolution models that allow insertions and deletions of subsequences (fragments) and not just single bases. The model we propose is a variant of a model introduced by Thorne et al., (J. Mol. Evol., 34, 3-16, 1992). The computational tractability of the model depends on certain restrictions in the insertion/deletion process, possible effects we discuss.'),
(70560, 2003, 'bio', 'MaxSubSeq: an algorithm for segment-length optimization The case study of the transmembrane spanning segments', 'Fariselli, Piero|Finelli, Michele|Marchignoli, Davide|Martelli, Pier Luigi|Rossi, Ivan|Casadio, Rita', 'Department of Biology/CIRB, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. piero@biocomp.unibo.it|Department of Biology/CIRB, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. piero@biocomp.unibo.it|Department of Biology/CIRB, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. piero@biocomp.unibo.it|Department of Biology/CIRB, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. piero@biocomp.unibo.it|Department of Biology/CIRB, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. piero@biocomp.unibo.it|Department of Biology/CIRB, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. piero@biocomp.unibo.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 22, 'Algorithms|Amino Acid Sequence|Animals|Calcium-Transporting ATPases|Cattle|Electron Transport Complex IV|Membrane Proteins|Molecular Conformation|Molecular Sequence Data|Porins|Quality Control|Rabbits|Reproducibility of Results|Salmonella typhimurium|Sarcoplasmic Reticulum|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg023', '12611805', 'A problem in predicting the topography of transmembrane proteins is the optimal localization of the transmembrane segments along the protein sequences, provided that each residue is associated with a propensity of being or not being included in the transmembrane protein region. From previous work it is known that post-processing of propensity signals with suited algorithms can greatly improve the quality and the accuracy of the predictions. In this paper we describe a general dynamic programming-like algorithm (MaxSubSeq, Maximal SubSequence) specifically designed to optimize the number and length of segments with constrained length in a given protein sequence. Previous application of our algorithm, has proved its effectiveness in the optimization task of both neural network and hidden Markov models output, and in this paper we present the detailed description of MaxSubSeq.'),
(70561, 2003, 'bio', 'Detection of unrelated proteins in sequences multiple alignments by using predicted secondary structures', 'Errami, Mounir|Geourjon, Christophe|Deléage, Gilbert', 'Pôle de BioInformatique Lyonnais, Institut de Biologie et de Chimie des Protéines, Centre National de la Recherche Scientifique, UMR 5086, 69367 Lyon CEDEX 07, France.|Pôle de BioInformatique Lyonnais, Institut de Biologie et de Chimie des Protéines, Centre National de la Recherche Scientifique, UMR 5086, 69367 Lyon CEDEX 07, France.|Pôle de BioInformatique Lyonnais, Institut de Biologie et de Chimie des Protéines, Centre National de la Recherche Scientifique, UMR 5086, 69367 Lyon CEDEX 07, France.', 'France|France|France', 16, 'Algorithms|Amino Acid Sequence|Base Sequence|Databases, Protein|Protein Conformation|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Serine Proteinase Inhibitors', 'Comparative Study', '10.1093/bioinformatics/btg016', '12611806', 'Multiple sequence alignments are essential tools for establishing the homology relations between proteins. Essential amino acids for the function and/or the structure are generally conserved, thus providing key arguments to help in protein characterization. However for distant proteins, it is more difficult to establish, in a reliable way, the homology relations that may exist between them. In this article, we show that secondary structure prediction is a valuable way to validate protein families at low identity rate.'),
(70562, 2003, 'bio', 'Alignment-free sequence comparison-a review', 'Vinga, Susana|Almeida, Jonas', 'Department of Biometry & Epidemiology, Medical University of South Carolina, 135 Cannon Street, Suite 303, PO Box 250835, Charleston, SC 29425, USA.|Department of Biometry & Epidemiology, Medical University of South Carolina, 135 Cannon Street, Suite 303, PO Box 250835, Charleston, SC 29425, USA.', 'United States|United States', 540, 'Algorithms|Animals|Humans|Models, Genetic|Models, Statistical|Sequence Alignment|Sequence Analysis|Sequence Homology', 'Comparative Study', '10.1093/bioinformatics/btg005', '12611807', 'Genetic recombination and, in particular, genetic shuffling are at odds with sequence comparison by alignment, which assumes conservation of contiguity between homologous segments. A variety of theoretical foundations are being used to derive alignment-free methods that overcome this limitation. The formulation of alternative metrics for dissimilarity between sequences and their algorithmic implementations are reviewed.'),
(70563, 2003, 'bio', 'The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models', 'Hucka, M|Finney, A|Sauro, H M|Bolouri, H|Doyle, J C|Kitano, H|Arkin, A P|Bornstein, B J|Bray, D|Cornish-Bowden, A|Cuellar, A A|Dronov, S|Gilles, E D|Ginkel, M|Gor, V|Goryanin, I I|Hedley, W J|Hodgman, T C|Hofmeyr, J-H|Hunter, P J|Juty, N S|Kasberger, J L|Kremling, A|Kummer, U|Le Novère, N|Loew, L M|Lucio, D|Mendes, P|Minch, E|Mjolsness, E D|Nakayama, Y|Nelson, M R|Nielsen, P F|Sakurada, T|Schaff, J C|Shapiro, B E|Shimizu, T S|Spence, H D|Stelling, J|Takahashi, K|Tomita, M|Wagner, J|Wang, J|SBML Forum', 'Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu|Control and Dynamical Systems, MC 107-81, California Institute of Technology, Pasadena, CA 91125, USA. sysbio-team@caltech.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|Uni', 1990, 'Database Management Systems|Databases, Factual|Documentation|Gene Expression Regulation|Hypermedia|Information Storage and Retrieval|Metabolism|Models, Biological|Models, Chemical|Programming Languages|Software|Software Design|Terminology as Topic|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/btg015', '12611808', 'Molecular biotechnology now makes it possible to build elaborate systems models, but the systems biology community needs information standards if models are to be shared, evaluated and developed cooperatively.'),
(70564, 2003, 'bio', 'Subnetwork hierarchies of biochemical pathways', 'Holme, Petter|Huss, Mikael|Jeong, Hawoong', 'Department of Theoretical Physics, Umea, 901 87 Umea, Sweden. holme@tp.umu.se|Department of Theoretical Physics, Umea, 901 87 Umea, Sweden. holme@tp.umu.se|Department of Theoretical Physics, Umea, 901 87 Umea, Sweden. holme@tp.umu.se', 'Sweden|Sweden|Sweden', 276, 'Algorithms|Genomics|Metabolism|Models, Biological|Models, Chemical|Pattern Recognition, Automated|Pneumonia, Mycoplasma|Proteomics|Treponema pallidum', 'Evaluation Studies', '10.1093/bioinformatics/btg033', '12611809', 'The vastness and complexity of the biochemical networks that have been mapped out by modern genomics calls for decomposition into subnetworks. Such networks can have inherent non-local features that require the global structure to be taken into account in the decomposition procedure. Furthermore, basic questions such as to what extent the network (graph theoretically) can be said to be built by distinct subnetworks are little studied.'),
(70565, 2003, 'bio', 'PopHist: inferring population history from the spectrum of allele frequencies', 'Wooding, Stephen', 'Eccles Institute of Human Genetics, University of Utah, 15 North 2030 East, Salt Lake City, UT 84112-5330, USA. swooding@genetics.utah.edu', 'United States', 3, 'Algorithms|Alleles|Animals|Biological Evolution|Computer Simulation|DNA Mutational Analysis|Gene Frequency|Humans|Likelihood Functions|Models, Genetic|Models, Statistical|Polymorphism, Genetic|Population|Population Dynamics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btg024', '12611810', 'PopHist is a computer program that uses the frequency spectrum of alleles to: (a) estimate maximum likelihood parameters describing a populations history, and (b) compare alternative hypotheses about population history using likelihood ratio tests. The program uses the matrix coalescent, a method for calculating theoretical frequency spectra that can be applied to sets of unlinked sites.'),
(70566, 2003, 'bio', '3MOTIF: visualizing conserved protein sequence motifs in the protein structure database', 'Bennett, Steven P|Nevill-Manning, Craig G|Brutlag, Douglas L', 'Department of Biochemistry, B400 Beckman Center, Stanford University, CA 94305-5307, USA.|Department of Biochemistry, B400 Beckman Center, Stanford University, CA 94305-5307, USA.|Department of Biochemistry, B400 Beckman Center, Stanford University, CA 94305-5307, USA.', 'United States|United States|United States', 6, 'Amino Acid Motifs|Amino Acid Sequence|Conserved Sequence|Database Management Systems|Databases, Protein|Imaging, Three-Dimensional|Internet|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btf862', '12611811', '3MOTIF is a web application that visually maps conserved sequence motifs onto three-dimensional protein structures in the Protein Data Bank (PDB, Berman et al., Nucleic Acids Res., 28, 235-242, 2000). Important properties of motifs such as conservation strength and solvent accessible surface area at each position are visually represented on the structure using a variety of color shading schemes. Users can manipulate the displayed motifs using the freely available Chime plugin.'),
(70567, 2003, 'bio', 'IS: a web-site for intron statistics', 'Barta, Endre|Kaján, László|Pongor, Sándor', 'Agricultural Biotechnology Center, 2100 Gödöllö, Hungary. barta@abc.hu|Agricultural Biotechnology Center, 2100 Gödöllö, Hungary. barta@abc.hu|Agricultural Biotechnology Center, 2100 Gödöllö, Hungary. barta@abc.hu', 'Hungary|Hungary|Hungary', 2, 'Database Management Systems|Databases, Nucleic Acid|Information Storage and Retrieval|Internet|Introns|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btg019', '12611812', 'A web server has been established for the statistical evaluation of introns in various taxonomic groups and the comparison of taxonomic groups in terms of intron type, length, base composition, etc. The options include the graphic analysis of splice sites and a probability test for exon-shuffling within the selected group.'),
(70568, 2003, 'bio', 'Protein family annotation in a multiple alignment viewer', 'Johnson, Jason M|Mason, Keith|Moallemi, Ciamac|Xi, Hualin|Somaroo, Shyamal|Huang, Enoch S', 'Pfizer Discovery Technology Center, 620 Memorial Drive, Cambridge, MA 02139, USA. jason_johnson@merck.com|Pfizer Discovery Technology Center, 620 Memorial Drive, Cambridge, MA 02139, USA. jason_johnson@merck.com|Pfizer Discovery Technology Center, 620 Memorial Drive, Cambridge, MA 02139, USA. jason_johnson@merck.com|Pfizer Discovery Technology Center, 620 Memorial Drive, Cambridge, MA 02139, USA. jason_johnson@merck.com|Pfizer Discovery Technology Center, 620 Memorial Drive, Cambridge, MA 02139, USA. jason_johnson@merck.com|Pfizer Discovery Technology Center, 620 Memorial Drive, Cambridge, MA 02139, USA. jason_johnson@merck.com', 'United States|United States|United States|United States|United States|United States', 36, 'Amino Acid Sequence|Documentation|Information Storage and Retrieval|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg021', '12611813', 'The Pfaat protein family alignment annotation tool is a Java-based multiple sequence alignment editor and viewer designed for protein family analysis. The application merges display features such as dendrograms, secondary and tertiary protein structure with SRS retrieval, subgroup comparison, and extensive user-annotation capabilities.'),
(70569, 2003, 'bio', 'The European Bioinformatics Institute web site: a new view', 'Lopez, Rodrigo|Robinson, Stephen|Kibria, Asif|Harte, Nicola|Patel, Gulam|Harper, Rob|Quevillon, Emmanuel|Silventoinen, Ville|Kallio, Kimmo|Jokinen, Petteri', 'EMBL Outstation the European Bioinformatics Institute, Hinxton Hall, Cambridge CB10 1SD, UK. rls@ebi.ac.uk|EMBL Outstation the European Bioinformatics Institute, Hinxton Hall, Cambridge CB10 1SD, UK. rls@ebi.ac.uk|EMBL Outstation the European Bioinformatics Institute, Hinxton Hall, Cambridge CB10 1SD, UK. rls@ebi.ac.uk|EMBL Outstation the European Bioinformatics Institute, Hinxton Hall, Cambridge CB10 1SD, UK. rls@ebi.ac.uk|EMBL Outstation the European Bioinformatics Institute, Hinxton Hall, Cambridge CB10 1SD, UK. rls@ebi.ac.uk|EMBL Outstation the European Bioinformatics Institute, Hinxton Hall, Cambridge CB10 1SD, UK. rls@ebi.ac.uk|EMBL Outstation the European Bioinformatics Institute, Hinxton Hall, Cambridge CB10 1SD, UK. rls@ebi.ac.uk|EMBL Outstation the European Bioinformatics Institute, Hinxton Hall, Cambridge CB10 1SD, UK. rls@ebi.ac.uk|EMBL Outstation the European Bioinformatics Institute, Hinxton Hall, Cambridge CB10 1SD, UK. rls@ebi.ac.uk|EMBL Outstation the European Bioinformatics Institute, Hinxton Hall, Cambridge CB10 1SD, UK. rls@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 1, 'Academies and Institutes|Database Management Systems|Databases, Genetic|Europe|Information Storage and Retrieval|Internet|Molecular Conformation|Protein Conformation|Sequence Alignment|Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btg022', '12611814', 'The European Bioinformatics Institute (EBI), and outstation of the European Molecular Biology laboratory, has revamped its web site for the second time since 1997 in order to address increased user demand as well as establishing better uniformity and easier accessibility for the ever growing number of users and services it offers to the community. A GRID-like hardware infrastructure has been put in place to provide round the clock services in a redundant and reliable fashion.'),
(70570, 2003, 'bio', 'Triplet repeats in human genome: distribution and their association with genes and other genomic regions', 'Subramanian, Subbaya|Madgula, Vamsi M|George, Ranjan|Mishra, Rakesh K|Pandit, Madhusudhan W|Kumar, Chanderashekar S|Singh, Lalji', 'Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad, 500 007, India.|Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad, 500 007, India.|Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad, 500 007, India.|Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad, 500 007, India.|Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad, 500 007, India.|Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad, 500 007, India.|Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad, 500 007, India.', 'India|India|India|India|India|India|India', 0, 'Databases, Nucleic Acid|Exons|Genome, Human|Humans|Information Storage and Retrieval|Introns|Sequence Alignment|Sequence Analysis, DNA|Trinucleotide Repeat Expansion|Trinucleotide Repeats|Untranslated Regions', 'Journal Article', '10.1093/bioinformatics/btg029', '12651711', 'Simple sequence repeats (SSRs) or microsatellite repeats are found abundantly in many prokaryotic and eukaryotic genomes. Among SSRs, triplet repeats are of special significance because some of them have been linked to various genetic disorders. The objective of the study is to analyze the triplet repeats of complete human genome and to identify the genes that contain the triplet repeats in their coding region. The analysis will help us to identify the candidate genes that have potential for repeat expansion.'),
(70571, 2003, 'bio', 'Automatic analysis of DNA microarray images using mathematical morphology', 'Angulo, Jesús|Serra, Jean', 'Centre de Morphologie Mathématique, Ecole des Mines de Paris, 77305 Fontainebleau, France. angulo,serra@cmm.ensmp.fr|Centre de Morphologie Mathématique, Ecole des Mines de Paris, 77305 Fontainebleau, France. angulo,serra@cmm.ensmp.fr', 'France|France', 123, 'Algorithms|Computer Simulation|Gene Expression Profiling|Image Interpretation, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Pilot Projects|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Spectrometry, Fluorescence|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/btg057', '12651712', 'DNA microarrays are an experimental technology which consists in arrays of thousands of discrete DNA sequences that are printed on glass microscope slides. Image analysis is an important aspect of microarray experiments. The aim of this step is to reduce an image of spots into a table with a measure of the intensity for each spot. Efficient, accurate and automatic analysis of DNA spot images is essential in order to use this technology in laboratory routines.'),
(70572, 2003, 'bio', 'Effective dimension reduction methods for tumor classification using gene expression data', 'Antoniadis, A|Lambert-Lacroix, S|Leblanc, F', 'Laboratoire IMAG-LMC, University Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France. anestis.antoniadis@imag.fr|Laboratoire IMAG-LMC, University Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France. anestis.antoniadis@imag.fr|Laboratoire IMAG-LMC, University Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France. anestis.antoniadis@imag.fr', 'France|France|France', 132, 'Algorithms|Colonic Neoplasms|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Variation|Humans|Leukemia|Models, Genetic|Models, Statistical|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sample Size', 'Comparative Study', '10.1093/bioinformatics/btg062', '12651713', 'One particular application of microarray data, is to uncover the molecular variation among cancers. One feature of microarray studies is the fact that the number n of samples collected is relatively small compared to the number p of genes per sample which are usually in the thousands. In statistical terms this very large number of predictors compared to a small number of samples or observations makes the classification problem difficult. An efficient way to solve this problem is by using dimension reduction statistical techniques in conjunction with nonparametric discriminant procedures.'),
(70573, 2003, 'bio', 'PCA disjoint models for multiclass cancer analysis using gene expression data', 'Bicciato, S|Luchini, A|Di Bello, C', 'Department of Chemical Process Engineering, University of Padova, via Marzolo, 9, 35131, Padova, Italy. silvio.bicciato@unipd.it|Department of Chemical Process Engineering, University of Padova, via Marzolo, 9, 35131, Padova, Italy. silvio.bicciato@unipd.it|Department of Chemical Process Engineering, University of Padova, via Marzolo, 9, 35131, Padova, Italy. silvio.bicciato@unipd.it', 'Italy|Italy|Italy', 91, 'Acute Disease|Algorithms|Biomarkers, Tumor|Child|Child, Preschool|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Infant|Infant, Newborn|Leukemia, Myeloid|Lymphoma, Non-Hodgkin|Models, Genetic|Models, Statistical|Neoplasms|Neuroblastoma|Oligonucleotide Array Sequence Analysis|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Principal Component Analysis|Rhabdomyosarcoma|Sarcoma, Ewing', 'Comparative Study', '10.1093/bioinformatics/btg051', '12651714', 'Microarray expression profiling appears particularly promising for a deeper understanding of cancer biology and to identify molecular signatures supporting the histological classification schemes of neoplastic specimens. However, molecular diagnostics based on microarray data presents major challenges due to the overwhelming number of variables and the complex, multiclass nature of tumor samples. Thus, the development of marker selection methods, that allow the identification of those genes that are most likely to confer high classification accuracy of multiple tumor types, and of multiclass classification schemes is of paramount importance.'),
(70574, 2003, 'bio', 'Mapping multiple co-sequenced T-DNA integration sites within the Arabidopsis genome', 'Presting, Gernot G', 'Torrey Mesa Research Institute, 3115 Merryfield Row, San Diego, CA 92121, USA. gernot@genome.clemson.edu', 'United States', 0, 'Arabidopsis|Base Sequence|DNA Mutational Analysis|DNA Transposable Elements|DNA, Bacterial|Gene Expression Profiling|Genome, Plant|Molecular Sequence Data|Mutation|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology', 'Comparative Study', '10.1093/bioinformatics/btg049', '12651715', 'Insertion mutagenesis, using transgenes or endogenous transposons, is a popular method for generating null mutations (knockouts) in model organisms. Insertions are mapped to specific genes by amplifying (via TAIL-PCR) and sequencing genomic regions flanking the inserted DNA. The presence of multiple TAIL-PCR templates in one sequencing reaction results in chimeric sequence of intermittently low quality. Standard processing of this sequence by applying Phred quality requirements results in loss of informative sequence, whereas not trimming low-quality sequence causes inclusion of low-complexity homopolymers from the ends of sequence runs. Accurate mapping of the flanking sequences is complicated by the presence of gene families.'),
(70575, 2003, 'bio', 'The fuzzy polynucleotide space: basic properties', 'Torres, Angela|Nieto, Juan J', 'Departamento de Psiquiatría, Radiología y Salud Pública, Facultad de Medicina, Universidad de Santiago de Compostela, Spain.|Departamento de Psiquiatría, Radiología y Salud Pública, Facultad de Medicina, Universidad de Santiago de Compostela, Spain.', 'Spain|Spain', 34, 'Algorithms|Codon|DNA, Bacterial|Escherichia coli|Fuzzy Logic|Gene Frequency|Genome, Bacterial|Mycobacterium tuberculosis|Polynucleotides|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg032', '12651716', 'Any triplet codon may be regarded as a 12-dimensional fuzzy code. Sufficient information about a particular sequence may not be available in certain situations. The investigator will be confronted with imprecise sequences, yet want to make comparisons of sequences. Fuzzy polynucleotides can be compared by using geometrical interpretation of fuzzy sets as points in a hypercube.'),
(70576, 2003, 'bio', 'The Z curve database: a graphic representation of genome sequences', 'Zhang, Chun-Ting|Zhang, Ren|Ou, Hong-Yu', 'Department of Physics, Tianjin University, Tianjin 300072, Peoples Republic of China. ctzhang@tju.edu.cn|Department of Physics, Tianjin University, Tianjin 300072, Peoples Republic of China. ctzhang@tju.edu.cn|Department of Physics, Tianjin University, Tianjin 300072, Peoples Republic of China. ctzhang@tju.edu.cn', 'China|China|China', 0, 'Animals|Base Sequence|Computer Graphics|DNA|Database Management Systems|Databases, Nucleic Acid|Genome|Humans|Information Storage and Retrieval|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg041', '12651717', 'Genome projects for many prokaryotic and eukaryotic species have been completed and more new genome projects are being underway currently. The availability of a large number of genomic sequences for researchers creates a need to find graphic tools to study genomes in a perceivable form. The Z curve is one of such tools available for visualizing genomes. The Z curve is a unique three-dimensional curve representation for a given DNA sequence in the sense that each can be uniquely reconstructed given the other. The Z curve database for more than 1000 genomes have been established here.'),
(70577, 2003, 'bio', 'The estimation of relative site variability among aligned homologous protein sequences', 'Horner, D S|Pesole, G', 'Dipartimento di Fisiologia e Biochimica Generale, Universita di Milano, 20113 Milano, Italy.|Dipartimento di Fisiologia e Biochimica Generale, Universita di Milano, 20113 Milano, Italy.', 'Italy|Italy', 4, 'Algorithms|Amino Acid Sequence|Computer Simulation|Gene Frequency|Genetic Variation|Models, Genetic|Models, Statistical|Molecular Sequence Data|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology', 'Comparative Study', '10.1093/bioinformatics/btg063', '12651718', 'Maximum likelihood-based methods to estimate site by site substitution rate variability in aligned homologous protein sequences rely on the formulation of a phylogenetic tree and generally assume that the patterns of relative variability follow a pre-determined distribution. We present a phylogenetic tree-independent method to estimate the relative variability of individual sites within large datasets of homologous protein sequences. It is based upon two simple assumptions. Firstly that substitutions observed between two closely related sequences are likely, in general, to occur at the most variable sites. Secondly that non-conservative amino acid substitutions tend to occur at more variable sites. Our methodology makes no assumptions regarding the underlying pattern of relative variability between sites.'),
(70578, 2003, 'bio', 'Greedy mixture learning for multiple motif discovery in biological sequences', 'Blekas, Konstantinos|Fotiadis, Dimitrios I|Likas, Aristidis', 'Department of Computer Science, University of Ioannina 45110 Ioannina, Greece. kblekas@cs.uoi.gr|Department of Computer Science, University of Ioannina 45110 Ioannina, Greece. kblekas@cs.uoi.gr|Department of Computer Science, University of Ioannina 45110 Ioannina, Greece. kblekas@cs.uoi.gr', 'Greece|Greece|Greece', 38, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Conserved Sequence|Models, Chemical|Models, Genetic|Models, Statistical|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg037', '12651719', 'This paper studies the problem of discovering subsequences, known as motifs, that are common to a given collection of related biosequences, by proposing a greedy algorithm for learning a mixture of motifs model through likelihood maximization. The approach adds sequentially a new motif to a mixture model by performing a combined scheme of global and local search for appropriately initializing its parameters. In addition, a hierarchical partitioning scheme based on kd-trees is presented for partitioning the input dataset in order to speed-up the global searching procedure. The proposed method compares favorably over the well-known MEME approach and treats successfully several drawbacks of MEME.'),
(70579, 2003, 'bio', 'How Bayes tests of molecular phylogenies compare with frequentist approaches', 'Aris-Brosou, Stéphane', 'Department of Biology, University College London, Darwin Building, Gower Street, London WC1E 6BT, USA. stephane@statgen.ncsu.edu', 'United States', 0, 'Algorithms|Bayes Theorem|DNA Mutational Analysis|DNA, Mitochondrial|Evolution, Molecular|Gene Expression Profiling|HIV-1|Humans|Models, Genetic|Models, Statistical|Phylogeny|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg065', '12651720', 'The desire to compare molecular phylogenies has stimulated the design of numerous tests. Most of these tests are formulated in a frequentist framework, and it is not known how they compare with Bayes procedures. I propose here two new Bayes tests that either compare pairs of trees (Bayes hypothesis test, BHT), or test each tree against an average of the trees included in the analysis (Bayes significance test, BST).'),
(70580, 2003, 'bio', 'MINRMS: an efficient algorithm for determining protein structure similarity using root-mean-squared-distance', 'Jewett, Andrew I|Huang, Conrad C|Ferrin, Thomas E', 'Computer Graphics Laboratory, Department of Pharmaceutical Chemistry, University of California at San Fransisco, San Fransisco, CA 94143-0446, USA.|Computer Graphics Laboratory, Department of Pharmaceutical Chemistry, University of California at San Fransisco, San Fransisco, CA 94143-0446, USA.|Computer Graphics Laboratory, Department of Pharmaceutical Chemistry, University of California at San Fransisco, San Fransisco, CA 94143-0446, USA.', 'United States|United States|United States', 40, 'Algorithms|Amino Acid Sequence|Linear Models|Molecular Sequence Data|Muramidase|Protein Conformation|Proteins|Quality Control|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg035', '12651721', 'Existing algorithms for automated protein structure alignment generate contradictory results and are difficult to interpret. An algorithm which can provide a context for interpreting the alignment and uses a simple method to characterize protein structure similarity is needed.'),
(70581, 2003, 'bio', 'Prediction of human protein function according to Gene Ontology categories', 'Jensen, L J|Gupta, R|Staerfeldt, H-H|Brunak, S', 'Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Lyngby, Denmark. ljj@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Lyngby, Denmark. ljj@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Lyngby, Denmark. ljj@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Lyngby, Denmark. ljj@cbs.dtu.dk', 'Denmark|Denmark|Denmark|Denmark', 0, 'Algorithms|Database Management Systems|Databases, Protein|Gene Expression Profiling|Humans|Information Storage and Retrieval|Neural Networks (Computer)|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/btg036', '12651722', 'The human genome project has led to the discovery of many human protein coding genes which were previously unknown. As a large fraction of these are functionally uncharacterized, it is of interest to develop methods for predicting their molecular function from sequence.'),
(70582, 2003, 'bio', 'Dynamic modeling of genetic networks using genetic algorithm and S-system', 'Kikuchi, Shinichi|Tominaga, Daisuke|Arita, Masanori|Takahashi, Katsutoshi|Tomita, Masaru', 'Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-41-6 Aomi, Koto-ku, Tokyo, 135-0064, Japan. kikuchi@sfc.keio.ac.jp|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-41-6 Aomi, Koto-ku, Tokyo, 135-0064, Japan. kikuchi@sfc.keio.ac.jp|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-41-6 Aomi, Koto-ku, Tokyo, 135-0064, Japan. kikuchi@sfc.keio.ac.jp|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-41-6 Aomi, Koto-ku, Tokyo, 135-0064, Japan. kikuchi@sfc.keio.ac.jp|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-41-6 Aomi, Koto-ku, Tokyo, 135-0064, Japan. kikuchi@sfc.keio.ac.jp', 'Japan|Japan|Japan|Japan|Japan', 0, 'Algorithms|Computer Simulation|Feedback|Gene Expression Profiling|Gene Expression Regulation|Metabolism|Models, Genetic|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg027', '12651723', 'The modeling of system dynamics of genetic networks, metabolic networks or signal transduction cascades from time-course data is formulated as a reverse-problem. Previous studies focused on the estimation of only network structures, and they were ineffective in inferring a network structure with feedback loops. We previously proposed a method to predict not only the network structure but also its dynamics using a Genetic Algorithm (GA) and an S-system formalism. However, it could predict only a small number of parameters and could rarely obtain essential structures. In this work, we propose a unified extension of the basic method. Notable improvements are as follows: (1) an additional term in its evaluation function that aims at eliminating futile parameters, (2) a crossover method called Simplex Crossover (SPX) to improve its optimization ability, and (3) a gradual optimization strategy to increase the number of predictable parameters.'),
(70583, 2003, 'bio', 'TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets', 'Pertea, Geo|Huang, Xiaoqiu|Liang, Feng|Antonescu, Valentin|Sultana, Razvan|Karamycheva, Svetlana|Lee, Yuandan|White, Joseph|Cheung, Foo|Parvizi, Babak|Tsai, Jennifer|Quackenbush, John', 'The Institute for Genomic Research, Rockville, MD 20850, USA.|The Institute for Genomic Research, Rockville, MD 20850, USA.|The Institute for Genomic Research, Rockville, MD 20850, USA.|The Institute for Genomic Research, Rockville, MD 20850, USA.|The Institute for Genomic Research, Rockville, MD 20850, USA.|The Institute for Genomic Research, Rockville, MD 20850, USA.|The Institute for Genomic Research, Rockville, MD 20850, USA.|The Institute for Genomic Research, Rockville, MD 20850, USA.|The Institute for Genomic Research, Rockville, MD 20850, USA.|The Institute for Genomic Research, Rockville, MD 20850, USA.|The Institute for Genomic Research, Rockville, MD 20850, USA.|The Institute for Genomic Research, Rockville, MD 20850, 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', 1280, 'Cluster Analysis|Database Management Systems|Databases, Nucleic Acid|Expressed Sequence Tags|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology|Software', 'Journal Article', '10.1093/bioinformatics/btg034', '12651724', 'TGICL is a pipeline for analysis of large Expressed Sequence Tags (EST) and mRNA databases in which the sequences are first clustered based on pairwise sequence similarity, and then assembled by individual clusters (optionally with quality values) to produce longer, more complete consensus sequences. The system can run on multi-CPU architectures including SMP and PVM.'),
(70584, 2003, 'bio', 'DigiNorthern, digital expression analysis of query genes based on ESTs', 'Wang, Jianxin|Liang, Ping', 'Department of Cancer Genetics and the Biomathematics & Biostatistics Core Facility, Roswell Park Cancer Institute, Elm & Carlton Streets, Buffalo, NY 14263, USA.|Department of Cancer Genetics and the Biomathematics & Biostatistics Core Facility, Roswell Park Cancer Institute, Elm & Carlton Streets, Buffalo, NY 14263, USA.', 'United States|United States', 0, 'DNA, Neoplasm|Databases, Bibliographic|Databases, Genetic|Expressed Sequence Tags|Gene Expression Profiling|Gene Expression Regulation|Gene Expression Regulation, Neoplastic|Humans|Internet|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg044', '12651725', 'DigiNorthern (DN) is a web-based tool for virtually displaying expression profiles of query genes based on EST sequences. Two utilities are available: DN1 takes one query gene and quantitatively display its expression levels in tissues/organs that express the gene with comparison between normal and neoplastic status of each tissue, DN2 takes two sequences as query genes and compares their expression profiles side by side.'),
(70585, 2003, 'bio', 'Gene expression data preprocessing', 'Herrero, J|Díaz-Uriarte, R|Dopazo, J', 'Unidad de Bioinformática, Centro Nacional de Investigaciones Oncológicas (CNIO), Melchor Fernández Almagro, 3 28029 Madrid, Spain.|Unidad de Bioinformática, Centro Nacional de Investigaciones Oncológicas (CNIO), Melchor Fernández Almagro, 3 28029 Madrid, Spain.|Unidad de Bioinformática, Centro Nacional de Investigaciones Oncológicas (CNIO), Melchor Fernández Almagro, 3 28029 Madrid, Spain.', 'Spain|Spain|Spain', 73, 'Database Management Systems|Gene Expression Profiling|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg040', '12651726', 'We present an interactive web tool for preprocessing microarray gene expression data. It analyses the data, suggests the most appropriate transformations and proceeds with them after user agreement. The normal preprocessing steps include scale transformations, management of missing values, replicate handling, flat pattern filtering and pattern standardization and they are required before performing any pattern analysis. The processed data set can be sent to other pattern analysis tools.'),
(70586, 2003, 'bio', 'Engene: the processing and exploratory analysis of gene expression data', 'García de la Nava, Jorge|Santaella, Daniel Franco|Cuenca Alba, Jesús|María Carazo, José|Trelles, Oswaldo|Pascual-Montano, Alberto', 'Computer Architecture Department, Universidad de Málaga, 29080 Málaga, Spain.|Computer Architecture Department, Universidad de Málaga, 29080 Málaga, Spain.|Computer Architecture Department, Universidad de Málaga, 29080 Málaga, Spain.|Computer Architecture Department, Universidad de Málaga, 29080 Málaga, Spain.|Computer Architecture Department, Universidad de Málaga, 29080 Málaga, Spain.|Computer Architecture Department, Universidad de Málaga, 29080 Málaga, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Database Management Systems|Gene Expression Profiling|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg028', '12651727', 'Engene is a versatile, and platform-independent web tool for exploratory analysis of gene expression data that aims at storing, visualizing and processing large sets of gene expression patterns.'),
(70587, 2003, 'bio', 'MatArray: a Matlab toolbox for microarray data', 'Venet, David', 'I.R.I.B.H.M. - Campus Hopital Erasme, Route de Lennik 808 Bat C, CP 602-1070 Brussels, Belgium. davenet@ulb.ac.be', 'Belgium', 0, 'Algorithms|Cluster Analysis|Databases, Bibliographic|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg046', '12651728', 'The microarray technology allows the high-throughput quantification of the mRNA level of thousands of genes under dozens of conditions, generating a wealth of data which must be analyzed using some form of computational means. A popular framework for such analysis is Matlab, a powerful computing language for which many functions have been written. However, although complex topics like neural networks or principal component analysis are freely available in Matlab, functions to perform more basic tasks like data normalization or hierarchical clustering in an efficient manner are not. The MatArray toolbox aims at filling this gap by offering efficient implementations of the most needed functions for microarray analysis. The functions in the toolbox are command-line only, since it is geared toward seasoned Matlab users.'),
(70588, 2003, 'bio', 'TRAIT (TRAnscript Integrated Table): a knowledgebase of human skeletal muscle transcripts', 'Toppo, Stefano|Cannata, Nicola|Fontana, Paolo|Romualdi, Chiara|Laveder, Paolo|Bertocco, Emanuela|Lanfranchi, Gerolamo|Valle, Giorgio', 'CRIBI, Università di Padova, via Ugo Bassi 58/B, Padova, 35131 Italy.|CRIBI, Università di Padova, via Ugo Bassi 58/B, Padova, 35131 Italy.|CRIBI, Università di Padova, via Ugo Bassi 58/B, Padova, 35131 Italy.|CRIBI, Università di Padova, via Ugo Bassi 58/B, Padova, 35131 Italy.|CRIBI, Università di Padova, via Ugo Bassi 58/B, Padova, 35131 Italy.|CRIBI, Università di Padova, via Ugo Bassi 58/B, Padova, 35131 Italy.|CRIBI, Università di Padova, via Ugo Bassi 58/B, Padova, 35131 Italy.|CRIBI, Università di Padova, via Ugo Bassi 58/B, Padova, 35131 Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Database Management Systems|Databases, Genetic|Documentation|Expressed Sequence Tags|Humans|Information Storage and Retrieval|Muscle Proteins|Muscle, Skeletal|Sequence Alignment|Sequence Analysis, DNA|Software|Transcription, Genetic|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg045', '12651729', 'TRAIT is a knowledgebase integrating information on transcripts with related data from genome, proteins, ortholog genes and diseases. It was initially built as a system to manage an EST-based gene discovery project on human skeletal muscle, which yielded over 4500 independent sequence clusters. Transcripts are annotated using automatic as well as manual procedures, linking known transcripts to public databases and unknown transcripts to tables of predicted features. Data are stored in a MySQL database. Complex queries are automatically built by means of a user-friendly web interface that allows the concurrent selection of many fields such as ontology, expression level, map position and protein domains. The results are parsed by the system and returned in a ranked order, in respect to the number of satisfied criteria.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70589, 2003, 'bio', 'MENDB: a database of polymorphic loci from natural populations', 'Livingstone, K|Rieseberg, L', 'Department of Biology, 142 Jordan Hall, Indiana University, Bloomington, IN 47405, USA. klivings@bio.indiana.edu|Department of Biology, 142 Jordan Hall, Indiana University, Bloomington, IN 47405, USA. klivings@bio.indiana.edu', 'India|India', 0, 'Database Management Systems|Databases, Nucleic Acid|Gene Expression Profiling|Genetic Variation|Information Storage and Retrieval|Internet|Polymorphism, Genetic|Sequence Alignment|Sequence Analysis, DNA|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg048', '12651730', 'MENDB is an online database for genetic markers determined to be polymorphic in natural populations. The database contains primer sequences and conditions for PCR, taxonomic information, and links to GenBank records, as well as basic statistics on the level of polymorphism for the surveyed populations/individuals.'),
(70590, 2003, 'bio', 'MHCBN: a comprehensive database of MHC binding and non-binding peptides', 'Bhasin, Manoj|Singh, Harpreet|Raghava, G P S', 'Institute of Microbial Technology, Chandigarh, India.|Institute of Microbial Technology, Chandigarh, India.|Institute of Microbial Technology, Chandigarh, India.', 'India|India|India', 0, 'Amino Acid Sequence|Binding Sites|Database Management Systems|Databases, Protein|Histocompatibility Antigens|Information Storage and Retrieval|Macromolecular Substances|Major Histocompatibility Complex|Molecular Sequence Data|Peptide Fragments|Peptides|Protein Binding|Protein Conformation|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg055', '12651731', 'MHCBN is a comprehensive database of Major Histocompatibility Complex (MHC) binding and non-binding peptides compiled from published literature and existing databases. The latest version of the database has 19 777 entries including 17 129 MHC binders and 2648 MHC non-binders for more than 400 MHC molecules. The database has sequence and structure data of (a) source proteins of peptides and (b) MHC molecules. MHCBN has a number of web tools that include: (i) mapping of peptide on query sequence, (ii) search on any field, (iii) creation of data sets, and (iv) online data submission. The database also provides hypertext links to major databases like SWISS-PROT, PDB, IMGT/HLA-DB, GenBank and PUBMED.'),
(70591, 2003, 'bio', 'GPCR-GRAPA-LIB--a refined library of hidden Markov Models for annotating GPCRs', 'Shigeta, Ron|Cline, Melissa|Liu, Guoying|Siani-Rose, Michael A', 'Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100 Emeryville, CA 94608, USA. ron_shigeta@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100 Emeryville, CA 94608, USA. ron_shigeta@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100 Emeryville, CA 94608, USA. ron_shigeta@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100 Emeryville, CA 94608, USA. ron_shigeta@affymetrix.com', 'United States|United States|United States|United States', 7, 'Algorithms|Amino Acid Sequence|Databases, Protein|Documentation|Evolution, Molecular|GTP-Binding Proteins|Models, Genetic|Models, Statistical|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btg061', '12651732', 'GPCR-GRAPA-LIB is a library of HMMs describing G protein coupled receptor families. These families are initially defined by class of receptor ligand, with divergent families divided into subfamilies using phylogenic analysis and knowledge of GPCR function. Protein sequences are applied to the models with the GRAPA curve-based selection criteria. RefSeq sequences for Homo sapiens, Drosophila melanogaster, and Caenorhabditis elegans have been annotated using this approach.'),
(70592, 2003, 'bio', 'PedNavigator: a pedigree drawing servlet for large and inbred populations', 'Mancosu, Gianmaria|Ledda, Giuseppe|Melis, Paola M', 'Shardna Life Science, Cagliari, Italy. mancosu@shardna.it|Shardna Life Science, Cagliari, Italy. mancosu@shardna.it|Shardna Life Science, Cagliari, Italy. mancosu@shardna.it', 'Italy|Italy|Italy', 0, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Genetic|Genetics, Population|Hypermedia|Inbreeding|Information Storage and Retrieval|Internet|Pedigree|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg050', '12651733', 'PedNavigator is a pedigree drawing application for large and complex pedigrees. It has been developed especially for genetic and epidemiological studies of isolated populations characterized by high inbreeding and multiple matrimonies. PedNavigator is written in Java and is intended as a server-side web application, allowing researchers to walk through family ties by point-and-clicking on persons symbols. The application is able to enrich the pedigree drawings with genotypic and phenotypic information taken from the underlying relational database.'),
(70593, 2003, 'bio', 'TreeSAAP: selection on amino acid properties using phylogenetic trees', 'Woolley, Steve|Johnson, Justin|Smith, Matthew J|Crandall, Keith A|McClellan, David A', 'Department of Computer Science, Brigham Young University, Provo, UT 84602, USA.|Department of Computer Science, Brigham Young University, Provo, UT 84602, USA.|Department of Computer Science, Brigham Young University, Provo, UT 84602, USA.|Department of Computer Science, Brigham Young University, Provo, UT 84602, USA.|Department of Computer Science, Brigham Young University, Provo, UT 84602, USA.', 'United States|United States|United States|United States|United States', 0, 'Amino Acid Sequence|Evolution, Molecular|Genetic Variation|Molecular Sequence Data|Phylogeny|Proteins|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg043', '12651734', 'The software program TreeSAAP measures the selective influences on 31 structural and biochemical amino acid properties during cladogenesis, and performs goodness-of-fit and categorical statistical tests.'),
(70594, 2003, 'bio', 'DomCut: prediction of inter-domain linker regions in amino acid sequences', 'Suyama, Mikita|Ohara, Osamu', 'Laboratory of DNA Technology, Kazusa DNA Research Institute, 1532-3 Yana, Kisarazu, Chiba 292-0812, Japan. suyama@embl-heidelberg.de|Laboratory of DNA Technology, Kazusa DNA Research Institute, 1532-3 Yana, Kisarazu, Chiba 292-0812, Japan. suyama@embl-heidelberg.de', 'Japan|Japan', 98, 'Amino Acid Sequence|Binding Sites|Databases, Protein|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Structure, Tertiary|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg031', '12651735', 'DomCut is a program to predict inter-domain linker regions solely by amino acid sequence information. The prediction is made by using linker index deduced from a data set of domain/linker segments. The linker preference profile, which is the averaged linker index along a sequence, can be visualized in the graphical interface.'),
(70595, 2003, 'bio', 'ASAP: automated sequence annotation pipeline for web-based updating of sequence information with a local dynamic database', 'Kossenkov, Andrew|Manion, Frank J|Korotkov, Eugene|Moloshok, Thomas D|Ochs, Michael F', 'Cybernetics Department, Moscow Engineering Physics Institute, Moscow, Russian Federation. av_kossenkov@fccc.edu|Cybernetics Department, Moscow Engineering Physics Institute, Moscow, Russian Federation. av_kossenkov@fccc.edu|Cybernetics Department, Moscow Engineering Physics Institute, Moscow, Russian Federation. av_kossenkov@fccc.edu|Cybernetics Department, Moscow Engineering Physics Institute, Moscow, Russian Federation. av_kossenkov@fccc.edu|Cybernetics Department, Moscow Engineering Physics Institute, Moscow, Russian Federation. av_kossenkov@fccc.edu', 'Russian Federation|Russian Federation|Russian Federation|Russian Federation|Russian Federation', 15, 'Database Management Systems|Databases, Nucleic Acid|Documentation|Expressed Sequence Tags|Information Storage and Retrieval|Internet|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btg056', '12651736', 'The automated sequence annotation pipeline (ASAP) is designed to ease routine investigation of new functional annotations on unknown sequences, such as expressed sequence tags (ESTs), through querying of web-accessible resources and maintenance of a local database. The system allows easy use of the output from one search as the input for a new search, as well as the filtering of results. The database is used to store formats and parameters and information for parsing data from web sites. The database permits easy updating of format information should a site modify the format of a query or of a returned web page.'),
(70596, 2003, 'bio', 'Cellerator: extending a computer algebra system to include biochemical arrows for signal transduction simulations', 'Shapiro, Bruce E|Levchenko, Andre|Meyerowitz, Elliot M|Wold, Barbara J|Mjolsness, Eric D', 'Jet Propulsion Laboratory, California Institute of Technology, Mail Stop 126-347, 4800 Oak Grove Drive, Pasadena, CA 91109, USA. bshapiro@jpl.nasa.gov|Jet Propulsion Laboratory, California Institute of Technology, Mail Stop 126-347, 4800 Oak Grove Drive, Pasadena, CA 91109, USA. bshapiro@jpl.nasa.gov|Jet Propulsion Laboratory, California Institute of Technology, Mail Stop 126-347, 4800 Oak Grove Drive, Pasadena, CA 91109, USA. bshapiro@jpl.nasa.gov|Jet Propulsion Laboratory, California Institute of Technology, Mail Stop 126-347, 4800 Oak Grove Drive, Pasadena, CA 91109, USA. bshapiro@jpl.nasa.gov|Jet Propulsion Laboratory, California Institute of Technology, Mail Stop 126-347, 4800 Oak Grove Drive, Pasadena, CA 91109, USA. bshapiro@jpl.nasa.gov', 'United States|United States|United States|United States|United States', 0, 'Computer Graphics|Computer Simulation|Documentation|Models, Biological|Natural Language Processing|Signal Transduction|Software|Terminology as Topic|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg042', '12651737', 'Cellerator describes single and multi-cellular signal transduction networks (STN) with a compact, optionally palette-driven, arrow-based notation to represent biochemical reactions and transcriptional activation. Multi-compartment systems are represented as graphs with STNs embedded in each node. Interactions include mass-action, enzymatic, allosteric and connectionist models. Reactions are translated into differential equations and can be solved numerically to generate predictive time courses or output as systems of equations that can be read by other programs. Cellerator simulations are fully extensible and portable to any operating system that supports Mathematica, and can be indefinitely nested within larger data structures to produce highly scaleable models.'),
(70597, 2003, 'bio', 'Open bioinformatics', 'Jamison, D Curtis', 'Jet Propulsion Laboratory, California Institute of Technology, Mail Stop 126-347, 4800 Oak Grove Drive, Pasadena, CA 91109, USA. bshapiro@jpl.nasa.gov', 'United States', 9, 'Algorithms|Computational Biology|Database Management Systems|Databases, Factual|Hypermedia|Information Storage and Retrieval|Internet|Programming Languages|Software', 'Editorial', '10.1093/bioinformatics/btg214', '12691978', '-'),
(70598, 2003, 'bio', 'Genome-wide analysis of Bkm sequences (GATA repeats): predominant association with sex chromosomes and potential role in higher order chromatin organization and function', 'Subramanian, Subbaya|Mishra, Rakesh K|Singh, Lalji', 'Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad 500 007, India.|Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad 500 007, India.|Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad 500 007, India.', 'India|India|India', 0, 'Animals|Base Sequence|Biological Evolution|Bungarus|Chromatin|Chromosomes, Human, Y|Gene Expression Regulation|Genome, Human|Humans|Microsatellite Repeats|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Tandem Repeat Sequences|Y Chromosome', 'Comparative Study', '10.1093/bioinformatics/btg067', '12691979', 'Bkm (Banded krait minor) satellite DNA sequences (GATA repeats) have been shown to be associated with the sex determining chromosomes of various eukaryotes and have been implicated in the evolution and differentiation of sex chromosomes in snakes. The objective of the study is to analyze the GATA repeats of human genome specifically, the Y-chromosome, and other model organisms to understand the possible function and potential role in higher order chromatin organization.'),
(70599, 2003, 'bio', 'Directed indices for exploring gene expression data', 'LeBlanc, Michael|Kooperberg, Charles|Grogan, Thomas M|Miller, Thomas P', 'Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. mikel@crab.org|Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. mikel@crab.org|Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. mikel@crab.org|Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. mikel@crab.org', 'United States|United States|United States|United States', 0, 'Algorithms|Gene Expression Profiling|Genetic Testing|Humans|Lymphoma, Non-Hodgkin|Models, Genetic|Models, Statistical|Reproducibility of Results|Risk Assessment|Sensitivity and Specificity|Survival Analysis', 'Comparative Study', '10.1093/bioinformatics/btg079', '12691980', 'Large expression studies with clinical outcome data are becoming available for analysis. An important goal is to identify genes or clusters of genes where expression is related to patient outcome. While clustering methods are useful data exploration tools, they do not directly allow one to relate the expression data to clinical outcome. Alternatively, methods which rank genes based on their univariate significance do not incorporate gene function or relationships to genes that have been previously identified. In addition, after sifting through potentially thousands of genes, summary estimates (e.g. regression coefficients or error rates) algorithms should address the potentially large bias introduced by gene selection.'),
(70600, 2003, 'bio', 'Statistical tests for identifying differentially expressed genes in time-course microarray experiments', 'Park, Taesung|Yi, Sung-Gon|Lee, Seungmook|Lee, Seung Yeoun|Yoo, Dong-Hyun|Ahn, Jun-Ik|Lee, Yong-Sung', 'Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr|Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr|Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr|Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr|Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr|Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr|Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr', '-|-|-|-|-|-|-', 106, 'Algorithms|Amino Acid Sequence|Animals|Base Sequence|Cell Differentiation|Cerebral Cortex|Cluster Analysis|Gene Expression Profiling|Gene Expression Regulation, Developmental|Models, Genetic|Models, Statistical|Molecular Sequence Data|Nerve Tissue Proteins|Neurons|Oligonucleotide Array Sequence Analysis|Rats|Sequence Alignment|Stem Cells', 'Comparative Study', '10.1093/bioinformatics/btg068', '12691981', 'Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. In time-course experiments in which gene expression is monitored over time, we are interested in testing gene expression profiles for different experimental groups. However, no sophisticated analytic methods have yet been proposed to handle time-course experiment data.'),
(70601, 2003, 'bio', 'Computer simulation of the cellular arrangement using physical model in early cleavage of the nematode Caenorhabditis elegans', 'Kajita, Atsushi|Yamamura, Masayuki|Kohara, Yuji', 'Genome Biology Laboratory, National Institute of Genetics, 1111 Yata, Mishima, 411-8540, Japan. akajita@lab.nig.ac.jp|Genome Biology Laboratory, National Institute of Genetics, 1111 Yata, Mishima, 411-8540, Japan. akajita@lab.nig.ac.jp|Genome Biology Laboratory, National Institute of Genetics, 1111 Yata, Mishima, 411-8540, Japan. akajita@lab.nig.ac.jp', 'Japan|Japan|Japan', 0, 'Animals|Caenorhabditis elegans|Cell Communication|Cell Division|Computer Simulation|Models, Biological', 'Comparative Study', '10.1093/bioinformatics/btg069', '12691982', 'The ultimate goal of bioinformatics is to reconstruct biological systems in the computer. Since biological systems have many levels, it is important to focus on an appropriate level. In our first application of computer modeling to the early development of the nematode Caenorhabditis elegans, we focus on the cellular arrangement in early embryos. This plays a very important role in cell fate determination by cell-cell interaction, and is regarded as a system, one level higher than the system of gene regulation within cells. It is largely restricted by physical conditions that seemed feasible to model by computer.'),
(70602, 2003, 'bio', 'Evaluation of annotation strategies using an entire genome sequence', 'Iliopoulos, Ioannis|Tsoka, Sophia|Andrade, Miguel A|Enright, Anton J|Carroll, Mark|Poullet, Patrick|Promponas, Vassilis|Liakopoulos, Theodore|Palaios, Giorgos|Pasquier, Claude|Hamodrakas, Stavros|Tamames, Javier|Yagnik, Asutosh T|Tramontano, Anna|Devos, Damien|Blaschke, Christian|Valencia, Alfonso|Brett, David|Martin, David|Leroy, Christophe|Rigoutsos, Isidore|Sander, Chris|Ouzounis, Christos A', 'Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, 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|United Kingdom|', 54, 'Amino Acid Sequence|Bacterial Proteins|Chlamydia trachomatis|Database Management Systems|Databases, Genetic|Databases, Protein|Documentation|Gene Expression Profiling|Genome|Genome, Bacterial|Information Storage and Retrieval|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg077', '12691983', 'Genome-wide functional annotation either by manual or automatic means has raised considerable concerns regarding the accuracy of assignments and the reproducibility of methodologies. In addition, a performance evaluation of automated systems that attempt to tackle sequence analyses rapidly and reproducibly is generally missing. In order to quantify the accuracy and reproducibility of function assignments on a genome-wide scale, we have re-annotated the entire genome sequence of Chlamydia trachomatis (serovar D), in a collaborative manner.'),
(70603, 2003, 'bio', 'Automated generation and refinement of protein signatures: case study with G-protein coupled receptors', 'Sadowski, Michael I|Parish, John Howard', 'School of Biochemistry and Molecular Biology, The University of Leeds, Leeds LS2 9JT, UK.|School of Biochemistry and Molecular Biology, The University of Leeds, Leeds LS2 9JT, UK.', 'United Kingdom|United Kingdom', 9, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|GTP-Binding Proteins|Molecular Sequence Data|Protein Conformation|Protein Structure, Secondary|Receptors, Cell Surface|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg075', '12691984', 'Previous work had established that it was possible to derive sparse signatures (essentially sequence-length motifs) by examining points of contact between residues in proteins of known three-dimensional (3D) structure. Many interesting protein families have very little tertiary structural information. Methods for deriving signatures using only primary and secondary-structural information were therefore developed.'),
(70604, 2003, 'bio', 'Protein structure comparison by probability-based matching of secondary structure elements', 'Shih, Edward S C|Hwang, Ming-Jing', 'Institute of Biomedical Sciences, Academia Sinica, Taipei 11529, Taiwan.|Institute of Biomedical Sciences, Academia Sinica, Taipei 11529, Taiwan.', '-|-', 17, 'Algorithms|Amino Acid Sequence|Models, Molecular|Models, Statistical|Molecular Sequence Data|Protein Conformation|Protein Structure, Secondary|Proteins|Quality Control|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg058', '12691985', 'Protein structure comparison (PSC) has been used widely in studies of structural and functional genomics. However, PSC is computationally expensive and as a result almost all of the PSC methods currently in use look only for the optimal alignment and ignore many alternative alignments that are statistically significant and that may provide insight into protein evolution or folding.'),
(70605, 2003, 'bio', 'A segment alignment approach to protein comparison', 'Ye, Yuzhen|Jaroszewski, Lukasz|Li, Weizhong|Godzik, Adam', 'The Burnham Institute, La Jolla, CA 92037, USA.|The Burnham Institute, La Jolla, CA 92037, USA.|The Burnham Institute, La Jolla, CA 92037, USA.|The Burnham Institute, La Jolla, CA 92037, USA.', 'United States|United States|United States|United States', 24, 'Algorithms|Amino Acid Sequence|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Structure, Secondary|Proteins|Quality Control|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg073', '12691986', 'Local structure segments (LSSs) are small structural units shared by unrelated proteins. They are extensively used in protein structure comparison, and predicted LSSs (PLSSs) are used very successfully in ab initio folding simulations. However, predicted or real LSSs are rarely exploited by protein sequence comparison programs that are based on position-by-position alignments.'),
(70606, 2003, 'bio', 'Using multiple interdependency to separate functional from phylogenetic correlations in protein alignments', 'Tillier, Elisabeth R M|Lui, Thomas W H', 'Ontario Cancer Institute, University Health Network, Suite 703, 620 University Avenue, Toronto, Ontario, Canada M5G 2M9. e.tillier@utoronto.ca|Ontario Cancer Institute, University Health Network, Suite 703, 620 University Avenue, Toronto, Ontario, Canada M5G 2M9. e.tillier@utoronto.ca', 'Canada|Canada', 99, 'Algorithms|Amino Acid Sequence|Models, Molecular|Models, Statistical|Molecular Sequence Data|Phylogeny|Protein Conformation|Protein Structure, Secondary|Proteins|Quality Control|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg072', '12691987', 'Multiple sequence alignments of homologous proteins are useful for inferring their phylogenetic history and to reveal functionally important regions in the proteins. Functional constraints may lead to co-variation of two or more amino acids in the sequence, such that a substitution at one site is accompanied by compensatory substitutions at another site. It is not sufficient to find the statistical correlations between sites in the alignment because these may be the result of several undetermined causes. In particular, phylogenetic clustering will lead to many strong correlations.'),
(70607, 2003, 'bio', 'Construction of reliable protein-protein interaction networks with a new interaction generality measure', 'Saito, Rintaro|Suzuki, Harukazu|Hayashizaki, Yoshihide', 'Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center (GSC), Tsurumi-ku, Yokohama 230-0045, Japan. rgscerg@gsc.riken.go.jp|Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center (GSC), Tsurumi-ku, Yokohama 230-0045, Japan. rgscerg@gsc.riken.go.jp|Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center (GSC), Tsurumi-ku, Yokohama 230-0045, Japan. rgscerg@gsc.riken.go.jp', 'Japan|Japan|Japan', 95, 'Binding Sites|Databases, Protein|Fungal Proteins|Macromolecular Substances|Metabolism|Models, Biological|Models, Chemical|Models, Statistical|Principal Component Analysis|Protein Binding|Protein Interaction Mapping|Proteins|Reproducibility of Results|Sensitivity and Specificity|Yeasts', 'Comparative Study', '10.1093/bioinformatics/btg070', '12691988', 'Recent screening techniques have made large amounts of protein-protein interaction data available, from which biologically important information such as the function of uncharacterized proteins, the existence of novel protein complexes, and novel signal-transduction pathways can be discovered. However, experimental data on protein interactions contain many false positives, making these discoveries difficult. Therefore computational methods of assessing the reliability of each candidate protein-protein interaction are urgently needed.'),
(70608, 2003, 'bio', 'Feature selection and transduction for prediction of molecular bioactivity for drug design', 'Weston, Jason|Pérez-Cruz, Fernando|Bousquet, Olivier|Chapelle, Olivier|Elisseeff, André|Schölkopf, Bernhard', 'Max Planck Institute, Spemannstr. 38, Tuebingen, 72076, Germany. jason.weston@tuebingen.mpg.de|Max Planck Institute, Spemannstr. 38, Tuebingen, 72076, Germany. jason.weston@tuebingen.mpg.de|Max Planck Institute, Spemannstr. 38, Tuebingen, 72076, Germany. jason.weston@tuebingen.mpg.de|Max Planck Institute, Spemannstr. 38, Tuebingen, 72076, Germany. jason.weston@tuebingen.mpg.de|Max Planck Institute, Spemannstr. 38, Tuebingen, 72076, Germany. jason.weston@tuebingen.mpg.de|Max Planck Institute, Spemannstr. 38, Tuebingen, 72076, Germany. jason.weston@tuebingen.mpg.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Artificial Intelligence|Binding Sites|Databases, Protein|Drug Design|Macromolecular Substances|Models, Biological|Models, Chemical|Models, Statistical|Pattern Recognition, Automated|Principal Component Analysis|Protein Binding|Protein Interaction Mapping|Proteins|Receptors, Drug|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg054', '12691989', 'In drug discovery a key task is to identify characteristics that separate active (binding) compounds from inactive (non-binding) ones. An automated prediction system can help reduce resources necessary to carry out this task.'),
(70609, 2003, 'bio', 'Client-server environment for high-performance gene expression data analysis', 'Sturn, Alexander|Mlecnik, Bernhard|Pieler, Roland|Rainer, Johannes|Truskaller, Thomas|Trajanoski, Zlatko', 'Institute of Biomedical Engineering, Graz University of Technology, Christian Doppler Laboratory for Genomics and Bioinformatics, Krenngasse 37, 8010 Graz, Austria.|Institute of Biomedical Engineering, Graz University of Technology, Christian Doppler Laboratory for Genomics and Bioinformatics, Krenngasse 37, 8010 Graz, Austria.|Institute of Biomedical Engineering, Graz University of Technology, Christian Doppler Laboratory for Genomics and Bioinformatics, Krenngasse 37, 8010 Graz, Austria.|Institute of Biomedical Engineering, Graz University of Technology, Christian Doppler Laboratory for Genomics and Bioinformatics, Krenngasse 37, 8010 Graz, Austria.|Institute of Biomedical Engineering, Graz University of Technology, Christian Doppler Laboratory for Genomics and Bioinformatics, Krenngasse 37, 8010 Graz, Austria.|Institute of Biomedical Engineering, Graz University of Technology, Christian Doppler Laboratory for Genomics and Bioinformatics, Krenngasse 37, 8010 Graz, Austria.', 'Austria|Austria|Austria|Austria|Austria|Austria', 17, 'Computing Methodologies|Gene Expression Profiling|Hypermedia|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btg074', '12691990', 'We have developed a platform independent, flexible and scalable Java environment for high-performance large-scale gene expression data analysis, which integrates various computational intensive hierarchical and non-hierarchical clustering algorithms. The environment includes a powerful client for data preparation and results visualization, an application server for computation and an additional administration tool. The package is available free of charge for academic and non-profit institutions.'),
(70610, 2003, 'bio', 'GAAS: gene array analyzer software for management, analysis and visualization of gene expression data', 'Masseroli, M|Cerveri, P|Pelicci, P G|Alcalay, M', 'Bioengineering Department, Politecnico di Milano, I-20133 Milano, Italy. masseroli@biomed.polimi.it|Bioengineering Department, Politecnico di Milano, I-20133 Milano, Italy. masseroli@biomed.polimi.it|Bioengineering Department, Politecnico di Milano, I-20133 Milano, Italy. masseroli@biomed.polimi.it|Bioengineering Department, Politecnico di Milano, I-20133 Milano, Italy. masseroli@biomed.polimi.it', 'Italy|Italy|Italy|Italy', 3, 'Algorithms|Database Management Systems|Gene Expression Profiling|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg071', '12691991', 'GAAS, Gene Array Analyzer Software supports multi-user efficient management and suitable analyses of large amounts of gene expression data across replicated experiments. Its management framework handles input data generated by different technologies. A multi-user environment allows each user to store his/her own data visualization scheme, analysis parameters used, values and formats of the output data. The analysis engine performs: background and spot quality evaluation, data normalization, differential gene expression analyses in single and multiple replica experiments. Results of expression profiles can be interactively navigated through graphical interfaces and stored into output databases.'),
(70611, 2003, 'bio', 'AFLPinSilico, simulating AFLP fingerprints', 'Rombauts, Stephane|Van De Peer, Yves|Rouzé, Pierre', 'Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), K.L. Ledeganckstraat 35, Gent 9000, Belgium. strom@gengenp.rug.ac.be|Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), K.L. Ledeganckstraat 35, Gent 9000, Belgium. strom@gengenp.rug.ac.be|Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), K.L. Ledeganckstraat 35, Gent 9000, Belgium. strom@gengenp.rug.ac.be', 'Belgium|Belgium|Belgium', 13, 'Algorithms|Arabidopsis|Base Sequence|Chromosomes, Artificial, Bacterial|Computer Simulation|DNA Fingerprinting|Molecular Sequence Data|Polymorphism, Restriction Fragment Length|Random Amplified Polymorphic DNA Technique|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btg090', '12691992', 'A drawback of the Amplified Fragment Length Polymorphism (AFLP) fingerprinting method is the difficulty to correlate the different fragments with their DNA sequence. The AFLPinSilico application presented here simulates AFLP experiments run on either cDNA or genomic sequences, producing virtual fingerprints that allow high throughput identification of AFLP fragments. The program also enables biologists to manage experiments through simulations done beforehand, thereby reducing the number of experiments that have to be run. AFLPinSilico is available through the www or as a stand-alone version, through a command line executable (available upon request, for any platform running PERL).'),
(70612, 2003, 'bio', 'PGAGENE: integrating quantitative gene-specific results from the NHLBI programs for genomic applications', 'Lee, Kyungjoon|Kohane, Isaac S|Butte, Atul J', 'Childrens Hospital Informatics Program, 300 Longwood Ave, Boston, MA 02115, USA.|Childrens Hospital Informatics Program, 300 Longwood Ave, Boston, MA 02115, USA.|Childrens Hospital Informatics Program, 300 Longwood Ave, Boston, MA 02115, USA.', 'United States|United States|United States', 1, 'Base Sequence|Cooperative Behavior|Database Management Systems|Databases, Nucleic Acid|Gene Expression Profiling|Genomics|Information Storage and Retrieval|Interinstitutional Relations|Internet|Molecular Sequence Data|National Institutes of Health (U.S.)|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|United States', 'Journal Article', '10.1093/bioinformatics/btg066', '12691993', 'PGAGENE is a web-based gene-specific genomic data search engine, which allows users to search over 5.9 million pieces of collective genetic and genomic data from the NHLBI supported Programs for Genomic Applications. This data includes microarray measurements, SNPs, and mutations, and data may be found using symbols, parts of gene names or products, Affymetrix probe IDs, GenBank accession numbers, UniGene IDs, dbSNP IDs, and others. The PGAGENE indexing agent periodically maps all publicly available gene-specific PGA data onto LocusLink using dynamically generated cross-referencing tables.'),
(70613, 2003, 'bio', 'Perfect phylogeny haplotyper: haplotype inferral using a tree model', 'Chung, Ren Hua|Gusfield, Dan', 'Department of Computer Science, 3051 Engineering II, University of California, One Shields Avenue, Davis, CA 95616, USA.|Department of Computer Science, 3051 Engineering II, University of California, One Shields Avenue, Davis, CA 95616, USA.', 'United States|United States', 27, 'Algorithms|Gene Expression Profiling|Genetic Variation|Haplotypes|Internet|Models, Genetic|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btg078', '12691994', 'We have developed an efficient program, the Perfect Phylogeny Haplotyper (PPH) that takes in unphased population genotype data, and determines if that data can be explained by haplotype pairs that could have evolved on a perfect phylogeny.'),
(70614, 2003, 'bio', 'Phylogenetic web profiler', 'Wong, Philip|Kolesov, Grigory|Frishman, Dmitrij|Houry, Walid A', 'Department of Biochemistry, University of Toronto, Medical Sciences Building, 1 Kings College Circle, Toronto, ON M5S 1A8, Canada.|Department of Biochemistry, University of Toronto, Medical Sciences Building, 1 Kings College Circle, Toronto, ON M5S 1A8, Canada.|Department of Biochemistry, University of Toronto, Medical Sciences Building, 1 Kings College Circle, Toronto, ON M5S 1A8, Canada.|Department of Biochemistry, University of Toronto, Medical Sciences Building, 1 Kings College Circle, Toronto, ON M5S 1A8, Canada.', 'Canada|Canada|Canada|Canada', 1, 'Amino Acid Sequence|Evolution, Molecular|Gene Expression Profiling|Genetic Variation|Internet|Molecular Sequence Data|Phylogeny|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btg064', '12691995', 'Phylogenetic Web Profiler (PWP) is a web-based service designed to perform phylogenetic profiling of proteins against genomes. The current version offers a selection of 63 completed genomes and available plasmids as annotated in the PEDANT genome database. Unlike currently available applications, this tool offers several choices of ortholog prediction parameters including E-value cutoff, percent length difference tolerance, and annotation similarity. Additional features include tight integration with the PEDANT database and tools to analyze properties of predicted proteins. PWP should prove very useful for the analysis of functional-linkage between proteins.'),
(70615, 2003, 'bio', 'EPPS: mining the COG database by an extended phylogenetic patterns search', 'Reichard, Klaus|Kaufmann, Michael', 'Institute of Mathematics, AG Statistics Institute of Neurobiochemistry, AG Proteinchemistry, University of Witten/Herdecke, Stockumer Str. 10, 58448 Witten, Germany.|Institute of Mathematics, AG Statistics Institute of Neurobiochemistry, AG Proteinchemistry, University of Witten/Herdecke, Stockumer Str. 10, 58448 Witten, Germany.', 'Germany|Germany', 12, 'Amino Acid Sequence|Cluster Analysis|Conserved Sequence|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Phylogeny|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1093/bioinformatics/btg089', '12691996', 'EPPS runs under Microsoft Windows. It is an extended version of the phylogenetic patterns search (PPS). The output condition of PPS is the exact match of a user defined phylogenetic pattern with the pattern represented by the respective cluster of orthologous groups (COG). In contrast, the software described here is less restrictive. The user may define the accuracy of the search by the number of genomes that are allowed not to match the predefined phylogenetic pattern. Thus, EPPS has the advantage to detect COGs even if organisms defined to be included are not or organisms defined to be excluded are present in the output COGs.'),
(70616, 2003, 'bio', 'Java editor for biological pathways', 'Trost, Elmar|Hackl, Hubert|Maurer, Michael|Trajanoski, Zlatko', 'Institute of Biomedical Engineering and Christian Doppler Laboratory for Genomics and Bioinformatics, Graz University of Technology, Krenngasse 37, 8010 Graz, Austria.|Institute of Biomedical Engineering and Christian Doppler Laboratory for Genomics and Bioinformatics, Graz University of Technology, Krenngasse 37, 8010 Graz, Austria.|Institute of Biomedical Engineering and Christian Doppler Laboratory for Genomics and Bioinformatics, Graz University of Technology, Krenngasse 37, 8010 Graz, Austria.|Institute of Biomedical Engineering and Christian Doppler Laboratory for Genomics and Bioinformatics, Graz University of Technology, Krenngasse 37, 8010 Graz, Austria.', 'Austria|Austria|Austria|Austria', 11, 'Documentation|Hypermedia|Internet|Metabolism|Models, Biological|Proteins|Software|Terminology as Topic|User-Computer Interface|Vocabulary, Controlled|Word Processing', 'Journal Article', '10.1093/bioinformatics/btg052', '12691997', 'A visual Java-based tool for drawing and annotating biological pathways was developed. This tool integrates the possibilities of charting elements with different attributes (size, color, labels), drawing connections between elements in distinct characteristics (color, structure, width, arrows), as well as adding links to molecular biology databases, promoter sequences, information on the function of the genes or gene products, and references. It is easy to use and system independent. The result of the editing process is a PNG (portable network graphics) file for the images and XML (extended markup language) file for the appropriate links.'),
(70617, 2003, 'bio', 'GoFish finds genes with combinations of Gene Ontology attributes', 'Berriz, Gabriel F|White, James V|King, Oliver D|Roth, Frederick P', 'Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology, 250 Longwood Avenue, Boston, MA 02115, USA.|Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology, 250 Longwood Avenue, Boston, MA 02115, USA.|Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology, 250 Longwood Avenue, Boston, MA 02115, USA.|Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology, 250 Longwood Avenue, Boston, MA 02115, USA.', 'United States|United States|United States|United States', 14, 'Amino Acid Sequence|Gene Expression Profiling|Hypermedia|Molecular Sequence Data|Phylogeny|Proteomics|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg088', '12691998', 'GoFish is a Java application that allows users to search for gene products with particular gene ontology (GO) attributes, or combinations of attributes. GoFish ranks gene products by the degree to which they satisfy a Boolean query. Four organisms are currently supported: Saccaromyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and M.musculus.'),
(70618, 2003, 'bio', 'RECSIM and INDSTATS: probabilities of identity in general genealogies', 'Dimitropoulou, Polixeni|Cannings, Chris', 'Division of Genomic Medicine, University of Sheffield, UK.|Division of Genomic Medicine, University of Sheffield, UK.', 'United Kingdom|United Kingdom', 0, 'Chromosome Mapping|Chromosomes, Human|Female|Gene Expression Profiling|Genetic Variation|Human Genome Project|Humans|Male|Models, Genetic|Models, Statistical|Pedigree|Recombination, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg060', '12691999', 'RECSIM takes a general genealogy and simulates the transmission of chromosomes through that genealogy. INDSTATS extracts some basic statistics from the output of RECSIM.'),
(70619, 2003, 'bio', 'Interpreting peptide mass spectra by VEMS', 'Matthiesen, R|Lundsgaard, M|Welinder, K G|Bauw, G', 'Department of Biotechnology, Aalborg University, Sohngaardsholmsvej 49, DK-9000 Aalborg, Denmark. rm@bio.auc.dk|Department of Biotechnology, Aalborg University, Sohngaardsholmsvej 49, DK-9000 Aalborg, Denmark. rm@bio.auc.dk|Department of Biotechnology, Aalborg University, Sohngaardsholmsvej 49, DK-9000 Aalborg, Denmark. rm@bio.auc.dk|Department of Biotechnology, Aalborg University, Sohngaardsholmsvej 49, DK-9000 Aalborg, Denmark. rm@bio.auc.dk', 'Denmark|Denmark|Denmark|Denmark', 18, 'Databases, Bibliographic|Databases, Protein|Information Storage and Retrieval|Mass Spectrometry|Molecular Weight|Peptides|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btg059', '12692000', 'Most existing Mass Spectra (MS) analysis programs are automatic and provide limited opportunity for editing during the interpretation. Furthermore, they rely entirely on publicly available databases for interpretation. VEMS (Virtual Expert Mass Spectrometrist) is a program for interactive analysis of peptide MS/MS spectra imported in text file format. Peaks are annotated, the monoisotopic peaks retained, and the b-and y-ion series identified in an interactive manner. The called peptide sequence is searched against a local protein database for sequence identity and peptide mass. The report compares the calculated and the experimental mass spectrum of the called peptide. The program package includes four accessory programs. VEMStrans creates protein databases in FASTA format from EST or cDNA sequence files. VEMSdata creates a virtual peptide database from FASTA files. VEMSdist displays the distribution of masses up to 5000 Da. VEMSmaldi searches singly charged peptide masses against the local database.'),
(70620, 2003, 'bio', 'Meta, Meta(N) and cyber servers', 'Valencia, Alfonso', 'Department of Biotechnology, Aalborg University, Sohngaardsholmsvej 49, DK-9000 Aalborg, Denmark. rm@bio.auc.dk', 'Denmark', 5, 'Computers|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Protein Conformation|Proteins|Sequence Analysis, Protein', 'Editorial', '10.1093/bioinformatics/btg215', '12724287', '-'),
(70621, 2003, 'bio', 'Selection of oligonucleotide probes for protein coding sequences', 'Wang, Xiaowei|Seed, Brian', 'Department of Molecular Biology, 50 Blossom Street, Massachusetts General Hospital, Boston 02114, USA.|Department of Molecular Biology, 50 Blossom Street, Massachusetts General Hospital, Boston 02114, USA.', 'United States|United States', 0, 'Algorithms|Animals|Cluster Analysis|Contig Mapping|DNA Probes|Gene Expression Profiling|Genome, Human|Humans|Mice|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg086', '12724288', 'Large arrays of oligonucleotide probes have become popular tools for analyzing RNA expression. However to date most oligo collections contain poorly validated sequences or are biased toward untranslated regions (UTRs). Here we present a strategy for picking oligos for microarrays that focus on a design universe consisting exclusively of protein coding regions. We describe the constraints in oligo design that are imposed by this strategy, as well as a software tool that allows the strategy to be applied broadly.'),
(70622, 2003, 'bio', 'Statistical design of reverse dye microarrays', 'Dobbin, K|Shih, J H|Simon, R', 'National Cancer Institute, Biometric Research Branch, 6130 Executive Blvd., MSC 7434, Bethesda, MD 20892, USA. dobbinke@mail.nih.gov|National Cancer Institute, Biometric Research Branch, 6130 Executive Blvd., MSC 7434, Bethesda, MD 20892, USA. dobbinke@mail.nih.gov|National Cancer Institute, Biometric Research Branch, 6130 Executive Blvd., MSC 7434, Bethesda, MD 20892, USA. dobbinke@mail.nih.gov', 'United States|United States|United States', 91, 'Algorithms|Artifacts|Carbocyanines|Cluster Analysis|Computer-Aided Design|Equipment Design|Equipment Failure Analysis|Fluorescent Dyes|Models, Statistical|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Sequence Analysis, DNA|Staining and Labeling', 'Comparative Study', '10.1093/bioinformatics/btg076', '12724289', 'In cDNA microarray experiments all samples are labelled with either Cy3 dye or Cy5 dye. Certain genes exhibit dye bias-a tendency to bind more efficiently to one of the dyes. The common reference design avoids the problem of dye bias by running all arrays forward, so that the samples being compared are always labelled with the same dye. But comparison of samples labelled with different dyes is sometimes of interest. In these situations, it is necessary to run some arrays reverse-with the dye labelling reversed-in order to correct for the dye bias. The design of these experiments will impact ones ability to identify genes that are differentially expressed in different tissues or conditions. We address the design issue of how many specimens are needed, how many forward and reverse labelled arrays to perform, and how to optimally assign Cy3 and Cy5 labels to the specimens.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70623, 2003, 'bio', 'SamCluster: an integrated scheme for automatic discovery of sample classes using gene expression profile', 'Li, Wuju|Fan, Ming|Xiong, Momiao', 'Beijing Institute of Basic Medical Sciences, PO Box 130(3), Peoples Republic of China. wujuli@yahoo.com|Beijing Institute of Basic Medical Sciences, PO Box 130(3), Peoples Republic of China. wujuli@yahoo.com|Beijing Institute of Basic Medical Sciences, PO Box 130(3), Peoples Republic of China. wujuli@yahoo.com', 'China|China|China', 14, 'Algorithms|Animals|Cluster Analysis|Colonic Neoplasms|Consensus Sequence|Female|Gene Expression Profiling|Humans|Leukemia|Neoplasms|Oligonucleotide Array Sequence Analysis|Ovarian Neoplasms|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software|Systems Integration', 'Comparative Study', '10.1093/bioinformatics/btg095', '12724290', 'Feature (gene) selection can dramatically improve the accuracy of gene expression profile based sample class prediction. Many statistical methods for feature (gene) selection such as stepwise optimization and Monte Carlo simulation have been developed for tissue sample classification. In contrast to class prediction, few statistical and computational methods for feature selection have been applied to clustering algorithms for pattern discovery.'),
(70624, 2003, 'bio', 'Robust cluster analysis of microarray gene expression data with the number of clusters determined biologically', 'Bickel, David R', 'Medical College of Georgia, Office of Biostatistics and Bioinformatics, 1120 Fifteenth St, AE-3037 Augusta 30912-4900, USA. dbickel@mail.mcg.edu', 'Georgia', 39, 'Algorithms|Base Sequence|Cluster Analysis|Electron Transport Complex III|Electron Transport Complex IV|Gene Expression Profiling|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Quality Control|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg092', '12724291', 'The success of each method of cluster analysis depends on how well its underlying model describes the patterns of expression. Outlier-resistant and distribution-insensitive clustering of genes are robust against violations of model assumptions.'),
(70625, 2003, 'bio', 'Non-linear normalization and background correction in one-channel cDNA microarray studies', 'Edwards, David', 'Department of Biostatistics, Novo Nordisk, Bagsvaerd, Denmark. DEd@novonordisk.com', 'Denmark', 111, 'Adipose Tissue|Animals|Artifacts|Carbocyanines|Gene Expression Profiling|Male|Mice|Models, Genetic|Models, Statistical|Nonlinear Dynamics|Oligonucleotide Array Sequence Analysis|Quality Control|RNA|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/btg083', '12724292', 'Data from one-channel cDNA microarray studies may exhibit poor reproducibility due to spatial heterogeneity, non-linear array-to-array variation and problems in correcting for background. Uncorrected, these phenomena can give rise to misleading conclusions.'),
(70626, 2003, 'bio', 'Gene selection and clustering for time-course and dose-response microarray experiments using order-restricted inference', 'Peddada, Shyamal D|Lobenhofer, Edward K|Li, Leping|Afshari, Cynthia A|Weinberg, Clarice R|Umbach, David M', 'Biostatistics Branch, Laboratory of Molecular Carcinogenesis, Research Triangle Park, NC 27709, USA. peddada@embryo.niehs.nih.gov|Biostatistics Branch, Laboratory of Molecular Carcinogenesis, Research Triangle Park, NC 27709, USA. peddada@embryo.niehs.nih.gov|Biostatistics Branch, Laboratory of Molecular Carcinogenesis, Research Triangle Park, NC 27709, USA. peddada@embryo.niehs.nih.gov|Biostatistics Branch, Laboratory of Molecular Carcinogenesis, Research Triangle Park, NC 27709, USA. peddada@embryo.niehs.nih.gov|Biostatistics Branch, Laboratory of Molecular Carcinogenesis, Research Triangle Park, NC 27709, USA. peddada@embryo.niehs.nih.gov|Biostatistics Branch, Laboratory of Molecular Carcinogenesis, Research Triangle Park, NC 27709, USA. peddada@embryo.niehs.nih.gov', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Breast Neoplasms|Cell Line, Tumor|Cluster Analysis|Computer Simulation|Dose-Response Relationship, Drug|Estradiol|Gene Expression Profiling|Humans|Models, Genetic|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Statistics as Topic|Time Factors|Transcription, Genetic', 'Comparative Study', '10.1093/bioinformatics/btg093', '12724293', 'We propose an algorithm for selecting and clustering genes according to their time-course or dose-response profiles using gene expression data. The proposed algorithm is based on the order-restricted inference methodology developed in statistics. We describe the methodology for time-course experiments although it is applicable to any ordered set of treatments. Candidate temporal profiles are defined in terms of inequalities among mean expression levels at the time points. The proposed algorithm selects genes when they meet a bootstrap-based criterion for statistical significance and assigns each selected gene to the best fitting candidate profile. We illustrate the methodology using data from a cDNA microarray experiment in which a breast cancer cell line was stimulated with estrogen for different time intervals. In this example, our method was able to identify several biologically interesting genes that previous analyses failed to reveal.'),
(70627, 2003, 'bio', 'Reconstructing the temporal ordering of biological samples using microarray data', 'Magwene, Paul M|Lizardi, Paul|Kim, Junhyong', 'Department of Ecology and Evolutionary Biology, Yale University School of Medicine, New Haven, CT, USA.|Department of Ecology and Evolutionary Biology, Yale University School of Medicine, New Haven, CT, USA.|Department of Ecology and Evolutionary Biology, Yale University School of Medicine, New Haven, CT, USA.', 'United States|United States|United States', 57, 'Algorithms|Caulobacter crescentus|Computer Simulation|Gene Expression Profiling|Models, Genetic|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Sample Size|Sequence Analysis, DNA|Time Factors|Transcription, Genetic', 'Comparative Study', '10.1093/bioinformatics/btg081', '12724294', 'Accurate time series for biological processes are difficult to estimate due to problems of synchronization, temporal sampling and rate heterogeneity. Methods are needed that can utilize multi-dimensional data, such as those resulting from DNA microarray experiments, in order to reconstruct time series from unordered or poorly ordered sets of observations.'),
(70628, 2003, 'bio', 'ALES: cell lineage analysis and mapping of developmental events', 'Braun, V|Azevedo, R B R|Gumbel, M|Agapow, P-M|Leroi, A M|Meinzer, H-P', 'Division of Medical and Biological Informatics, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Germany. CellO@dkfz-heidelberg.de|Division of Medical and Biological Informatics, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Germany. CellO@dkfz-heidelberg.de|Division of Medical and Biological Informatics, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Germany. CellO@dkfz-heidelberg.de|Division of Medical and Biological Informatics, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Germany. CellO@dkfz-heidelberg.de|Division of Medical and Biological Informatics, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Germany. CellO@dkfz-heidelberg.de|Division of Medical and Biological Informatics, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Germany. CellO@dkfz-heidelberg.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 4, 'Algorithms|Animals|Biological Evolution|Caenorhabditis elegans|Cell Differentiation|Cell Lineage|Computer Simulation|Database Management Systems|Documentation|Information Storage and Retrieval|Models, Biological|Neurons|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg087', '12724295', 'Animals build their bodies by altering the fates of cells. The way in which they do so is reflected in the topology of cell lineages and the fates of terminal cells. Cell lineages should, therefore, contain information about the molecular events that determined them. Here we introduce new tools for visualizing, manipulating, and extracting the information contained in cell lineages. Our tools enable us to analyze very large cell lineages, where previously analyses have only been carried out on cell lineages no larger than a few dozen cells.'),
(70629, 2003, 'bio', 'MuGeN: simultaneous exploration of multiple genomes and computer analysis results', 'Hoebeke, Mark|Nicolas, Pierre|Bessières, Philippe', 'Unité Mathématique, Informatique & Génome - INRA - Domaine de Vilvert - F 78352 Jouy en Josas CEDEX, France. mark.hoebeke@jouy.inra.fr|Unité Mathématique, Informatique & Génome - INRA - Domaine de Vilvert - F 78352 Jouy en Josas CEDEX, France. mark.hoebeke@jouy.inra.fr|Unité Mathématique, Informatique & Génome - INRA - Domaine de Vilvert - F 78352 Jouy en Josas CEDEX, France. mark.hoebeke@jouy.inra.fr', 'France|France|France', 13, 'Computer Graphics|Database Management Systems|Documentation|Gene Expression Profiling|Genome|Information Storage and Retrieval|Internet|Online Systems|Programming Languages|Sequence Analysis, DNA|Software|Software Design|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg101', '12724296', 'The availability of increasing amounts of sequence data about completely sequenced genomes spurs the development of new methods in the fields of automated annotation, and of comparative genomics. Tools allowing the visualization of results produced by analysis methods, superimposed on possibly annotated sequence data, and enabling synchronized navigation in multiple genomes, provide new means for interactive genome exploration. This kind of visual inspection can be used as a basis to assess the quality of new analysis algorithms, or to discover genome portions to be subjected to in-depth studies.'),
(70630, 2003, 'bio', 'A search for H/ACA snoRNAs in yeast using MFE secondary structure prediction', 'Edvardsson, Sverker|Gardner, Paul P|Poole, Anthony M|Hendy, Michael D|Penny, David|Moulton, Vincent', 'Department of Information Technology, Mid Sweden University, S-851 70, Sundsvall, Sweden.|Department of Information Technology, Mid Sweden University, S-851 70, Sundsvall, Sweden.|Department of Information Technology, Mid Sweden University, S-851 70, Sundsvall, Sweden.|Department of Information Technology, Mid Sweden University, S-851 70, Sundsvall, Sweden.|Department of Information Technology, Mid Sweden University, S-851 70, Sundsvall, Sweden.|Department of Information Technology, Mid Sweden University, S-851 70, Sundsvall, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 0, 'Algorithms|Base Sequence|Conserved Sequence|Databases, Nucleic Acid|Energy Transfer|Genome, Fungal|Molecular Sequence Data|Nucleic Acid Conformation|RNA, Small Nucleolar|Saccharomyces cerevisiae|Sequence Alignment|Sequence Analysis, RNA', 'Comparative Study', '10.1093/bioinformatics/btg080', '12724297', 'Noncoding RNA genes produce functional RNA molecules rather than coding for proteins. One such family is the H/ACA snoRNAs. Unlike the related C/D snoRNAs these have resisted automated detection to date.'),
(70631, 2003, 'bio', 'Improvement of the GenTHREADER method for genomic fold recognition', 'McGuffin, Liam J|Jones, David T', 'Bioinformatics Group, Department of Computer Science, University College London, Gower Street, UK. l.mcguffin@cs.ucl.ac.uk|Bioinformatics Group, Department of Computer Science, University College London, Gower Street, UK. l.mcguffin@cs.ucl.ac.uk', 'United Kingdom|United Kingdom', 292, 'Amino Acid Sequence|Animals|Databases, Protein|False Positive Reactions|Genome|Molecular Sequence Data|Protein Folding|Protein Structure, Secondary|Proteins|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology|Software', 'Comparative Study', '10.1093/bioinformatics/btg097', '12724298', 'In order to enhance genome annotation, the fully automatic fold recognition method GenTHREADER has been improved and benchmarked. The previous version of GenTHREADER consisted of a simple neural network which was trained to combine sequence alignment score, length information and energy potentials derived from threading into a single score representing the relationship between two proteins, as designated by CATH. The improved version incorporates PSI-BLAST searches, which have been jumpstarted with structural alignment profiles from FSSP, and now also makes use of PSIPRED predicted secondary structure and bi-directional scoring in order to calculate the final alignment score. Pairwise potentials and solvation potentials are calculated from the given sequence alignment which are then used as inputs to a multi-layer, feed-forward neural network, along with the alignment score, alignment length and sequence length. The neural network has also been expanded to accommodate the secondary structure element alignment (SSEA) score as an extra input and it is now trained to learn the FSSP Z-score as a measurement of similarity between two proteins.'),
(70632, 2003, 'bio', 'Towards optimal views of proteins', 'Sverud, Oscar|MacCallum, Robert M', 'Stockholm Bioinformatics Center, Stockholm University, Sweden.|Stockholm Bioinformatics Center, Stockholm University, Sweden.', 'Sweden|Sweden', 2, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Protein|Image Interpretation, Computer-Assisted|Imaging, Three-Dimensional|Models, Molecular|Neural Networks (Computer)|Observer Variation|Protein Conformation|Proteins|Quality Control|Rotation|Staphylococcal Protein A|Surveys and Questionnaires|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg100', '12724299', 'Graphical representations of proteins in online databases generally give default views orthogonal to the PDB file coordinate system. These views are often uninformative in terms of protein structure and/or function. Here we discuss the development of a simple automatic algorithm to provide a good view of a protein domain with respect to its structural features.'),
(70633, 2003, 'bio', 'R/qtl: QTL mapping in experimental crosses', 'Broman, Karl W|Wu, Hao|Sen, Saunak|Churchill, Gary A', 'Department of Biostatistics, Johns Hopkins University, 615 N. Wolfe St, Baltimore, MD 21205, USA. kbroman@jhsph.edu|Department of Biostatistics, Johns Hopkins University, 615 N. Wolfe St, Baltimore, MD 21205, USA. kbroman@jhsph.edu|Department of Biostatistics, Johns Hopkins University, 615 N. Wolfe St, Baltimore, MD 21205, USA. kbroman@jhsph.edu|Department of Biostatistics, Johns Hopkins University, 615 N. Wolfe St, Baltimore, MD 21205, USA. kbroman@jhsph.edu', 'United States|United States|United States|United States', 1813, 'Algorithms|Chromosome Mapping|Chromosomes, Human, Pair 1|Crosses, Genetic|Gene Expression Profiling|Genetic Markers|Genome|Genotype|Humans|Inbreeding|Markov Chains|Models, Genetic|Models, Statistical|Quantitative Trait Loci|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg112', '12724300', 'R/qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental populations derived from inbred lines. It is implemented as an add-on package for the freely-available statistical software, R, and includes functions for estimating genetic maps, identifying genotyping errors, and performing single-QTL and two-dimensional, two-QTL genome scans by multiple methods, with the possible inclusion of covariates.'),
(70634, 2003, 'bio', 'GeneMerge--post-genomic analysis, data mining, and hypothesis testing', 'Castillo-Davis, Cristian I|Hartl, Daniel L', 'Department of Organismic and Evolutionary Biology, Harvard University, Biological Laboratories, 16 Divinity Avenue, Cambridge, MA 02138, USA. ccastillo-davis@oeb.harvard.edu|Department of Organismic and Evolutionary Biology, Harvard University, Biological Laboratories, 16 Divinity Avenue, Cambridge, MA 02138, USA. ccastillo-davis@oeb.harvard.edu', 'United States|United States', 0, 'Algorithms|Database Management Systems|Gene Expression Profiling|Genetics, Population|Genome|Information Storage and Retrieval|Models, Genetic|Models, Statistical|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btg114', '12724301', 'GeneMerge is a web-based and standalone program written in PERL that returns a range of functional and genomic data for a given set of study genes and provides statistical rank scores for over-representation of particular functions or categories in the data set. Functional or categorical data of all kinds can be analyzed with GeneMerge, facilitating regulatory and metabolic pathway analysis, tests of population genetic hypotheses, cross-experiment comparisons, and tests of chromosomal clustering, among others. GeneMerge can perform analyses on a wide variety of genomic data quickly and easily and facilitates both data mining and hypothesis testing.'),
(70635, 2003, 'bio', 'MARAN: normalizing micro-array data', 'Engelen, Kristof|Coessens, Bert|Marchal, Kathleen|De Moor, Bart', 'ESAT-SCD, KULeuven, Kasteelpark Arenberg 10, Belgium. kristof.engelen@esat.kuleuven.ac.be|ESAT-SCD, KULeuven, Kasteelpark Arenberg 10, Belgium. kristof.engelen@esat.kuleuven.ac.be|ESAT-SCD, KULeuven, Kasteelpark Arenberg 10, Belgium. kristof.engelen@esat.kuleuven.ac.be|ESAT-SCD, KULeuven, Kasteelpark Arenberg 10, Belgium. kristof.engelen@esat.kuleuven.ac.be', 'Belgium|Belgium|Belgium|Belgium', 0, 'Algorithms|Gene Expression Profiling|Internet|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg085', '12724302', 'MARAN is a web-based application for normalizing microarray data. MARAN comprises a generic ANOVA model, an option for Loess fitting prior to ANOVA analysis, and a module for selecting genes with significantly changing expression.'),
(70636, 2003, 'bio', 'Do current sequence analysis algorithms disclose multifunctional (moonlighting) proteins?', 'Gómez, Antonio|Domedel, Nuria|Cedano, Juan|Piñol, Jaume|Querol, Enrique', 'Institut de Biotecnologia i Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona. 08193 Bellaterra, Spain. enric.querol@uab.es|Institut de Biotecnologia i Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona. 08193 Bellaterra, Spain. enric.querol@uab.es|Institut de Biotecnologia i Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona. 08193 Bellaterra, Spain. enric.querol@uab.es|Institut de Biotecnologia i Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona. 08193 Bellaterra, Spain. enric.querol@uab.es|Institut de Biotecnologia i Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona. 08193 Bellaterra, Spain. enric.querol@uab.es', 'Spain|Spain|Spain|Spain|Spain', 37, 'Algorithms|Databases, Protein|Protein Conformation|Proteins|Proteomics|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg111', '12724303', 'A number of multifunctional, moonlighting, proteins have been analyzed by different current programs to test whether they identify both functions. PSI-BLAST and PRODOM perform best in predicting the alternative function.'),
(70637, 2003, 'bio', 'BioEditor-simplifying macromolecular structure annotation', 'Yang, Peng|Craig, Paul A|Goodsell, David|Bourne, Philip E', 'San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman Drive, MC 0505, La Jolla 92093-0505, USA.|San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman Drive, MC 0505, La Jolla 92093-0505, USA.|San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman Drive, MC 0505, La Jolla 92093-0505, USA.|San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman Drive, MC 0505, La Jolla 92093-0505, USA.', 'United States|United States|United States|United States', 0, 'Biopolymers|Crystallography|Database Management Systems|Documentation|Hypermedia|Information Storage and Retrieval|Macromolecular Substances|Models, Molecular|Software|Structure-Activity Relationship|User-Computer Interface|Word Processing', 'Journal Article', '10.1093/bioinformatics/btg103', '12724304', 'BioEditor is an application to enable scientists and educators to prepare and present structure annotations containing formatted text, graphics, sequence data, and interactive molecular views. It is intended to bridge the gap between printed journal articles and Internet presentation formats. BioEditor is relevant in the era of structural genomics, where annotation and publication could become the rate determining step in structure determination.'),
(70638, 2003, 'bio', 'SCide: identification of stabilization centers in proteins', 'Dosztányi, Zsuzsanna|Magyar, Csaba|Tusnády, Gábor|Simon, István', 'Institute of Enzymology Biological Research Center, Hungarian Academy of Sciences, PO Box 7, Budapest, H-1518, Hungary.|Institute of Enzymology Biological Research Center, Hungarian Academy of Sciences, PO Box 7, Budapest, H-1518, Hungary.|Institute of Enzymology Biological Research Center, Hungarian Academy of Sciences, PO Box 7, Budapest, H-1518, Hungary.|Institute of Enzymology Biological Research Center, Hungarian Academy of Sciences, PO Box 7, Budapest, H-1518, Hungary.', 'Hungary|Hungary|Hungary|Hungary', 0, 'Amino Acid Sequence|Binding Sites|Capsid Proteins|Conserved Sequence|Drug Stability|Information Storage and Retrieval|Molecular Sequence Data|Protein Binding|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein|Software|Structure-Activity Relationship|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg110', '12724305', 'SCide is a program to identify stabilization centers from known protein structures. These are residues involved in cooperative long-range contacts, which can be formed between various regions of a single polypeptide chain, or they can belong to different peptides or polypeptides in a complex. The server takes a PDB file as an input, and the result is presented in graphical or text format.'),
(70639, 2003, 'bio', 'BioQuery: an object framework for building queries to biomedical databases', 'Brundege, James M|Dubay, Christopher', 'Division of Medical Informatics and Outcomes Research, BICC Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland 97239, USA.|Division of Medical Informatics and Outcomes Research, BICC Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland 97239, USA.', 'United States|United States', 3, 'Biomedical Research|Database Management Systems|Databases, Factual|Hypermedia|Information Storage and Retrieval|Internet|National Library of Medicine (U.S.)|Software|United States|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg094', '12724306', 'BioQuery is an application that helps scientists automate database searches. Users can build and store queries to public biomedical databases, and receive periodic updates on the results of those queries when new data is available. The application is implemented on a portable object framework that can provide database-searching capability to other applications. This framework is easily extensible, allowing users to develop plug-ins that provide access to new databases. BioQuery thus provides end-users with a complete database searching interface and updating service, and gives developers a toolkit to provide database-searching capability to their applications.'),
(70640, 2003, 'bio', 'IPPRED: server for proteins interactions inference', 'Goffard, Nicolas|Garcia, Virginie|Iragne, Florian|Groppi, Alexis|de Daruvar, Antoine', 'Centre de Bioinformatique Bordeaux, Université V. Segalen Bordeaux 2, 146 rue Léo Saignat, France.|Centre de Bioinformatique Bordeaux, Université V. Segalen Bordeaux 2, 146 rue Léo Saignat, France.|Centre de Bioinformatique Bordeaux, Université V. Segalen Bordeaux 2, 146 rue Léo Saignat, France.|Centre de Bioinformatique Bordeaux, Université V. Segalen Bordeaux 2, 146 rue Léo Saignat, France.|Centre de Bioinformatique Bordeaux, Université V. Segalen Bordeaux 2, 146 rue Léo Saignat, France.', 'France|France|France|France|France', 0, 'Algorithms|Amino Acid Sequence|Computers|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Local Area Networks|Macromolecular Substances|Molecular Sequence Data|Protein Binding|Proteins|Sequence Alignment|Sequence Analysis|Sequence Homology, Amino Acid|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg091', '12724307', 'IPPRED is a web based server to infer protein-protein interactions through homology search between candidate proteins and those described as interacting. This simple inference allows to propose or to validate potential interactions.'),
(70641, 2003, 'bio', 'Inference of transcriptional regulation relationships from gene expression data', 'Kwon, Andrew T|Hoos, Holger H|Ng, Raymond', 'Department of Computer Science, University of British Columbia, Vancouver, BC, Canada.|Department of Computer Science, University of British Columbia, Vancouver, BC, Canada.|Department of Computer Science, University of British Columbia, Vancouver, BC, Canada.', 'Canada|Canada|Canada', 66, 'Algorithms|Base Pair Mismatch|CDC28 Protein Kinase, S cerevisiae|Cell Cycle Proteins|Computer Simulation|Databases, Nucleic Acid|Fungal Proteins|GTP-Binding Proteins|Gene Expression Regulation|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Saccharomyces cerevisiae|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Transcription, Genetic', 'Comparative Study', '10.1093/bioinformatics/btg106', '12761051', 'In order to find gene regulatory networks from microarray data, it is important to first find direct regulatory relationships between pairs of genes.'),
(70642, 2003, 'bio', 'FPV: fast protein visualization using Java 3D', 'Can, Tolga|Wang, Yujun|Wang, Yuan-Fang|Su, Jianwen', 'Department of Computer Science, University of California at Santa Barbara, Santa Barbara, CA 93117-5110, USA. tcan@cs.ucsb.edu|Department of Computer Science, University of California at Santa Barbara, Santa Barbara, CA 93117-5110, USA. tcan@cs.ucsb.edu|Department of Computer Science, University of California at Santa Barbara, Santa Barbara, CA 93117-5110, USA. tcan@cs.ucsb.edu|Department of Computer Science, University of California at Santa Barbara, Santa Barbara, CA 93117-5110, USA. tcan@cs.ucsb.edu', 'United States|United States|United States|United States', 18, 'Computer Graphics|Computer Simulation|Computing Methodologies|Database Management Systems|Databases, Protein|Hypermedia|Imaging, Three-Dimensional|Information Storage and Retrieval|Internet|Models, Molecular|Programming Languages|Protein Conformation|Proteins|Quality Control|Software|Software Design|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg104', '12761052', 'Many tools have been developed to visualize protein structures. Tools that have been based on Java 3D((TM)) are compatible among different systems and they can be run remotely through web browsers. However, using Java 3D for visualization has some performance issues with it. The primary concerns about molecular visualization tools based on Java 3D are in their being slow in terms of interaction speed and in their inability to load large molecules. This behavior is especially apparent when the number of atoms to be displayed is huge, or when several proteins are to be displayed simultaneously for comparison.'),
(70643, 2003, 'bio', 'Integrative approach for computationally inferring protein domain interactions', 'Ng, See-Kiong|Zhang, Zhuo|Tan, Soon-Heng', 'Laboratories for Information Technology, 21 Heng Mui Keng Terrace, Singapore 119613. skng@lit.org.sg|Laboratories for Information Technology, 21 Heng Mui Keng Terrace, Singapore 119613. skng@lit.org.sg|Laboratories for Information Technology, 21 Heng Mui Keng Terrace, Singapore 119613. skng@lit.org.sg', 'Singapore|Singapore|Singapore', 0, 'Algorithms|Binding Sites|Computer Simulation|Database Management Systems|Databases, Protein|Fungal Proteins|Information Storage and Retrieval|Models, Molecular|Protein Binding|Protein Conformation|Protein Structure, Tertiary|Proteins|Reproducibility of Results|Sensitivity and Specificity|Systems Integration', 'Comparative Study', '10.1093/bioinformatics/btg118', '12761053', 'The current need for high-throughput protein interaction detection has resulted in interaction data being generated en masse through such experimental methods as yeast-two-hybrids and protein chips. Such data can be erroneous and they often do not provide adequate functional information for the detected interactions. Therefore, it is useful to develop an in silico approach to further validate and annotate the detected protein interactions.'),
(70644, 2003, 'bio', 'Pathways database system: an integrated system for biological pathways', 'Krishnamurthy, L|Nadeau, J|Ozsoyoglu, G|Ozsoyoglu, M|Schaeffer, G|Tasan, M|Xu, W', 'Center for Computational Genomics, Case Western Reserve University (CWRU), USA.|Center for Computational Genomics, Case Western Reserve University (CWRU), USA.|Center for Computational Genomics, Case Western Reserve University (CWRU), USA.|Center for Computational Genomics, Case Western Reserve University (CWRU), USA.|Center for Computational Genomics, Case Western Reserve University (CWRU), USA.|Center for Computational Genomics, Case Western Reserve University (CWRU), USA.|Center for Computational Genomics, Case Western Reserve University (CWRU), USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Database Management Systems|Databases, Factual|Databases, Genetic|Information Storage and Retrieval|Metabolism|Models, Biological|Software|Software Design|Systems Integration|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg113', '12761054', 'During the next phase of the Human Genome Project, research will focus on functional studies of attributing functions to genes, their regulatory elements, and other DNA sequences. To facilitate the use of genomic information in such studies, a new modeling perspective is needed to examine and study genome sequences in the context of many kinds of biological information. Pathways are the logical format for modeling and presenting such information in a manner that is familiar to biological researchers.'),
(70645, 2003, 'bio', 'Terminology-driven mining of biomedical literature', 'Nenadic, Goran|Spasic, Irena|Ananiadou, Sophia', 'Computer Science, University of Salford, Salford M5 4WT, UK. g.nenadic@umist.ac.uk|Computer Science, University of Salford, Salford M5 4WT, UK. g.nenadic@umist.ac.uk|Computer Science, University of Salford, Salford M5 4WT, UK. g.nenadic@umist.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Abbreviations as Topic|Algorithms|Artificial Intelligence|Database Management Systems|Databases, Bibliographic|Information Storage and Retrieval|Natural Language Processing|Pattern Recognition, Automated|Terminology as Topic|Vocabulary, Controlled', 'Comparative Study', '10.1093/bioinformatics/btg105', '12761055', 'With an overwhelming amount of textual information in molecular biology and biomedicine, there is a need for effective literature mining techniques that can help biologists to gather and make use of the knowledge encoded in text documents. Although the knowledge is organized around sets of domain-specific terms, few literature mining systems incorporate deep and dynamic terminology processing.'),
(70646, 2003, 'bio', 'Corrected small-sample estimation of the Bayes error', 'Brun, Marcel|Sabbagh, David L|Kim, Seungchan|Dougherty, Edward R', 'Department of Electrical Engineering, Texas A&M University, College Station, TX 77840, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77840, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77840, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77840, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Bayes Theorem|Computer Simulation|Gene Expression Regulation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Quality Control|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Sequence Alignment|Signal Processing, Computer-Assisted', 'Evaluation Studies', '10.1093/bioinformatics/btg144', '12761056', 'A major problem of pattern classification is estimation of the Bayes error when only small samples are available. One way to estimate the Bayes error is to design a classifier based on some classification rule applied to sample data, estimate the error of the designed classifier, and then use this estimate as an estimate of the Bayes error. Relative to the Bayes error, the expected error of the designed classifier is biased high, and this bias can be severe with small samples.'),
(70647, 2003, 'bio', 'Computation method to identify differential allelic gene expression and novel imprinted genes', 'Yang, Howard H|Hu, Ying|Edmonson, Michael|Buetow, Kenneth|Lee, Maxwell P', 'Laboratory of Population Genetics, National Cancer Institute, Gaithersburg, MD 20877, USA.|Laboratory of Population Genetics, National Cancer Institute, Gaithersburg, MD 20877, USA.|Laboratory of Population Genetics, National Cancer Institute, Gaithersburg, MD 20877, USA.|Laboratory of Population Genetics, National Cancer Institute, Gaithersburg, MD 20877, USA.|Laboratory of Population Genetics, National Cancer Institute, Gaithersburg, MD 20877, USA.', 'United States|United States|United States|United States|United States', 19, 'Algorithms|Alleles|Expressed Sequence Tags|Gene Expression Regulation|Gene Frequency|Gene Library|Genomic Imprinting|Humans|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btg127', '12761057', 'Genomic imprinting plays an important role in both normal development and diseases. Abnormal imprinting is strongly associated with several human diseases including cancers. Most of the imprinted genes were discovered in the neighborhood of the known imprinted genes. This approach is difficult to extend to analyze the whole genome. We have decided to take a computational approach to systematically search the whole genome for the presence of mono-allelic expressed genes and imprinted genes in human genome.'),
(70648, 2003, 'bio', 'Microarray standard data set and figures of merit for comparing data processing methods and experiment designs', 'He, Yudong D|Dai, Hongyue|Schadt, Eric E|Cavet, Guy|Edwards, Stephen W|Stepaniants, Sergey B|Duenwald, Sven|Kleinhanz, Robert|Jones, Allan R|Shoemaker, Daniel D|Stoughton, Roland B', 'Rosetta Inpharmatics Inc., 12 040 115th Avenue Northeast, Kirkland, WA 98034, USA. yudong_he@merck.com|Rosetta Inpharmatics Inc., 12 040 115th Avenue Northeast, Kirkland, WA 98034, USA. yudong_he@merck.com|Rosetta Inpharmatics Inc., 12 040 115th Avenue Northeast, Kirkland, WA 98034, USA. yudong_he@merck.com|Rosetta Inpharmatics Inc., 12 040 115th Avenue Northeast, Kirkland, WA 98034, USA. yudong_he@merck.com|Rosetta Inpharmatics Inc., 12 040 115th Avenue Northeast, Kirkland, WA 98034, USA. yudong_he@merck.com|Rosetta Inpharmatics Inc., 12 040 115th Avenue Northeast, Kirkland, WA 98034, USA. yudong_he@merck.com|Rosetta Inpharmatics Inc., 12 040 115th Avenue Northeast, Kirkland, WA 98034, USA. yudong_he@merck.com|Rosetta Inpharmatics Inc., 12 040 115th Avenue Northeast, Kirkland, WA 98034, USA. yudong_he@merck.com|Rosetta Inpharmatics Inc., 12 040 115th Avenue Northeast, Kirkland, WA 98034, USA. yudong_he@merck.com|Rosetta Inpharmatics Inc., 12 040 115th Avenue Northeast, Kirkland, WA 98034, USA. yudong_he@merck.com|Rosetta Inpharmatics Inc., 12 040 115th Avenue Northeast, Kirkland, WA 98034, USA. yudong_he@merck.com', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Base Sequence|DNA, Complementary|Databases, Nucleic Acid|Equipment Failure Analysis|Gene Expression Profiling|Gene Expression Regulation|Humans|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Quality Control|Reference Standards|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg126', '12761058', 'There is a very large and growing level of effort toward improving the platforms, experiment designs, and data analysis methods for microarray expression profiling. Along with a growing richness in the approaches there is a growing confusion among most scientists as to how to make objective comparisons and choices between them for different applications. There is a need for a standard framework for the microarray community to compare and improve analytical and statistical methods.'),
(70649, 2003, 'bio', 'Approximate variance-stabilizing transformations for gene-expression microarray data', 'Rocke, David M|Durbin, Blythe', 'Department of Applied Science, University of California, Davis, Davis, CA 95616, USA. dmrocke@ucdavis.edu|Department of Applied Science, University of California, Davis, Davis, CA 95616, USA. dmrocke@ucdavis.edu', 'United States|United States', 0, 'Algorithms|Analysis of Variance|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg107', '12761059', 'A variance stabilizing transformation for microarray data was recently introduced independently by several research groups. This transformation has sometimes been called the generalized logarithm or glog transformation. In this paper, we derive several alternative approximate variance stabilizing transformations that may be easier to use in some applications.'),
(70650, 2003, 'bio', 'Fuzzy C-means method for clustering microarray data', 'Dembélé, Doulaye|Kastner, Philippe', 'Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS-IMSERM-ULP, BP 10142, 67404 Illkirch Cedex, France. doulaye@titus.u-strasbg.fr|Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS-IMSERM-ULP, BP 10142, 67404 Illkirch Cedex, France. doulaye@titus.u-strasbg.fr', 'France|France', 376, 'Algorithms|Cluster Analysis|Databases, Genetic|Fuzzy Logic|Gene Expression Profiling|Gene Expression Regulation|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Quality Control|Sequence Analysis, DNA|Tumor Cells, Cultured|Yeasts', 'Comparative Study', '10.1093/bioinformatics/btg119', '12761060', 'Clustering analysis of data from DNA microarray hybridization studies is essential for identifying biologically relevant groups of genes. Partitional clustering methods such as K-means or self-organizing maps assign each gene to a single cluster. However, these methods do not provide information about the influence of a given gene for the overall shape of clusters. Here we apply a fuzzy partitioning method, Fuzzy C-means (FCM), to attribute cluster membership values to genes.'),
(70651, 2003, 'bio', 'Mining HIV dynamics using independent component analysis', 'Draghici, Sorin|Graziano, Frank|Kettoola, Samira|Sethi, Ishwar|Towfic, George', 'Department of Computer Science, Wayne State University, IA, USA.|Department of Computer Science, Wayne State University, IA, USA.|Department of Computer Science, Wayne State University, IA, USA.|Department of Computer Science, Wayne State University, IA, USA.|Department of Computer Science, Wayne State University, IA, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|CD4-Positive T-Lymphocytes|CD8-Positive T-Lymphocytes|Computer Simulation|Database Management Systems|HIV|HIV Infections|Humans|Information Storage and Retrieval|Models, Biological|Models, Statistical|Nonlinear Dynamics|Pattern Recognition, Automated|Principal Component Analysis|Treatment Outcome|Viral Load', 'Comparative Study', '10.1093/bioinformatics/btg123', '12761061', 'We implement a data mining technique based on the method of Independent Component Analysis (ICA) to generate reliable independent data sets for different HIV therapies. We show that this technique takes advantage of the ICA power to eliminate the noise generated by artificial interaction of HIV system dynamics. Moreover, the incorporation of the actual laboratory data sets into the analysis phase offers a powerful advantage when compared with other mathematical procedures that consider the general behavior of HIV dynamics.'),
(70652, 2003, 'bio', 'Codon pairs in the genome of Escherichia coli', 'Boycheva, Svetlana|Chkodrov, Georgi|Ivanov, Ivan', 'Department of Gene Regulations, Institute of Molecular Biology, Bulgarian Academy of Sciences, Sofia 1113, Bulgaria. svetlana@obzor.bio21.bas.bg|Department of Gene Regulations, Institute of Molecular Biology, Bulgarian Academy of Sciences, Sofia 1113, Bulgaria. svetlana@obzor.bio21.bas.bg|Department of Gene Regulations, Institute of Molecular Biology, Bulgarian Academy of Sciences, Sofia 1113, Bulgaria. svetlana@obzor.bio21.bas.bg', 'Bulgaria|Bulgaria|Bulgaria', 0, 'Algorithms|Codon|Databases, Nucleic Acid|Escherichia coli|Gene Expression Regulation, Bacterial|Gene Frequency|Genome, Bacterial|Protein Biosynthesis|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/btg082', '12761062', 'The effect of two neighboring codons (codon pairs) on gene expression is mediated via the interaction of their cognate tRNAs occupying the two functional ribosomal sites during the translation elongation step. For steric reasons it is reasonable to assume that not all combinations of codons and therefore of tRNAs are equally favorable when situated on the ribosome surface. Aiming of identifying preferential and rare codon pairs, we have determined the frequency of occurrence of all possible combinations of codon pairs in the entire genome of Escherichia coli (E.coli).'),
(70653, 2003, 'bio', 'Generating consensus sequences from partial order multiple sequence alignment graphs', 'Lee, Christopher', 'UCLA-DOE Center for Genomics and Proteomics, Molecular Biology Institute Department of Chemistry, University of California, Los Angeles, Los Angeles, CA 90095-1570, USA. leec@mbi.ucla.edu', 'United States', 0, 'Algorithms|Consensus Sequence|Gene Expression Profiling|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btg109', '12761063', 'Consensus sequence generation is important in many kinds of sequence analysis ranging from sequence assembly to profile-based iterative search methods. However, how can a consensus be constructed when its inherent assumption-that the aligned sequences form a single linear consensus-is not true?'),
(70654, 2003, 'bio', 'ProPred1: prediction of promiscuous MHC Class-I binding sites', 'Singh, Harpreet|Raghava, G P S', 'Institute of Microbial technology, Chandigarh 160036, India.|Institute of Microbial technology, Chandigarh 160036, India.', 'India|India', 0, 'Antigen Presentation|Binding Sites|Cysteine Endopeptidases|Databases, Protein|Histocompatibility Antigens Class I|Internet|Macromolecular Substances|Major Histocompatibility Complex|Multienzyme Complexes|Oligopeptides|Peptides|Proteasome Endopeptidase Complex|Protein Binding|Sequence Analysis, Protein|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg108', '12761064', 'ProPred1 is an on-line web tool for the prediction of peptide binding to MHC class-I alleles. This is a matrix-based method that allows the prediction of MHC binding sites in an antigenic sequence for 47 MHC class-I alleles. The server represents MHC binding regions within an antigenic sequence in user-friendly formats. These formats assist user in the identification of promiscuous MHC binders in an antigen sequence that can bind to large number of alleles. ProPred1 also allows the prediction of the standard proteasome and immunoproteasome cleavage sites in an antigenic sequence. This server allows identification of MHC binders, who have the cleavage site at the C terminus. The simultaneous prediction of MHC binders and proteasome cleavage sites in an antigenic sequence leads to the identification of potential T-cell epitopes.'),
(70655, 2003, 'bio', '3D-Jury: a simple approach to improve protein structure predictions', 'Ginalski, Krzysztof|Elofsson, Arne|Fischer, Daniel|Rychlewski, Leszek', 'BioInfoBank Institute, Limanowskiego 24A, 60-744 Poznan, Poland.|BioInfoBank Institute, Limanowskiego 24A, 60-744 Poznan, Poland.|BioInfoBank Institute, Limanowskiego 24A, 60-744 Poznan, Poland.|BioInfoBank Institute, Limanowskiego 24A, 60-744 Poznan, Poland.', 'Poland|Poland|Poland|Poland', 644, 'Algorithms|Computer Simulation|Database Management Systems|Databases, Protein|Models, Molecular|Protein Conformation|Protein Folding|Protein Structure, Tertiary|Proteins|Quality Control|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btg124', '12761065', 'Consensus structure prediction methods (meta-predictors) have higher accuracy than individual structure prediction algorithms (their components). The goal for the development of the 3D-Jury system is to create a simple but powerful procedure for generating meta-predictions using variable sets of models obtained from diverse sources. The resulting protocol should help to improve the quality of structural annotations of novel proteins.'),
(70656, 2003, 'bio', 'Observing and interpreting correlations in metabolomic networks', 'Steuer, R|Kurths, J|Fiehn, O|Weckwerth, W', 'University Potsdam, Nonlinear Dynamics Group, Am Neuen Palais 10, 14469 Potsdam, Germany. steuer@agnld.uni-potsdam.de|University Potsdam, Nonlinear Dynamics Group, Am Neuen Palais 10, 14469 Potsdam, Germany. steuer@agnld.uni-potsdam.de|University Potsdam, Nonlinear Dynamics Group, Am Neuen Palais 10, 14469 Potsdam, Germany. steuer@agnld.uni-potsdam.de|University Potsdam, Nonlinear Dynamics Group, Am Neuen Palais 10, 14469 Potsdam, Germany. steuer@agnld.uni-potsdam.de', 'Germany|Germany|Germany|Germany', 227, 'Algorithms|Glycolysis|Metabolism|Models, Biological|Models, Statistical|Multienzyme Complexes|Reproducibility of Results|Sensitivity and Specificity|Statistics as Topic|Stochastic Processes', 'Evaluation Studies', '10.1093/bioinformatics/btg120', '12761066', 'Metabolite profiling aims at an unbiased identification and quantification of all the metabolites present in a biological sample. Based on their pair-wise correlations, the data obtained from metabolomic experiments are organized into metabolic correlation networks and the key challenge is to deduce unknown pathways based on the observed correlations. However, the data generated is fundamentally different from traditional biological measurements and thus the analysis is often restricted to rather pragmatic approaches, such as data mining tools, to discriminate between different metabolic phenotypes.'),
(70657, 2003, 'bio', 'Hierarchical analysis of dependency in metabolic networks', 'Gagneur, Julien|Jackson, David B|Casari, Georg', 'Lion Bioscience AG, Waldhoferstr. 98, 69123 Heidelberg, Germany. julien.gagneur@cellzome.com|Lion Bioscience AG, Waldhoferstr. 98, 69123 Heidelberg, Germany. julien.gagneur@cellzome.com|Lion Bioscience AG, Waldhoferstr. 98, 69123 Heidelberg, Germany. julien.gagneur@cellzome.com', 'Germany|Germany|Germany', 0, 'Algorithms|Escherichia coli|Gene Expression Regulation, Bacterial|Metabolism|Models, Biological|Models, Statistical|Multienzyme Complexes|Reproducibility of Results|Sensitivity and Specificity|Statistics as Topic|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/btg115', '12761067', 'Elucidation of metabolic networks for an increasing number of organisms reveals that even small networks can contain thousands of reactions and chemical species. The intimate connectivity between components complicates their decomposition into biologically meaningful sub-networks. Moreover, traditional higher-order representations of metabolic networks as metabolic pathways, suffers from the lack of rigorous definition, yielding pathways of disparate content and size.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70658, 2003, 'bio', 'Zerg: a very fast BLAST parser library', 'Paquola, Apuã C M|Machado, Abimael A|Reis, Eduardo M|Da Silva, Aline M|Verjovski-Almeida, Sergio', 'Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo 05508-900, São Paulo, SP, Brazil. verjo@iq.usp.br|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo 05508-900, São Paulo, SP, Brazil. verjo@iq.usp.br|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo 05508-900, São Paulo, SP, Brazil. verjo@iq.usp.br|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo 05508-900, São Paulo, SP, Brazil. verjo@iq.usp.br|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo 05508-900, São Paulo, SP, Brazil. verjo@iq.usp.br', 'Brazil|Brazil|Brazil|Brazil|Brazil', 0, 'Database Management Systems|Databases, Nucleic Acid|National Library of Medicine (U.S.)|Sequence Alignment|Sequence Analysis, DNA|Software|United States|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg122', '12761068', 'Zerg is a library of sub-routines that parses the output from all NCBI BLAST programs (Blastn, Blastp, Blastx, Tblastn and Tblastx) and returns the attributes of a BLAST report to the user. It is optimized for speed, being especially useful for large-scale genomic analysis. Benchmark tests show that Zerg is over two orders of magnitude faster than some widely used BLAST parsers.'),
(70659, 2003, 'bio', 'Visual representation of database search results: the RHIMS Plot', 'Martin, David M A|Hill, Pamela|Barton, Geoffrey J|Flavell, Andrew J', 'Post-Genomics and Molecular Interactions Centre, Wellcome Trust Biocentre, University of Dundee, Dundee DD1 5EH, UK. d.m.a.martin@dundee.ac.uk|Post-Genomics and Molecular Interactions Centre, Wellcome Trust Biocentre, University of Dundee, Dundee DD1 5EH, UK. d.m.a.martin@dundee.ac.uk|Post-Genomics and Molecular Interactions Centre, Wellcome Trust Biocentre, University of Dundee, Dundee DD1 5EH, UK. d.m.a.martin@dundee.ac.uk|Post-Genomics and Molecular Interactions Centre, Wellcome Trust Biocentre, University of Dundee, Dundee DD1 5EH, UK. d.m.a.martin@dundee.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Nucleic Acid|Gene Expression Profiling|Gene Expression Regulation, Plant|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology|Software|User-Computer Interface|Vicia sativa', 'Comparative Study', '10.1093/bioinformatics/btg116', '12761069', 'An algorithm and software are described that provide a fast method to produce a novel, function-oriented visualization of the results of a sequence database search. Text mining of sequence annotations allows position specific plots of potential functional similarity to be compared in a simple compact representation.'),
(70660, 2003, 'bio', 'ACGT-a comparative genomics tool', 'Xie, Tao|Hood, Leroy', 'Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. txie@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. txie@systemsbiology.org', 'United States|United States', 11, 'Computer Graphics|Conserved Sequence|Database Management Systems|Databases, Nucleic Acid|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Genomics|Haemophilus influenzae|Information Storage and Retrieval|Pasteurella multocida|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg121', '12761070', 'ACGT (a comparative genomics tool) is a genomic DNA sequence comparison viewer and analyzer. It can read a pair of DNA sequences in GenBank, Embl or Fasta formats, with or without a comparison file, and provide users with many options to view and analyze the similarities between the input sequences. It is written in Java and can be run on Unix, Linux and Windows platforms.'),
(70661, 2003, 'bio', 'Ligand-Info, searching for similar small compounds using index profiles', 'von Grotthuss, Marcin|Pas, Jakub|Rychlewski, Leszek', 'BioInfoBank Institute, ul. Limanowskiego 24A, 60-744 Poznan, Poland. leszek@bioinfo.pl|BioInfoBank Institute, ul. Limanowskiego 24A, 60-744 Poznan, Poland. leszek@bioinfo.pl|BioInfoBank Institute, ul. Limanowskiego 24A, 60-744 Poznan, Poland. leszek@bioinfo.pl', 'Poland|Poland|Poland', 0, 'Binding Sites|Computer Graphics|Conserved Sequence|Database Management Systems|Databases, Protein|Gene Expression Profiling|Genomics|Information Storage and Retrieval|Protein Binding|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg117', '12761071', 'The Ligand-Info system is based on the assumption that small molecules with similar structure have similar functional (binding) properties. The developed system enables a fast and sensitive index based search for similar compounds in large databases. Index profiles, constructed by averaging indexes of related molecules are used to increase the specificity of the search. The utilization of index profiles helps to focus on frequent, common features of a family of compounds.'),
(70662, 2003, 'bio', 'CAP: conformation angles package-displaying the conformation angles of side chains in proteins', 'Sheik, S S|Sundararajan, P|Shanthi, V|Sekar, K', 'Bioinformatics Centre and Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560 012, India. sekar@physics.iisc.ernet.in|Bioinformatics Centre and Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560 012, India. sekar@physics.iisc.ernet.in|Bioinformatics Centre and Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560 012, India. sekar@physics.iisc.ernet.in|Bioinformatics Centre and Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560 012, India. sekar@physics.iisc.ernet.in', 'India|India|India|India', 0, 'Amino Acids|Crystallography|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Leucine|Models, Molecular|Plant Lectins|Protein Conformation|Protein Structure, Tertiary|Proteins|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg125', '12761072', 'A graphics package has been developed to display all side chain conformation angles of the user selected residue in a given protein structure. The proposed package is incorporated with all the protein structures (solved using X-ray diffraction and NMR spectroscopy) available in the Protein Data Bank. The package displays the multiple conformations adopted by a single amino acid residue whose structure is solved and refined at very high resolution. In addition, it shows the percentage distribution of the side chain conformation angles in different rotameric states.'),
(70663, 2003, 'bio', 'New analytical techniques for the interpretation of microarray data Proceedings from the NIPS Workshop on Machine Learning Techniques for Bioinformatics British Columbia, Canada, December 2001', '-', '-', '-', 0, 'Gene Expression Profiling|Oligonucleotide Array Sequence Analysis', 'Congress', '10.1093/bioinformatics/btg125', '12801863', '-'),
(70664, 2003, 'bio', 'Modified nonparametric approaches to detecting differentially expressed genes in replicated microarray experiments', 'Zhao, Yanli|Pan, Wei', 'Division of Biostatistics, School of Public Health, University of Minnesota, MMC 303, A460 Mayo Building, 420 Delaware Street SE, Minneapolis, MN 55455, USA.|Division of Biostatistics, School of Public Health, University of Minnesota, MMC 303, A460 Mayo Building, 420 Delaware Street SE, Minneapolis, MN 55455, USA.', 'United States|United States', 61, 'Algorithms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Variation|Humans|Leukemia, Myeloid|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/btf879', '12801864', 'An important goal in analyzing microarray data is to determine which genes are differentially expressed across two kinds of tissue samples or samples obtained under two experimental conditions. Various parametric tests, such as the two-sample t-test, have been used, but their possibly too strong parametric assumptions or large sample justifications may not hold in practice. As alternatives, a class of three nonparametric statistical methods, including the empirical Bayes method of Efron et al. (2001), the significance analysis of microarray (SAM) method of Tusher et al. (2001) and the mixture model method (MMM) of Pan et al. (2001), have been proposed. All the three methods depend on constructing a test statistic and a so-called null statistic such that the null statistics distribution can be used to approximate the null distribution of the test statistic. However, relatively little effort has been directed toward assessment of the performance or the underlying assumptions of the methods in constructing such test and null statistics.'),
(70665, 2003, 'bio', 'Statistical adjustment of signal censoring in gene expression experiments', 'Wit, Ernst|McClure, John', 'Department of Statistics, University of Glasgow, Glasgow G12 8QW, UK. ernst@stats.gla.ac.uk|Department of Statistics, University of Glasgow, Glasgow G12 8QW, UK. ernst@stats.gla.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Artifacts|Cell Line, Tumor|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Image Interpretation, Computer-Assisted|Likelihood Functions|Microscopy, Fluorescence|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Signal Processing, Computer-Assisted|Skin Neoplasms|Spectrometry, Fluorescence', 'Comparative Study', '10.1093/bioinformatics/btg003', '12801865', 'Numerical output of spotted microarrays displays censoring of pixel intensities at some software dependent threshold. This reduces the quality of gene expression data, because it seriously violates the linearity of expression with respect to signal intensity. Statistical methods based on typically available spot summaries together with some parametric assumptions can suggest ways to correct for this defect.'),
(70666, 2003, 'bio', 'Boosting for tumor classification with gene expression data', 'Dettling, Marcel|Bühlmann, Peter', 'Seminar für Statistik, ETH Zürich, CH-8092, Switzerland. dettling@stat.math.ethz.ch|Seminar für Statistik, ETH Zürich, CH-8092, Switzerland. dettling@stat.math.ethz.ch', 'Switzerland|Switzerland', 0, 'Algorithms|Cluster Analysis|Databases, Genetic|Decision Trees|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btf867', '12801866', 'Microarray experiments generate large datasets with expression values for thousands of genes but not more than a few dozens of samples. Accurate supervised classification of tissue samples in such high-dimensional problems is difficult but often crucial for successful diagnosis and treatment. A promising way to meet this challenge is by using boosting in conjunction with decision trees.'),
(70667, 2003, 'bio', 'K-ary clustering with optimal leaf ordering for gene expression data', 'Bar-Joseph, Ziv|Demaine, Erik D|Gifford, David K|Srebro, Nathan|Hamel, Angèle M|Jaakkola, Tommi S', 'Laboratory for Computer Science, MIT, 545 Technology Square, Cambridge, MA 02139, USA. zivbj@mit.edu|Laboratory for Computer Science, MIT, 545 Technology Square, Cambridge, MA 02139, USA. zivbj@mit.edu|Laboratory for Computer Science, MIT, 545 Technology Square, Cambridge, MA 02139, USA. zivbj@mit.edu|Laboratory for Computer Science, MIT, 545 Technology Square, Cambridge, MA 02139, USA. zivbj@mit.edu|Laboratory for Computer Science, MIT, 545 Technology Square, Cambridge, MA 02139, USA. zivbj@mit.edu|Laboratory for Computer Science, MIT, 545 Technology Square, Cambridge, MA 02139, USA. zivbj@mit.edu', 'United States|United States|United States|United States|United States|United States', 53, 'Algorithms|Animals|Bursa of Fabricius|Chickens|Cluster Analysis|Decision Trees|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, myc|Lymphoma, B-Cell|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Quality Control|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology|Stochastic Processes|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg030', '12801867', 'A major challenge in gene expression analysis is effective data organization and visualization. One of the most popular tools for this task is hierarchical clustering. Hierarchical clustering allows a user to view relationships in scales ranging from single genes to large sets of genes, while at the same time providing a global view of the expression data. However, hierarchical clustering is very sensitive to noise, it usually lacks of a method to actually identify distinct clusters, and produces a large number of possible leaf orderings of the hierarchical clustering tree. In this paper we propose a new hierarchical clustering algorithm which reduces susceptibility to noise, permits up to k siblings to be directly related, and provides a single optimal order for the resulting tree.'),
(70668, 2003, 'bio', 'Coupled two-way clustering analysis of breast cancer and colon cancer gene expression data', 'Getz, Gad|Gal, Hilah|Kela, Itai|Notterman, Daniel A|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', 0, 'Algorithms|Breast Neoplasms|Cluster Analysis|Colonic Neoplasms|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btf876', '12801868', 'We present and review coupled two-way clustering, a method designed to mine gene expression data. The method identifies submatrices of the total expression matrix, whose clustering analysis reveals partitions of samples (and genes) into biologically relevant classes. We demonstrate, on data from colon and breast cancer, that we are able to identify partitions that elude standard clustering analysis.'),
(70669, 2003, 'bio', 'Bagging to improve the accuracy of a clustering procedure', 'Dudoit, Sandrine|Fridlyand, Jane', 'Division of Biostatistics, School of Public Health, University of California, Berkeley, 140 Earl Warren Hall, 7360, Berkeley, CA 94720-7360, USA. sandrine@stat.berkeley.edu|Division of Biostatistics, School of Public Health, University of California, Berkeley, 140 Earl Warren Hall, 7360, Berkeley, CA 94720-7360, USA. sandrine@stat.berkeley.edu', 'United States|United States', 361, 'Algorithms|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Leukemia|Melanoma|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg038', '12801869', 'The microarray technology is increasingly being applied in biological and medical research to address a wide range of problems such as the classification of tumors. An important statistical question associated with tumor classification is the identification of new tumor classes using gene expression profiles. Essential aspects of this clustering problem include identifying accurate partitions of the tumor samples into clusters and assessing the confidence of cluster assignments for individual samples.'),
(70670, 2003, 'bio', 'Simultaneous gene clustering and subset selection for sample classification via MDL', 'Jörnsten, Rebecka|Yu, Bin', 'Department of Statistics, Rutgers University, 501 Hill Center, Piscataway, NJ 08854, USA. rebecka@stat.rutgers.edu|Department of Statistics, Rutgers University, 501 Hill Center, Piscataway, NJ 08854, USA. rebecka@stat.rutgers.edu', 'United States|United States', 67, 'Algorithms|Cell Line, Tumor|Cluster Analysis|Colonic Neoplasms|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Leukemia|Models, Genetic|Models, Statistical|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Principal Component Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg039', '12801870', 'The microarray technology allows for the simultaneous monitoring of thousands of genes for each sample. The high-dimensional gene expression data can be used to study similarities of gene expression profiles across different samples to form a gene clustering. The clusters may be indicative of genetic pathways. Parallel to gene clustering is the important application of sample classification based on all or selected gene expressions. The gene clustering and sample classification are often undertaken separately, or in a directional manner (one as an aid for the other). However, such separation of these two tasks may occlude informative structure in the data. Here we present an algorithm for the simultaneous clustering of genes and subset selection of gene clusters for sample classification. We develop a new model selection criterion based on Rissanens MDL (minimum description length) principle. For the first time, an MDL code length is given for both explanatory variables (genes) and response variables (sample class labels). The final output of the proposed algorithm is a sparse and interpretable classification rule based on cluster centroids or the closest genes to the centroids.'),
(70671, 2003, 'bio', 'Novel clustering algorithm for microarray expression data in a truncated SVD space', 'Horn, David|Axel, Inon', 'School of Physics and Astronomy, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel. horn@post.tau.ac.il|School of Physics and Astronomy, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel. horn@post.tau.ac.il', 'Israel|Israel', 54, 'Algorithms|Cell Cycle|Cell Line, Tumor|Cluster Analysis|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Leukemia|Models, Genetic|Models, Statistical|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Principal Component Analysis|Reproducibility of Results|Saccharomyces cerevisiae|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btg053', '12801871', 'This paper introduces the application of a novel clustering method to microarray expression data. Its first stage involves compression of dimensions that can be achieved by applying SVD to the gene-sample matrix in microarray problems. Thus the data (samples or genes) can be represented by vectors in a truncated space of low dimensionality, 4 and 5 in the examples studied here. We find it preferable to project all vectors onto the unit sphere before applying a clustering algorithm. The clustering algorithm used here is the quantum clustering method that has one free scale parameter. Although the method is not hierarchical, it can be modified to allow hierarchy in terms of this scale parameter.'),
(70672, 2003, 'bio', 'Learning rule-based models of biological process from gene expression time profiles using gene ontology', 'Hvidsten, Torgeir R|Laegreid, Astrid|Komorowski, Jan', 'Department of Computer and Information Science, Norwegian University of Science and Technology, N-7491 Trondheim, Norway.|Department of Computer and Information Science, Norwegian University of Science and Technology, N-7491 Trondheim, Norway.|Department of Computer and Information Science, Norwegian University of Science and Technology, N-7491 Trondheim, Norway.', 'Norway|Norway|Norway', 83, 'Algorithms|Artificial Intelligence|Cell Cycle|Cluster Analysis|Databases, Genetic|Fibroblasts|Gene Expression Profiling|Gene Expression Regulation|Humans|Information Storage and Retrieval|Models, Genetic|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Terminology as Topic', 'Comparative Study', '10.1093/bioinformatics/btg047', '12801872', 'Microarray technology enables large-scale inference of the participation of genes in biological process from similar expression profiles. Our aim is to induce classificatory models from expression data and biological knowledge that can automatically associate genes with novel hypotheses of biological process.'),
(70673, 2003, 'bio', 'Gene interaction in DNA microarray data is decomposed by information geometric measure', 'Nakahara, Hiroyuki|Nishimura, Shin-ichi|Inoue, Masato|Hori, Gen|Amari, Shun-ichi', 'Lab. for Mathematical Neuroscience, RIKEN Brain Science Institute, Saitama 351-0198, Japan. hiro@brain.riken.go.jp|Lab. for Mathematical Neuroscience, RIKEN Brain Science Institute, Saitama 351-0198, Japan. hiro@brain.riken.go.jp|Lab. for Mathematical Neuroscience, RIKEN Brain Science Institute, Saitama 351-0198, Japan. hiro@brain.riken.go.jp|Lab. for Mathematical Neuroscience, RIKEN Brain Science Institute, Saitama 351-0198, Japan. hiro@brain.riken.go.jp|Lab. for Mathematical Neuroscience, RIKEN Brain Science Institute, Saitama 351-0198, Japan. hiro@brain.riken.go.jp', 'Japan|Japan|Japan|Japan|Japan', 9, 'Algorithms|Cluster Analysis|DNA-Binding Proteins|Epistasis, Genetic|Feasibility Studies|Gene Expression Profiling|Gene Expression Regulation|Gene Expression Regulation, Neoplastic|Humans|Immunoglobulin Heavy Chains|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Regulatory Factor X Transcription Factors|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Statistics as Topic|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/btg098', '12801873', 'Given the vast amount of gene expression data, it is essential to develop a simple and reliable method of investigating the fine structure of gene interaction. We show how an information geometric measure achieves this.'),
(70674, 2003, 'bio', 'Classification of multiple cancer types by multicategory support vector machines using gene expression data', 'Lee, Yoonkyung|Lee, Cheol-Koo', 'Department of Statistics, The Ohio State University, Columbus, OH 43210, USA. yklee@stat.ohio-state.edu|Department of Statistics, The Ohio State University, Columbus, OH 43210, USA. yklee@stat.ohio-state.edu', 'United States|United States', 231, 'Algorithms|Carcinoma, Neuroendocrine|Child|Computing Methodologies|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Testing|Humans|Leukemia, Myeloid|Neoplasms|Oligonucleotide Array Sequence Analysis|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg102', '12801874', 'High-density DNA microarray measures the activities of several thousand genes simultaneously and the gene expression profiles have been used for the cancer classification recently. This new approach promises to give better therapeutic measurements to cancer patients by diagnosing cancer types with improved accuracy. The Support Vector Machine (SVM) is one of the classification methods successfully applied to the cancer diagnosis problems. However, its optimal extension to more than two classes was not obvious, which might impose limitations in its application to multiple tumor types. We briefly introduce the Multicategory SVM, which is a recently proposed extension of the binary SVM, and apply it to multiclass cancer diagnosis problems.'),
(70675, 2003, 'bio', 'eXPatGen: generating dynamic expression patterns for the systematic evaluation of analytical methods', 'Michaud, Dennis J|Marsh, Adam G|Dhurjati, Prasad S', 'Department of Chemical Engineering, University of Delaware, Newark, DE 19716, USA.|Department of Chemical Engineering, University of Delaware, Newark, DE 19716, USA.|Department of Chemical Engineering, University of Delaware, Newark, DE 19716, USA.', 'United States|United States|United States', 21, 'Algorithms|Computer Simulation|Database Management Systems|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Internet|Models, Genetic|Oligonucleotide Array Sequence Analysis|Online Systems|Software', 'Comparative Study', '10.1093/bioinformatics/btg132', '12801875', 'Experimental gene expression data sets, such as those generated by microarray or gene chip experiments, typically have significant noise and complicated interconnectivities that make understanding even simple regulatory patterns difficult. Given these complications, characterizing the effectiveness of different analysis techniques to uncover network groups and structures remains a challenge. Generating simulated expression patterns with known biological features of expression complexity, diversity and interconnectivities provides a more controlled means of investigating the appropriateness of different analysis methods. A simulation-based approach can systematically evaluate different gene expression analysis techniques and provide a basis for improved methods in dynamic metabolic network reconstruction.'),
(70676, 2003, 'bio', 'A statistical problem for inference to regulatory structure from associations of gene expression measurements with microarrays', 'Chu, Tianjiao|Glymour, Clark|Scheines, Richard|Spirtes, Peter', 'Department of Philosophy, Carnegie Mellon University, USA. tchu@andrew.cmu.edu|Department of Philosophy, Carnegie Mellon University, USA. tchu@andrew.cmu.edu|Department of Philosophy, Carnegie Mellon University, USA. tchu@andrew.cmu.edu|Department of Philosophy, Carnegie Mellon University, USA. tchu@andrew.cmu.edu', 'United States|United States|United States|United States', 36, 'Algorithms|Artifacts|Gene Expression Profiling|Gene Expression Regulation|Genetic Variation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sample Size', 'Journal Article', '10.1093/bioinformatics/btg011', '12801876', 'One approach to inferring genetic regulatory structure from microarray measurements of mRNA transcript hybridization is to estimate the associations of gene expression levels measured in repeated samples. The associations may be estimated by correlation coefficients or by conditional frequencies (for discretized measurements) or by some other statistic. Although these procedures have been successfully applied to other areas, their validity when applied to microarray measurements has yet to be tested.'),
(70677, 2003, 'bio', 'Coupled two-way clustering server', 'Getz, Gad|Domany, Eytan', 'Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. ctwc_support@weizmann.ac.il|Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. ctwc_support@weizmann.ac.il', 'Israel|Israel', 19, 'Algorithms|Cluster Analysis|Computers|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Internet|Oligonucleotide Array Sequence Analysis|Online Systems|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1093/bioinformatics/btg143', '12801877', 'The CTWC server provides access to the software, CTWC1.00, that implements Coupled Two Way Clustering (Getz et al., 2000), a method designed to mine gene expression data'),
(70678, 2003, 'bio', 'RASCAL: rapid scanning and correction of multiple sequence alignments', 'Thompson, J D|Thierry, J C|Poch, O', 'Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire (CNRS/INSERM/ULP), B.P. 10142, 67404 Illkirch Cedex, France.|Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire (CNRS/INSERM/ULP), B.P. 10142, 67404 Illkirch Cedex, France.|Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire (CNRS/INSERM/ULP), B.P. 10142, 67404 Illkirch Cedex, France.', 'France|France|France', 104, 'Algorithms|Amino Acid Sequence|Databases, Protein|Gene Expression Profiling|Molecular Sequence Data|Proteins|Quality Control|Receptors, Cytoplasmic and Nuclear|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/btg133', '12801878', 'Most multiple sequence alignment programs use heuristics that sometimes introduce errors into the alignment. The most commonly used methods to correct these errors use iterative techniques to maximize an objective function. We present here an alternative, knowledge-based approach that combines a number of recently developed methods into a two-step refinement process. The alignment is divided horizontally and vertically to form a lattice in which well aligned regions can be differentiated. Alignment correction is then restricted to the less reliable regions, leading to a more reliable and efficient refinement strategy.'),
(70679, 2003, 'bio', 'The small-world dynamics of tree networks and data mining in phyloinformatics', 'Piel, William H|Sanderson, Michael J|Donoghue, Michael J', 'Institute of Evolutionary and Ecological Sciences, Kaiserstraat 63, Leiden University 2311 GP Leiden, The Netherlands. wpiel@buffalo.edu|Institute of Evolutionary and Ecological Sciences, Kaiserstraat 63, Leiden University 2311 GP Leiden, The Netherlands. wpiel@buffalo.edu|Institute of Evolutionary and Ecological Sciences, Kaiserstraat 63, Leiden University 2311 GP Leiden, The Netherlands. wpiel@buffalo.edu', 'Netherlands|Netherlands|Netherlands', 13, 'Algorithms|Biological Evolution|Database Management Systems|Databases, Genetic|Decision Trees|Evolution, Molecular|Gene Expression Profiling|Genetic Variation|Information Storage and Retrieval|Phylogeny', 'Evaluation Studies', '10.1093/bioinformatics/btg131', '12801879', 'A noble and ultimate objective of phyloinformatic research is to assemble, synthesize, and explore the evolutionary history of life on earth. Data mining methods for performing these tasks are not yet well developed, but one avenue of research suggests that network connectivity dynamics will play an important role in future methods. Analysis of disordered networks, such as small-world networks, has applications as diverse as disease propagation, collaborative networks, and power grids. Here we apply similar analyses to networks of phylogenetic trees in order to understand how synthetic information can emerge from a database of phylogenies.'),
(70680, 2003, 'bio', 'Modular modeling of cellular systems with ProMoT/Diva', 'Ginkel, M|Kremling, A|Nutsch, T|Rehner, R|Gilles, E D', 'Max-Planck-Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, D-39106 Magdeburg, Germany. ginkel@mpi-magdeburg.mpg.de|Max-Planck-Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, D-39106 Magdeburg, Germany. ginkel@mpi-magdeburg.mpg.de|Max-Planck-Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, D-39106 Magdeburg, Germany. ginkel@mpi-magdeburg.mpg.de|Max-Planck-Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, D-39106 Magdeburg, Germany. ginkel@mpi-magdeburg.mpg.de|Max-Planck-Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, D-39106 Magdeburg, Germany. ginkel@mpi-magdeburg.mpg.de', 'Germany|Germany|Germany|Germany|Germany', 70, 'Algorithms|Cell Physiological Phenomena|Computer Simulation|Databases, Factual|Metabolism|Models, Biological|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg128', '12801880', 'Need for software to setup and analyze complex mathematical models for cellular systems in a modular way, that also integrates the experimental environment of the cells.'),
(70681, 2003, 'bio', 'Genescript: DNA sequence annotation pipeline', 'Hudek, Alexander K|Cheung, Joseph|Boright, Andrew P|Scherer, Stephen W', 'Department of Genetics, The Hospital for Sick Children, Room 9107, Toronto, Ontario, M5G 1X8, Canada. alex@genet.sickkids.on.ca|Department of Genetics, The Hospital for Sick Children, Room 9107, Toronto, Ontario, M5G 1X8, Canada. alex@genet.sickkids.on.ca|Department of Genetics, The Hospital for Sick Children, Room 9107, Toronto, Ontario, M5G 1X8, Canada. alex@genet.sickkids.on.ca|Department of Genetics, The Hospital for Sick Children, Room 9107, Toronto, Ontario, M5G 1X8, Canada. alex@genet.sickkids.on.ca', 'Canada|Canada|Canada|Canada', 5, 'Computer Graphics|Database Management Systems|Databases, Genetic|Documentation|Expressed Sequence Tags|Gene Expression Profiling|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg134', '12801881', 'Genescript uses a number of publicly available analysis programs to annotate a DNA sequence. It provides an integrated display of results from each program, and includes an evidence-based scoring system that gives informative summaries of predicted gene models.'),
(70682, 2003, 'bio', 'A survey of the Predictive Toxicology Challenge 2000-2001', 'Helma, C|Kramer, S', 'Machine Learning Lab, University Freiburg, D-79110 Freiburg, Germany. helma@informatik.uni-freiburg.de|Machine Learning Lab, University Freiburg, D-79110 Freiburg, Germany. helma@informatik.uni-freiburg.de', 'Germany|Germany', 47, 'Animals|Carcinogenicity Tests|Carcinogens|Data Collection|Databases, Factual|Environmental Exposure|Government Programs|Mice|Models, Biological|Neoplasms|Rats|Risk Assessment|Structure-Activity Relationship|Toxicology|United States', 'Journal Article', '10.1093/bioinformatics/btg084', '12835259', 'The Predictive Toxicology Challenge (PTC) was initiated to stimulate the development of advanced techniques for predictive toxicology models. The goal of this challenge was to compare different approaches for the prediction of rodent carcinogenicity, based on the experimental results of the US National Toxicology Program (NTP).'),
(70683, 2003, 'bio', 'Statistical evaluation of the Predictive Toxicology Challenge 2000-2001', 'Toivonen, Hannu|Srinivasan, Ashwin|King, Ross D|Kramer, Stefan|Helma, Christoph', 'Department of Computer Science, PO Box 26 (Teollisuuskatu 23), FIN-00014 University of Helsinki, Finland. hannu.toivonen@cs.helsinki.fi|Department of Computer Science, PO Box 26 (Teollisuuskatu 23), FIN-00014 University of Helsinki, Finland. hannu.toivonen@cs.helsinki.fi|Department of Computer Science, PO Box 26 (Teollisuuskatu 23), FIN-00014 University of Helsinki, Finland. hannu.toivonen@cs.helsinki.fi|Department of Computer Science, PO Box 26 (Teollisuuskatu 23), FIN-00014 University of Helsinki, Finland. hannu.toivonen@cs.helsinki.fi|Department of Computer Science, PO Box 26 (Teollisuuskatu 23), FIN-00014 University of Helsinki, Finland. hannu.toivonen@cs.helsinki.fi', 'Finland|Finland|Finland|Finland|Finland', 82, 'Algorithms|Animals|Artificial Intelligence|Carcinogenicity Tests|Carcinogens|Data Collection|Databases, Factual|Environmental Exposure|Female|Government Programs|Male|Mice|Models, Biological|Models, Statistical|Neoplasms|Rats|Reproducibility of Results|Risk Assessment|Sensitivity and Specificity|Sex Factors|Species Specificity|Structure-Activity Relationship|Toxicology|United States', 'Comparative Study', '10.1093/bioinformatics/btg130', '12835260', 'The development of in silico models to predict chemical carcinogenesis from molecular structure would help greatly to prevent environmentally caused cancers. The Predictive Toxicology Challenge (PTC) competition was organized to test the state-of-the-art in applying machine learning to form such predictive models.'),
(70684, 2003, 'bio', 'Putting the Predictive Toxicology Challenge into perspective: reflections on the results', 'Benigni, Romualdo|Giuliani, Alessandro', 'Laboratory of Comparative Toxicology and Ecotoxicology, Istituto Superiore di Sanita, Viale Regina Elena 299, 00161 Rome, Italy. rbenigni@iss.it|Laboratory of Comparative Toxicology and Ecotoxicology, Istituto Superiore di Sanita, Viale Regina Elena 299, 00161 Rome, Italy. rbenigni@iss.it', 'Italy|Italy', 54, 'Algorithms|Animals|Artificial Intelligence|Carcinogenicity Tests|Carcinogens|Data Collection|Databases, Factual|Environmental Exposure|Government Programs|Models, Biological|Models, Statistical|Neoplasms|Rats|Reproducibility of Results|Risk Assessment|Sensitivity and Specificity|Structure-Activity Relationship|Toxicology|United States', 'Journal Article', '10.1093/bioinformatics/btg099', '12835261', 'Chemical carcinogenicity is of primary interest, because it drives much of the current regulatory actions regarding new and existing chemicals, and its experimental determination involves time-consuming and expensive animal testing. Both academia and private companies are actively trying to develop SAR and QSAR models. This paper reviews the new Predictive Toxicology Challenge (PTC) results, by putting them into the context of previous attempts.'),
(70685, 2003, 'bio', 'Toxicology analysis by means of the JSM-method', 'Blinova, V G|Dobrynin, D A|Finn, V K|Kuznetsov, S O|Pankratova, E S', 'All-Russia Institute for Scientific and Technical Information (VINITI), Usievicha 20, 125219 Moscow, Russia.|All-Russia Institute for Scientific and Technical Information (VINITI), Usievicha 20, 125219 Moscow, Russia.|All-Russia Institute for Scientific and Technical Information (VINITI), Usievicha 20, 125219 Moscow, Russia.|All-Russia Institute for Scientific and Technical Information (VINITI), Usievicha 20, 125219 Moscow, Russia.|All-Russia Institute for Scientific and Technical Information (VINITI), Usievicha 20, 125219 Moscow, Russia.', '-|-|-|-|-', 0, 'Algorithms|Animals|Artificial Intelligence|Carcinogenicity Tests|Carcinogens|Data Collection|Databases, Factual|Environmental Exposure|Female|Government Programs|Male|Mice|Models, Biological|Models, Statistical|Neoplasms|Rats|Reproducibility of Results|Risk Assessment|Sensitivity and Specificity|Sex Factors|Species Specificity|Structure-Activity Relationship|Toxicology|United States', 'Comparative Study', '10.1093/bioinformatics/btg096', '12835262', 'A model for learning potential causes of toxicity from positive and negative examples and predicting toxicity for the dataset used in the Predictive Toxicology Challenge (PTC) is presented. The learning model assumes that the causes of toxicity can be given as substructures common to positive examples that are not substructures of negative examples. This assumption results in the choice of a learning model, called the JSM-method, and a language for representing chemical compounds, called the Fragmentary Code of Substructure Superposition (FCSS). By means of the latter, chemical compounds are represented as sets of substructures which are biologically meaningful from the expert point of view.'),
(70686, 2003, 'bio', 'Characteristic substructures and properties in chemical carcinogens studied by the cascade model', 'Okada, Takashi', 'Center for Information & Media Studies, Kwansei Gakuin University, 1-1-155 Uegahara, Nishinomiya, 662-8501, Japan. okada-office@ksc.kwansei.ac.jp', 'Japan', 6, 'Algorithms|Animals|Artificial Intelligence|Carcinogenicity Tests|Carcinogens|Data Collection|Databases, Factual|Environmental Exposure|Female|Government Programs|Male|Mice|Models, Biological|Models, Statistical|Neoplasms|Rats|Reproducibility of Results|Risk Assessment|Sensitivity and Specificity|Sex Factors|Species Specificity|Structure-Activity Relationship|Toxicology|United States', 'Comparative Study', '10.1093/bioinformatics/btg129', '12835263', 'Chemical carcinogenicity is an important subject in health and environmental sciences, and a reliable method is expected to identify characteristic factors for carcinogenicity. The predictive toxicology challenge (PTC) 2000-2001 has provided the opportunity for various data mining methods to evaluate their performance. The cascade model, a data mining method developed by the author, has the capability to mine for local correlations in data sets with a large number of attributes. The current paper explores the effectiveness of the method on the problem of chemical carcinogenicity.'),
(70687, 2003, 'bio', 'Pyranose oxidase identified as a member of the GMC oxidoreductase family', 'Albrecht, Mario|Lengauer, Thomas', 'Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. mario.albrecht@mpi-sb.mpg.de|Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. mario.albrecht@mpi-sb.mpg.de', 'Germany|Germany', 0, 'Amino Acid Sequence|Basidiomycota|Carbohydrate Dehydrogenases|Conserved Sequence|Databases, Protein|Fungal Proteins|Glucose Dehydrogenases|Models, Molecular|Molecular Sequence Data|Oxidoreductases|Protein Conformation|Protein Structure, Secondary|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Species Specificity', 'Journal Article', '10.1093/bioinformatics/btg140', '12835264', 'Fungal pyranose oxidase is a flavoenzyme whose preferred substrate among several monosaccharides is D-glucose. After a comprehensive analysis of conserved features in a structure-based multiple sequence alignment of homologous proteins, we could classify this enzyme into the GMC oxidoreductase family. The identified homology also suggests a three-dimensional protein structure similar to the functionally related glucose oxidase.'),
(70688, 2003, 'bio', 'Fast sequence clustering using a suffix array algorithm', 'Malde, Ketil|Coward, Eivind|Jonassen, Inge', 'Department of Informatics, University of Bergen, HIB, N5020 Norway. ketil@ii.uib.no|Department of Informatics, University of Bergen, HIB, N5020 Norway. ketil@ii.uib.no|Department of Informatics, University of Bergen, HIB, N5020 Norway. ketil@ii.uib.no', 'Norway|Norway|Norway', 30, 'Algorithms|Cluster Analysis|Expressed Sequence Tags|Gene Expression Profiling|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis|Sequence Homology', 'Comparative Study', '10.1093/bioinformatics/btg138', '12835265', 'Efficient clustering is important for handling the large amount of available EST sequences. Most contemporary methods are based on some kind of all-against-all comparison, resulting in a quadratic time complexity. A different approach is needed to keep up with the rapid growth of EST data.'),
(70689, 2003, 'bio', 'A Bayesian network approach to operon prediction', 'Bockhorst, Joseph|Craven, Mark|Page, David|Shavlik, Jude|Glasner, Jeremy', 'Department of Biostatistics and Medical Informatics,University of Wisconsin, 1300 University Avenue, Madison, Wisconsin 53706, USA. joebock@biostat.wisc.edu|Department of Biostatistics and Medical Informatics,University of Wisconsin, 1300 University Avenue, Madison, Wisconsin 53706, USA. joebock@biostat.wisc.edu|Department of Biostatistics and Medical Informatics,University of Wisconsin, 1300 University Avenue, Madison, Wisconsin 53706, USA. joebock@biostat.wisc.edu|Department of Biostatistics and Medical Informatics,University of Wisconsin, 1300 University Avenue, Madison, Wisconsin 53706, USA. joebock@biostat.wisc.edu|Department of Biostatistics and Medical Informatics,University of Wisconsin, 1300 University Avenue, Madison, Wisconsin 53706, USA. joebock@biostat.wisc.edu', 'United States|United States|United States|United States|United States', 74, 'Algorithms|Bayes Theorem|Escherichia coli|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Genome, Bacterial|Operon|Promoter Regions, Genetic|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg147', '12835266', 'In order to understand transcription regulation in a given prokaryotic genome, it is critical to identify operons, the fundamental units of transcription, in such species. While there are a growing number of organisms whose sequence and gene coordinates are known, by and large their operons are not known.'),
(70690, 2003, 'bio', 'Estimating the occurrence of false positives and false negatives in microarray studies by approximating and partitioning the empirical distribution of p-values', 'Pounds, Stan|Morris, Stephan W', 'Department of Biostatistics, St. Jude Childrens Research Hospital, 332 N. Lauderdale St., Memphis, TN 38105-2794, USA. stanley.pounds@stjude.org|Department of Biostatistics, St. Jude Childrens Research Hospital, 332 N. Lauderdale St., Memphis, TN 38105-2794, USA. stanley.pounds@stjude.org', 'United States|United States', 277, 'Adaptor Proteins, Signal Transducing|Algorithms|Animals|B-Cell CLL-Lymphoma 10 Protein|B-Lymphocytes|False Negative Reactions|False Positive Reactions|Gene Expression Profiling|Mice|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis', 'Evaluation Studies', '10.1093/bioinformatics/btg148', '12835267', 'The occurrence of false positives and false negatives in a microarray analysis could be easily estimated if the distribution of p-values were approximated and then expressed as a mixture of null and alternative densities. Essentially any distribution of p-values can be expressed as such a mixture by extracting a uniform density from it.'),
(70691, 2003, 'bio', 'A mathematical programming approach for gene selection and tissue classification', 'Sun, Minghe|Xiong, Momiao', 'Department of Management Science and Statistics, College of Business, The University of Texas at San Antonio, San Antonio, TX 78249-0632, USA. msun@utsa.edu|Department of Management Science and Statistics, College of Business, The University of Texas at San Antonio, San Antonio, TX 78249-0632, USA. msun@utsa.edu', 'United States|United States', 18, 'Algorithms|Cluster Analysis|Connective Tissue Cells|Gene Expression Profiling|Humans|Leukemia, Myeloid, Acute|Models, Genetic|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis', 'Comparative Study', '10.1093/bioinformatics/btg145', '12835268', 'Extracting useful information from expression levels of thousands of genes generated with microarray technology needs a variety of analytical techniques. Mathematical programming approaches for classification analysis outperform parametric methods when the data depart from assumptions underlying these methods. Therefore, a mathematical programming approach is developed for gene selection and tissue classification using gene expression profiles.'),
(70692, 2003, 'bio', 'Graphical methods for class prediction using dimension reduction techniques on DNA microarray data', 'Bura, Efstathia|Pfeiffer, Ruth M', 'Department of Statistics, The George Washington University, 2201 G Street NW, Washington, DC 20052, USA. ebura@gwu.edu|Department of Statistics, The George Washington University, 2201 G Street NW, Washington, DC 20052, USA. ebura@gwu.edu', 'United States|United States', 45, 'Algorithms|BRCA1 Protein|BRCA2 Protein|Breast Neoplasms|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Regression Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis', 'Comparative Study', '10.1093/bioinformatics/btg150', '12835269', 'We introduce simple graphical classification and prediction tools for tumor status using gene-expression profiles. They are based on two dimension estimation techniques sliced average variance estimation (SAVE) and sliced inverse regression (SIR). Both SAVE and SIR are used to infer on the dimension of the classification problem and obtain linear combinations of genes that contain sufficient information to predict class membership, such as tumor type. Plots of the estimated directions as well as numerical thresholds estimated from the plots are used to predict tumor classes in cDNA microarrays and the performance of the class predictors is assessed by cross-validation. A microarray simulation study is carried out to compare the power and predictive accuracy of the two methods.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70693, 2003, 'bio', 'Unsupervised feature selection via two-way ordering in gene expression analysis', 'Ding, Chris H Q', 'NERSC Division, Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720, USA. chqding@lbl.gov', 'United States', 47, 'Algorithms|Analysis of Variance|Cluster Analysis|Colonic Neoplasms|Gene Expression Profiling|Humans|Leukemia|Pattern Recognition, Automated|Principal Component Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis|Sequence Homology', 'Comparative Study', '10.1093/bioinformatics/btg149', '12835270', 'Selection of genes most relevant and informative for certain phenotypes is an important aspect in gene expression analysis. Most current methods select genes based on known phenotype information. However, certain set of genes may correspond to new phenotypes which are yet unknown, and it is important to develop novel effective selection methods for their discovery without using any prior phenotype information.'),
(70694, 2003, 'bio', 'Local structure prediction with local structure-based sequence profiles', 'Yang, An-Suei|Wang, Lu-yong', 'Department of Pharmacology, Columbia Genome Center, and Center for Computational Biology and Bioinformatics, Columbia University, 630 West 168th street, PH 7 W Room 318, New York, NY 10032, USA. ay1@columbia.edu|Department of Pharmacology, Columbia Genome Center, and Center for Computational Biology and Bioinformatics, Columbia University, 630 West 168th street, PH 7 W Room 318, New York, NY 10032, USA. ay1@columbia.edu', 'United States|United States', 37, 'Amino Acid Sequence|Computer Simulation|Crystallography|Databases, Protein|Models, Molecular|Molecular Sequence Data|Oligopeptides|Protein Conformation|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg151', '12835271', 'A large body of experimental and theoretical evidence suggests that local structural determinants are frequently encoded in short segments of protein sequence. Although the local structural information, once recognized, is particularly useful in protein structural and functional analyses, it remains a difficult problem to identify embedded local structural codes based solely on sequence information.'),
(70695, 2003, 'bio', 'Investigating semantic similarity measures across the Gene Ontology: the relationship between sequence and annotation', 'Lord, P W|Stevens, R D|Brass, A|Goble, C A', 'Department of Computer Science, University of Manchester, Oxford Road, Manchester, M13 9PL, UK. p.lord@russet.org.uk|Department of Computer Science, University of Manchester, Oxford Road, Manchester, M13 9PL, UK. p.lord@russet.org.uk|Department of Computer Science, University of Manchester, Oxford Road, Manchester, M13 9PL, UK. p.lord@russet.org.uk|Department of Computer Science, University of Manchester, Oxford Road, Manchester, M13 9PL, UK. p.lord@russet.org.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 599, 'Artificial Intelligence|Databases, Factual|Databases, Genetic|Documentation|Gene Expression Profiling|Humans|Information Storage and Retrieval|Natural Language Processing|Phylogeny|Proteins|Reproducibility of Results|Semantics|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Statistics as Topic|Terminology as Topic', 'Comparative Study', '10.1093/bioinformatics/btg153', '12835272', 'Many bioinformatics data resources not only hold data in the form of sequences, but also as annotation. In the majority of cases, annotation is written as scientific natural language: this is suitable for humans, but not particularly useful for machine processing. Ontologies offer a mechanism by which knowledge can be represented in a form capable of such processing. In this paper we investigate the use of ontological annotation to measure the similarities in knowledge content or semantic similarity between entries in a data resource. These allow a bioinformatician to perform a similarity measure over annotation in an analogous manner to those performed over sequences. A measure of semantic similarity for the knowledge component of bioinformatics resources should afford a biologist a new tool in their repertoire of analyses.'),
(70696, 2003, 'bio', 'A comparison of parametric versus permutation methods with applications to general and temporal microarray gene expression data', 'Xu, Ronghui|Li, Xiaochun', 'Department of Biostatistics, Harvard School of Public Health and Dana-Farber Cancer Institute, 44 Binney Street, Boston, MA 02115, USA. rxu@jimmy.harvard.edu|Department of Biostatistics, Harvard School of Public Health and Dana-Farber Cancer Institute, 44 Binney Street, Boston, MA 02115, USA. rxu@jimmy.harvard.edu', 'United States|United States', 22, 'Algorithms|Analysis of Variance|Gene Expression Profiling|Leukemia|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis', 'Comparative Study', '10.1093/bioinformatics/btg155', '12835273', 'In analyses of microarray data with a design of different biological conditions, ranking genes by their differential importance is often desired so that biologists can focus research on a small subset of genes that are most likely related to the experiment conditions. Permutation methods are often recommended and used, in place of their parametric counterparts, due to the small sample sizes of microarray experiments and possible non-normality of the data. The recommendations, however, are based on classical knowledge in the hypothesis test setting.'),
(70697, 2003, 'bio', 'The DynDom database of protein domain motions', 'Lee, Richard A|Razaz, Moe|Hayward, Steven', 'Royal Society-Wolfson Bioinformatics Laboratory, School of Computing Sciences, University of East Anglia, Norwich NR4 7TJ, UK.|Royal Society-Wolfson Bioinformatics Laboratory, School of Computing Sciences, University of East Anglia, Norwich NR4 7TJ, UK.|Royal Society-Wolfson Bioinformatics Laboratory, School of Computing Sciences, University of East Anglia, Norwich NR4 7TJ, UK.', 'United Kingdom|United Kingdom|United Kingdom', 80, 'Crystallography|Databases, Protein|Information Storage and Retrieval|Internet|Models, Molecular|Protein Conformation|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg137', '12835274', 'A relational database has been developed based on the results from the application of the DynDom program to a number of proteins for which multiple X-ray conformers are available. The database is populated via a web-based tool that allows visitors to the website to run the DynDom program server-side by selecting pairs of X-ray conformers by Protein Data Bank code and chain identifier.'),
(70698, 2003, 'bio', 'TableView: portable genomic data visualization', 'Johnson, James E|Stromvik, Martina V|Silverstein, Kevin A T|Crow, John A|Shoop, Elizabeth|Retzel, Ernest F', 'Center for Computational Genomics and Bioinformatics, University of Minnesota, Minneapolis, MN 55455, USA. tableview@ccgb.umn.edu|Center for Computational Genomics and Bioinformatics, University of Minnesota, Minneapolis, MN 55455, USA. tableview@ccgb.umn.edu|Center for Computational Genomics and Bioinformatics, University of Minnesota, Minneapolis, MN 55455, USA. tableview@ccgb.umn.edu|Center for Computational Genomics and Bioinformatics, University of Minnesota, Minneapolis, MN 55455, USA. tableview@ccgb.umn.edu|Center for Computational Genomics and Bioinformatics, University of Minnesota, Minneapolis, MN 55455, USA. tableview@ccgb.umn.edu|Center for Computational Genomics and Bioinformatics, University of Minnesota, Minneapolis, MN 55455, USA. tableview@ccgb.umn.edu', 'United States|United States|United States|United States|United States|United States', 8, 'Computer Graphics|Database Management Systems|Databases, Genetic|Hypermedia|Information Storage and Retrieval|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg136', '12835275', 'TableView is a generalized scientific visualization program for exploration of various biological data, including EST, SAGE, microarray and annotation data. Written in Java, TableView is portable, is easily used together with other software including DBMSs and is versatile enough to be applied to any tabular data'),
(70699, 2003, 'bio', 'Longest biased interval and longest non-negative sum interval', 'Allison, Lloyd', 'School of Computer Science and Software Engineering, Monash University, Clayton, Victoria, Australia 3800. lloyd@bruce.cs.monash.edu.au', 'Australia', 0, 'Algorithms|Models, Statistical|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btg135', '12835276', 'Described is an algorithm to find the longest interval having at least a specified minimum bias in a sequence of characters (bases, amino acids), e.g. at least 0.95 (A+T)-rich. It is based on an algorithm to find the longest interval having a non-negative sum in a sequence of positive and negative numbers. In practice, it runs in linear time, this can be guaranteed if the bias is rational.'),
(70700, 2003, 'bio', 'GeneComber: combining outputs of gene prediction programs for improved results', 'Shah, Sohrab P|McVicker, Graham P|Mackworth, Alan K|Rogic, Sanja|Ouellette, B F Francis', 'UBC Bioinformatics Centre, University of British Columbia, 950 28th Ave W, Vancouver, BC V5Z4H4 Canada.|UBC Bioinformatics Centre, University of British Columbia, 950 28th Ave W, Vancouver, BC V5Z4H4 Canada.|UBC Bioinformatics Centre, University of British Columbia, 950 28th Ave W, Vancouver, BC V5Z4H4 Canada.|UBC Bioinformatics Centre, University of British Columbia, 950 28th Ave W, Vancouver, BC V5Z4H4 Canada.|UBC Bioinformatics Centre, University of British Columbia, 950 28th Ave W, Vancouver, BC V5Z4H4 Canada.', 'Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Hypermedia|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg139', '12835277', 'We recently demonstrated that combining the output from Genscan and HMMgene can provide increased accuracy of gene predictions. We have created a robust software system that runs algorithms previously described on DNA sequences and provides a public web interface to the system for use by the biological community worldwide. The GeneComber system performs ab initio gene prediction by first taking a user inputted DNA sequence and running Genscan and HMMgene. The outputs of Genscan and HMMgene are then integrated using the EUI, GI and EUI_frame algorithms. All results are then stored into a relational database management system (RDBMS) and can then be retrieved through a web interface. The web interface provides a unified view of the GeneComber predictions by graphically overlaying outputs from Genscan, HMMgene, EUI, GI and EUI_frame. Outputs can also be retrieved in general feature format (GFF) or FASTA format. The software is written in the Perl programming language and is both dependent on and interoperable with the Bioperl toolkit. It includes high-level application programming interfaces (APIs) to run Genscan, HMMgene and a database API to insert prediction results into an RDBMS. The APIs are assembled into the genecomber script which is executed by the web interface or can be run directly from the Unix command line. The web interface is written in PHP and is structured so as to be easily modified for viewing data from any database that stores gene structures.'),
(70701, 2003, 'bio', 'Calculation of helix packing angles in protein structures', 'Dalton, James A R|Michalopoulos, Ioannis|Westhead, David R', 'School of Biochemistry and Molecular Biology, University of Leeds, Leeds, West Yorkshire LS2 9JT, UK.|School of Biochemistry and Molecular Biology, University of Leeds, Leeds, West Yorkshire LS2 9JT, UK.|School of Biochemistry and Molecular Biology, University of Leeds, Leeds, West Yorkshire LS2 9JT, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Crystallography|Models, Molecular|Programming Languages|Protein Conformation|Protein Folding|Protein Structure, Secondary|Proteins|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg141', '12835278', 'Software is presented for the calculation of packing angles and geometry of helical secondary structure elements in protein structures.'),
(70702, 2003, 'bio', 'HaploBlockFinder: haplotype block analyses', 'Zhang, Kun|Jin, Li', 'Center for Genome Information, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45267, USA.|Center for Genome Information, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45267, USA.', 'United States|United States', 98, 'Algorithms|Chromosome Mapping|Gene Expression Profiling|Haplotypes|Linkage Disequilibrium|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg142', '12835279', 'Recent studies have unveiled discrete block-like structures of linkage disequilibrium (LD) in the human genome. We have developed a set of computer programs to analyze the block-like LD structures (haplotype blocks) based on haplotype data. Three definitions of haplotype block are supported, including minimal LD range, no historic recombination, and chromosome coverage. Tagged SNPs that uniquely distinguish common haplotypes are identified. A greedy algorithm was used to improve the efficiency. Two separate utilities were also provided to assist visual inspection of haplotype block structure and pattern of linkage disequilibrium.'),
(70703, 2003, 'bio', 'Ismb 2003 Proceedings of the 11th International Conference on Intelligent Systems for Molecular Biology Brisbane, Australia, June 29-July 3, 2003', '-', '-', '-', 0, 'Computational Biology', 'Congress', '10.1093/bioinformatics/btg1048', '12855430', '-'),
(70704, 2003, 'bio', 'Bayesian gene/species tree reconciliation and orthology analysis using MCMC', 'Arvestad, Lars|Berglund, Ann-Charlotte|Lagergren, Jens|Sennblad, Bengt', 'SBC and Center for Genomics and Bioinforamtics, Karolinska Instituet, SE-171 77, Stockholm, Sweden. lars.arvestad@sbc.su.se|SBC and Center for Genomics and Bioinforamtics, Karolinska Instituet, SE-171 77, Stockholm, Sweden. lars.arvestad@sbc.su.se|SBC and Center for Genomics and Bioinforamtics, Karolinska Instituet, SE-171 77, Stockholm, Sweden. lars.arvestad@sbc.su.se|SBC and Center for Genomics and Bioinforamtics, Karolinska Instituet, SE-171 77, Stockholm, Sweden. lars.arvestad@sbc.su.se', 'Sweden|Sweden|Sweden|Sweden', 119, 'Algorithms|Animals|Bayes Theorem|Evolution, Molecular|Gene Expression Profiling|Genes, MHC Class I|Likelihood Functions|Markov Chains|Models, Genetic|Models, Statistical|Monte Carlo Method|Phylogeny|Ribosomal Proteins|Sequence Analysis, DNA|Species Specificity', 'Comparative Study', '10.1093/bioinformatics/btg1000', '12855432', 'Comparative genomics in general and orthology analysis in particular are becoming increasingly important parts of gene function prediction. Previously, orthology analysis and reconciliation has been performed only with respect to the parsimony model. This discards many plausible solutions and sometimes precludes finding the correct one. In many other areas in bioinformatics probabilistic models have proven to be both more realistic and powerful than parsimony models. For instance, they allow for assessing solution reliability and consideration of alternative solutions in a uniform way. There is also an added benefit in making model assumptions explicit and therefore making model comparisons possible. For orthology analysis, uncertainty has recently been addressed using parsimonious reconciliation combined with bootstrap techniques. However, until now no probabilistic methods have been available.'),
(70705, 2003, 'bio', 'Methods for optimizing antiviral combination therapies', 'Beerenwinkel, Niko|Lengauer, Thomas|Däumer, Martin|Kaiser, Rolf|Walter, Hauke|Korn, Klaus|Hoffmann, Daniel|Selbig, Joachim', 'Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. beerenwinkel@mpi-sb.mpg.de|Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. beerenwinkel@mpi-sb.mpg.de|Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. beerenwinkel@mpi-sb.mpg.de|Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. beerenwinkel@mpi-sb.mpg.de|Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. beerenwinkel@mpi-sb.mpg.de|Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. beerenwinkel@mpi-sb.mpg.de|Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. beerenwinkel@mpi-sb.mpg.de|Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. beerenwinkel@mpi-sb.mpg.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Anti-HIV Agents|Artificial Intelligence|Cluster Analysis|Computing Methodologies|DNA, Viral|Drug Combinations|Drug Resistance, Viral|Drug Therapy, Computer-Assisted|Gene Expression Profiling|Genome, Viral|HIV|HIV Infections|Humans|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Phenotype|Polymorphism, Genetic|Quality Control|Regression Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Clinical Trial', '10.1093/bioinformatics/btg1001', '12855433', 'Despite some progress with antiretroviral combination therapies, therapeutic success in the management of HIV-infected patients is limited. The evolution of drug-resistant genetic variants in response to therapy plays a key role in treatment failure and finding a new potent drug combination after therapy failure is considered challenging.'),
(70706, 2003, 'bio', 'Remote homology detection: a motif based approach', 'Ben-Hur, Asa|Brutlag, Douglas', 'Department of Biochemistry, B400 Beckman Center, Stanford University, CA 94305-5307, USA. asa.benhur@stanford.edu|Department of Biochemistry, B400 Beckman Center, Stanford University, CA 94305-5307, USA. asa.benhur@stanford.edu', 'United States|United States', 0, 'Algorithms|Amino Acid Motifs|Artificial Intelligence|Cluster Analysis|Computing Methodologies|Databases, Nucleic Acid|Enzymes|Nuclear Proteins|Pattern Recognition, Automated|Phosphoprotein Phosphatases|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/btg1002', '12855434', 'Remote homology detection is the problem of detecting homology in cases of low sequence similarity. It is a hard computational problem with no approach that works well in all cases.'),
(70707, 2003, 'bio', 'Predicting bacterial transcription units using sequence and expression data', 'Bockhorst, Joseph|Qiu, Yu|Glasner, Jeremy|Liu, Mingzhu|Blattner, Frederick|Craven, Mark', 'Department of Computer Sciences, University of Wisconsin, Madison, Wisconsin 53706, USA. joebock@biostat.wisc.edu|Department of Computer Sciences, University of Wisconsin, Madison, Wisconsin 53706, USA. joebock@biostat.wisc.edu|Department of Computer Sciences, University of Wisconsin, Madison, Wisconsin 53706, USA. joebock@biostat.wisc.edu|Department of Computer Sciences, University of Wisconsin, Madison, Wisconsin 53706, USA. joebock@biostat.wisc.edu|Department of Computer Sciences, University of Wisconsin, Madison, Wisconsin 53706, USA. joebock@biostat.wisc.edu|Department of Computer Sciences, University of Wisconsin, Madison, Wisconsin 53706, USA. joebock@biostat.wisc.edu', 'United States|United States|United States|United States|United States|United States', 45, 'Algorithms|Artificial Intelligence|Codon|Escherichia coli|Escherichia coli Proteins|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Operator Regions, Genetic|Promoter Regions, Genetic|Regulatory Sequences, Nucleic Acid|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Software|Terminator Regions, Genetic|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/btg1003', '12855435', 'A key aspect of elucidating gene regulation in bacterial genomes is identifying the basic units of transcription. We present a method, based on probabilistic language models, that we apply to predict operons, promoters and terminators in the genome of Escherichia coli K-12. Our approach has two key properties: (i) it provides a coherent set of predictions for related regulatory elements of various types and (ii) it takes advantage of both DNA sequence and gene expression data, including expression measurements from inter-genic probes.'),
(70708, 2003, 'bio', 'SNP and mutation discovery using base-specific cleavage and MALDI-TOF mass spectrometry', 'Böcker, Sebastian', 'SEQUENOM Inc., 3595 John Hopkins Court, San Diego, CA 92121, USA. boecker@CeBiTec.uni-bielefeld.de', 'United States', 37, 'Algorithms|Base Composition|Base Sequence|DNA|DNA Mutational Analysis|Gene Expression Profiling|Molecular Sequence Data|Nucleotides|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Comparative Study', '10.1093/bioinformatics/btg1004', '12855436', 'Single Nucleotide Polymorphisms (SNPs) are believed to contribute strongly to the genetic variability in living beings, in particular their disease or drug side effect predispositions. Mutation-induced sequence variations are playing an important role in the development of cancer, among others. From this, it is clear that SNP and mutation discovery is of great interest in todays Life Sciences. Currently, such discovery is often performed utilizing electrophoresis-based Sanger Sequencing. Discovery of SNPs can also be performed by multiple sequence alignment of publicly available sequence data, but recent studies indicate that only a small percentage of SNPs can be discovered using this approach and, in particular, that SNPs with low frequency are often missed. Other SNP discovery methods only indicate the presence of a SNP in a sample region, but fail to resolve its characterization and localization.'),
(70709, 2003, 'bio', 'Glocal alignment: finding rearrangements during alignment', 'Brudno, Michael|Malde, Sanket|Poliakov, Alexander|Do, Chuong B|Couronne, Olivier|Dubchak, Inna|Batzoglou, Serafim', 'Department of Computer Science, Stanford University, Stanford, CA 94305, USA.|Department of Computer Science, Stanford University, Stanford, CA 94305, USA.|Department of Computer Science, Stanford University, Stanford, CA 94305, USA.|Department of Computer Science, Stanford University, Stanford, CA 94305, USA.|Department of Computer Science, Stanford University, Stanford, CA 94305, USA.|Department of Computer Science, Stanford University, Stanford, CA 94305, USA.|Department of Computer Science, Stanford University, Stanford, CA 94305, USA.', 'United States|United States|United States|United States|United States|United States|United States', 216, 'Algorithms|Animals|Base Sequence|Chromosome Mapping|DNA|Gene Expression Profiling|Genome, Human|Humans|Mice|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/btg1005', '12855437', 'To compare entire genomes from different species, biologists increasingly need alignment methods that are efficient enough to handle long sequences, and accurate enough to correctly align the conserved biological features between distant species. The two main classes of pairwise alignments are global alignment, where one string is transformed into the other, and local alignment, where all locations of similarity between the two strings are returned. Global alignments are less prone to demonstrating false homology as each letter of one sequence is constrained to being aligned to only one letter of the other. Local alignments, on the other hand, can cope with rearrangements between non-syntenic, orthologous sequences by identifying similar regions in sequences, this, however, comes at the expense of a higher false positive rate due to the inability of local aligners to take into account overall conservation maps.'),
(70710, 2003, 'bio', 'Linking genotype to phenotype: the International Rice Information System (IRIS)', 'Bruskiewich, Richard M|Cosico, Alexander B|Eusebio, William|Portugal, Arllet M|Ramos, Luralyn M|Reyes, Ma Teresa|Sallan, May Ann B|Ulat, Victor Jun M|Wang, Xusheng|McNally, Kenneth L|Sackville Hamilton, Ruaraidh|McLaren, Christopher Graham', 'Biometrics and Bioinformatics Unit, International Rice Research Institute, PO Box DAP O7777, Metro Manila, Philippines. r.bruskiewich@cgiar.org|Biometrics and Bioinformatics Unit, International Rice Research Institute, PO Box DAP O7777, Metro Manila, Philippines. r.bruskiewich@cgiar.org|Biometrics and Bioinformatics Unit, International Rice Research Institute, PO Box DAP O7777, Metro Manila, Philippines. r.bruskiewich@cgiar.org|Biometrics and Bioinformatics Unit, International Rice Research Institute, PO Box DAP O7777, Metro Manila, Philippines. r.bruskiewich@cgiar.org|Biometrics and Bioinformatics Unit, International Rice Research Institute, PO Box DAP O7777, Metro Manila, Philippines. r.bruskiewich@cgiar.org|Biometrics and Bioinformatics Unit, International Rice Research Institute, PO Box DAP O7777, Metro Manila, Philippines. r.bruskiewich@cgiar.org|Biometrics and Bioinformatics Unit, International Rice Research Institute, PO Box DAP O7777, Metro Manila, Philippines. r.bruskiewich@cgiar.org|Biometrics and Bioinformatics Unit, International Rice Research Institute, PO Box DAP O7777, Metro Manila, Philippines. r.bruskiewich@cgiar.org|Biometrics and Bioinformatics Unit, International Rice Research Institute, PO Box DAP O7777, Metro Manila, Philippines. r.bruskiewich@cgiar.org|Biometrics and Bioinformatics Unit, International Rice Research Institute, PO Box DAP O7777, Metro Manila, Philippines. r.bruskiewich@cgiar.org|Biometrics and Bioinformatics Unit, International Rice Research Institute, PO Box DAP O7777, Metro Manila, Philippines. r.bruskiewich@cgiar.org|Biometrics and Bioinformatics Unit, International Rice Research Institute, PO Box DAP O7777, Metro Manila, Philippines. r.bruskiewich@cgiar.org', 'Philippines|Philippines|Philippines|Philippines|Philippines|Philippines|Philippines|Philippines|Phil', 8, 'Database Management Systems|Databases, Genetic|Gene Expression Profiling|Genotype|Information Dissemination|Information Storage and Retrieval|Internationality|Oryza|Phenotype|Plant Proteins|Software|Software Design|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg1006', '12855438', 'The International Rice Information System (IRIS, http://www.iris.irri.org) is the rice implementation of the International Crop Information System (ICIS, http://www.icis.cgiar.org), a database system for the management and integration of global information on genetic resources and germplasm improvement for any crop. Building upon the germplasm genealogy and field data components of ICIS, IRIS is being extended to handle diverse rice genomics data including: genetic mapping, genome annotation, genotype, mutant, transcripteome, proteome and metabolomic data. Users can access information in the database through stand-alone programs and WWW interfaces offering specialist views to researchers with different interests.'),
(70711, 2003, 'bio', 'Stochastic modeling of RNA pseudoknotted structures: a grammatical approach', 'Cai, Liming|Malmberg, Russell L|Wu, Yunzhou', 'Department of Computer Science, The University of Georgia, Athens, Georgia 30602, USA. cai@cs.uga.edu|Department of Computer Science, The University of Georgia, Athens, Georgia 30602, USA. cai@cs.uga.edu|Department of Computer Science, The University of Georgia, Athens, Georgia 30602, USA. cai@cs.uga.edu', 'Georgia|Georgia|Georgia', 10, 'Algorithms|Base Pairing|Base Sequence|Binding Sites|Feasibility Studies|Models, Chemical|Models, Molecular|Models, Statistical|Molecular Sequence Data|Natural Language Processing|Nucleic Acid Conformation|Pattern Recognition, Automated|RNA|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/btg1007', '12855439', 'Modeling RNA pseudoknotted structures remains challenging. Methods have previously been developed to model RNA stem-loops successfully using stochastic context-free grammars (SCFG) adapted from computational linguistics, however, the additional complexity of pseudoknots has made modeling them more difficult. Formally a context-sensitive grammar is required, which would impose a large increase in complexity.'),
(70712, 2003, 'bio', 'Fast identification and statistical evaluation of segmental homologies in comparative maps', 'Calabrese, Peter P|Chakravarty, Sugata|Vision, Todd J', 'Department of Mathematics, University of Southern California, Los Angeles, CA 90089, USA.|Department of Mathematics, University of Southern California, Los Angeles, CA 90089, USA.|Department of Mathematics, University of Southern California, Los Angeles, CA 90089, USA.', 'United States|United States|United States', 80, 'Algorithms|Arabidopsis|Base Sequence|Chromosome Mapping|Evolution, Molecular|Gene Expression Profiling|Genetic Variation|Genome|Models, Genetic|Models, Statistical|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/btg1008', '12855440', 'Chromosomal segments that share common ancestry, either through genomic duplication or species divergence, are said to be segmental homologs of one another. Their identification allows researchers to leverage knowledge of model organisms for use in other systems and is of value for studies of genome evolution. However, identification and statistical evaluation of segmental homologies can be a challenge when the segments are highly diverged.'),
(70713, 2003, 'bio', 'PSI: indexing protein structures for fast similarity search', 'Camoglu, Orhan|Kahveci, Tamer|Singh, Ambuj K', 'Department of Computer Science University of California, Santa Barbara, CA 93106, USA. orhan@cs.ucsb.edu|Department of Computer Science University of California, Santa Barbara, CA 93106, USA. orhan@cs.ucsb.edu|Department of Computer Science University of California, Santa Barbara, CA 93106, USA. orhan@cs.ucsb.edu', 'United States|United States|United States', 29, 'Algorithms|Amino Acid Sequence|Databases, Protein|Information Storage and Retrieval|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/btg1009', '12855441', 'We consider the problem of finding similarities in protein structure databases. Current techniques sequentially compare the given query protein to all of the proteins in the database to find similarities. Therefore, the cost of similarity queries increases linearly as the volume of the protein databases increase. As the sizes of experimentally determined and theoretically estimated protein structure databases grow, there is a need for scalable searching techniques.'),
(70714, 2003, 'bio', 'Combining multiple microarray studies and modeling interstudy variation', 'Choi, Jung Kyoon|Yu, Ungsik|Kim, Sangsoo|Yoo, Ook Joon', 'Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 371-1 Guseong-dong Yuseong-gu, Daejeon 305-701, Korea. jkchoi@kaist.ac.kr|Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 371-1 Guseong-dong Yuseong-gu, Daejeon 305-701, Korea. jkchoi@kaist.ac.kr|Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 371-1 Guseong-dong Yuseong-gu, Daejeon 305-701, Korea. jkchoi@kaist.ac.kr|Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 371-1 Guseong-dong Yuseong-gu, Daejeon 305-701, Korea. jkchoi@kaist.ac.kr', '-|-|-|-', 0, 'Algorithms|Bayes Theorem|Data Interpretation, Statistical|Gene Expression Profiling|Genetic Testing|Genetic Variation|Humans|Liver Neoplasms|Male|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Prostatic Neoplasms|Reproducibility of Results|Sensitivity and Specificity|Systems Integration', 'Evaluation Studies', '10.1093/bioinformatics/btg1010', '12855442', 'We have established a method for systematic integration of multiple microarray datasets. The method was applied to two different sets of cancer profiling studies. The change of gene expression in cancer was expressed as effect size, a standardized index measuring the magnitude of a treatment or covariate effect. The effect sizes were combined to obtain the estimate of the overall mean. The statistical significance was determined by a permutation test extended to multiple datasets. It was shown that the data integration promotes the discovery of small but consistent expression changes with increased sensitivity and reliability. The effect size methods provided the efficient modeling framework for addressing interstudy variation as well. Based on the result of homogeneity tests, a fixed effects model was adopted for one set of datasets that had been created in controlled experimental conditions. By contrast, a random effects model was shown to be appropriate for the other set of datasets that had been published by independent groups. We also developed an alternative modeling procedure based on a Bayesian approach, which would offer flexibility and robustness compared to the classical procedure.'),
(70715, 2003, 'bio', 'Combining NLP and probabilistic categorisation for document and term selection for Swiss-Prot medical annotation', 'Dobrokhotov, Pavel B|Goutte, Cyril|Veuthey, Anne-Lise|Gaussier, Eric', 'Swiss Institute of Bioinformatics, CMU, 1 Michel-Servet - CH-1211 Geneva 4, Switzerland. Pavel.Dobrokhotov@isb-sib.ch|Swiss Institute of Bioinformatics, CMU, 1 Michel-Servet - CH-1211 Geneva 4, Switzerland. Pavel.Dobrokhotov@isb-sib.ch|Swiss Institute of Bioinformatics, CMU, 1 Michel-Servet - CH-1211 Geneva 4, Switzerland. Pavel.Dobrokhotov@isb-sib.ch|Swiss Institute of Bioinformatics, CMU, 1 Michel-Servet - CH-1211 Geneva 4, Switzerland. Pavel.Dobrokhotov@isb-sib.ch', 'Switzerland|Switzerland|Switzerland|Switzerland', 25, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Databases, Protein|Documentation|Models, Statistical|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Proteins|PubMed', 'Comparative Study', '10.1093/bioinformatics/btg1011', '12855443', 'Searching relevant publications for manual database annotation is a tedious task. In this paper, we apply a combination of Natural Language Processing (NLP) and probabilistic classification to re-rank documents returned by PubMed according to their relevance to Swiss-Prot annotation, and to identify significant terms in the documents.'),
(70716, 2003, 'bio', 'MASS: multiple structural alignment by secondary structures', 'Dror, O|Benyamini, H|Nussinov, R|Wolfson, H', 'School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. oranit@post.tau.ac.cil|School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. oranit@post.tau.ac.cil|School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. oranit@post.tau.ac.cil|School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. oranit@post.tau.ac.cil', 'Israel|Israel|Israel|Israel', 0, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg1012', '12855444', 'We present a novel method for multiple alignment of protein structures and detection of structural motifs. To date, only a few methods are available for addressing this task. Most of them are based on a series of pairwise comparisons. In contrast, MASS (Multiple Alignment by Secondary Structures) considers all the given structures at the same time. Exploiting the secondary structure representation aids in filtering out noisy results and in making the method highly efficient and robust. MASS disregards the sequence order of the secondary structure elements. Thus, it can find non-sequential and even non-topological structural motifs. An important novel feature of MASS is subset alignment detection: It does not require that all the input molecules be aligned. Rather, MASS is capable of detecting structural motifs shared only by a subset of the molecules. Given its high efficiency and capability of detecting subset alignments, MASS is suitable for a broad range of challenging applications: It can handle large-scale protein ensembles (on the order of tens) that may be heterogeneous, noisy, topologically unrelated and contain structures of low resolution.'),
(70717, 2003, 'bio', 'Annotation of bacterial genomes using improved phylogenomic profiles', 'Enault, F|Suhre, K|Abergel, C|Poirot, O|Claverie, J-M', 'Structural and Genomic Information, CNRS-UPR 2589, 31 chemin Joseph Aiguier, 13009 Marseille, France. enault@igs.cnrs-mrs.fr|Structural and Genomic Information, CNRS-UPR 2589, 31 chemin Joseph Aiguier, 13009 Marseille, France. enault@igs.cnrs-mrs.fr|Structural and Genomic Information, CNRS-UPR 2589, 31 chemin Joseph Aiguier, 13009 Marseille, France. enault@igs.cnrs-mrs.fr|Structural and Genomic Information, CNRS-UPR 2589, 31 chemin Joseph Aiguier, 13009 Marseille, France. enault@igs.cnrs-mrs.fr|Structural and Genomic Information, CNRS-UPR 2589, 31 chemin Joseph Aiguier, 13009 Marseille, France. enault@igs.cnrs-mrs.fr', 'France|France|France|France|France', 38, 'Algorithms|Bacterial Proteins|Chromosome Mapping|Documentation|Evolution, Molecular|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Genome, Bacterial|Phylogeny|Proteome', 'Comparative Study', '10.1093/bioinformatics/btg1013', '12855445', 'Phylogenomic profiling is a large-scale comparative genomic method used to infer protein function from evolutionary information first described in a binary form by Pellegrini et al. (1999). Here, we propose improvements of this approach including the use of normalized Blastp bit scores, a normalization of the matrix of profiles to take into account the evolutionary distances between bacteria, the definition of a phylogenomic neighborhood based on continuous pairwise distances between genes and an original annotation procedure including the computation of a p-value for each functional assignment.'),
(70718, 2003, 'bio', 'Chain functions and scoring functions in genetic networks', 'Gat-Viks, I|Shamir, R', 'School of Computer Science, Tel-Aviv University, Tel-Aviv 69978, Israel. iritg@post.tau.ac.il|School of Computer Science, Tel-Aviv University, Tel-Aviv 69978, Israel. iritg@post.tau.ac.il', 'Israel|Israel', 29, 'Galactose|Gene Expression Regulation|Models, Genetic|Multienzyme Complexes|Regulatory Sequences, Nucleic Acid|Signal Transduction|Transcription Factors|Transcription, Genetic|Yeasts', 'Comparative Study', '10.1093/bioinformatics/btg1014', '12855446', 'One of the grand challenges of system biology is to reconstruct the network of regulatory control among genes and proteins. High throughput data, particularly from expression experiments, may gradually make this possible in the future. Here we address two key ingredients in any such reverse engineering effort: The choice of a biologically relevant, yet restricted, set of potential regulation functions, and the appropriate score to evaluate candidate regulatory relations. We propose a set of regulation functions which we call chain functions, and argue for their ubiquity in biological networks. We analyze their complexity and show that their number is exponentially smaller than all boolean functions of the same dimension. We define two new scores: one evaluating the fitness of a candidate set of regulators of a particular gene, and the other evaluating a candidate function. Both scores use established statistical methods. Finally, we test our methods on experimental gene expression data from the yeast galactose pathway. We show the utility of using chain functions and the improved inference using our scores in comparison to several extant scores. We demonstrate that the combined use of the two scores gives an extra advantage. We expect both chain functions and the new scores to be helpful in future attempts to infer regulatory networks.'),
(70719, 2003, 'bio', 'Widespread predicted nonsense-mediated mRNA decay of alternatively-spliced transcripts of human normal and disease genes', 'Green, Richard E|Lewis, Benjamin P|Hillman, R Tyler|Blanchette, Marco|Lareau, Liana F|Garnett, Aaron T|Rio, Donald C|Brenner, Steven E', 'Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA.|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA.|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA.|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA.|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA.|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA.|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA.|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 126, 'Alternative Splicing|Alzheimer Disease|Codon, Nonsense|Gene Expression Regulation|Genetic Predisposition to Disease|Genetic Testing|Humans|Lymphoma|RNA Splice Sites|RNA Stability|RNA, Messenger|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/btg1015', '12855447', 'We have recently shown that a third of reliably-inferred alternative mRNA isoforms are candidates for nonsense-mediated mRNA decay (NMD), an mRNA surveillance system (Lewis et al., 2003, PROC: Natl Acad. Sci. USA, 100, 189-192). Rather than being translated to yield protein, these transcripts are expected to be degraded and may be subject to regulated unproductive splicing and translation (RUST). Our initial experimental studies are consistent with these predictions and suggest an unappreciated role for NMD in several human diseases.'),
(70720, 2003, 'bio', 'Detecting protein sequence conservation via metric embeddings', 'Halperin, E|Buhler, J|Karp, R|Krauthgamer, R|Westover, B', 'International Computer Science Institute and Computer Science Division, University of California, Berkeley, CA 94720, USA. eran@eecs.berkeley.edu|International Computer Science Institute and Computer Science Division, University of California, Berkeley, CA 94720, USA. eran@eecs.berkeley.edu|International Computer Science Institute and Computer Science Division, University of California, Berkeley, CA 94720, USA. eran@eecs.berkeley.edu|International Computer Science Institute and Computer Science Division, University of California, Berkeley, CA 94720, USA. eran@eecs.berkeley.edu|International Computer Science Institute and Computer Science Division, University of California, Berkeley, CA 94720, USA. eran@eecs.berkeley.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Conserved Sequence|Databases, Protein|Molecular Sequence Data|Proteins|Proteome|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg1016', '12855448', 'Comparing two protein databases is a fundamental task in biosequence annotation. Given two databases, one must find all pairs of proteins that align with high score under a biologically meaningful substitution score matrix, such as a BLOSUM matrix (Henikoff and Henikoff, 1992). Distance-based approaches to this problem map each peptide in the database to a point in a metric space, such that peptides aligning with higher scores are mapped to closer points. Many techniques exist to discover close pairs of points in a metric space efficiently, but the challenge in applying this work to proteomic comparison is to find a distance mapping that accurately encodes all the distinctions among residue pairs made by a proteomic score matrix. Buhler (2002) proposed one such mapping but found that it led to a relatively inefficient algorithm for protein-protein comparison.'),
(70721, 2003, 'bio', 'Sensitive pattern discovery with fuzzy alignments of distantly related proteins', 'Heger, Andreas|Holm, Liisa', 'Institute of Biotechnology, P.O. Box 56, 00014 University of Helsinki Finland.|Institute of Biotechnology, P.O. Box 56, 00014 University of Helsinki Finland.', 'Finland|Finland', 0, 'Algorithms|Amino Acid Sequence|Cluster Analysis|Evolution, Molecular|Fuzzy Logic|Gene Expression Profiling|Models, Chemical|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Urease', 'Journal Article', '10.1093/bioinformatics/btg1017', '12855449', 'Evolutionary comparison leads to efficient functional characterisation of hypothetical proteins. Here, our goal is to map specific sequence patterns to putative functional classes. The evolutionary signal stands out most clearly in a maximally diverse set of homologues. This diversity, however, leads to a number of technical difficulties. The targeted patterns-as gleaned from structure comparisons-are too sparse for statistically significant signals of sequence similarity and accurate multiple sequence alignment.'),
(70722, 2003, 'bio', 'Deriving phylogenetic trees from the similarity analysis of metabolic pathways', 'Heymans, Maureen|Singh, Ambuj K', 'Department of Computer Science, University of California, Santa Barbara, CA 93106, USA.|Department of Computer Science, University of California, Santa Barbara, CA 93106, USA.', 'United States|United States', 0, 'Algorithms|Carbohydrate Metabolism|Carbohydrates|Citric Acid Cycle|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Glycolysis|Metabolism|Models, Biological|Multienzyme Complexes|Pattern Recognition, Automated|Phylogeny|Signal Transduction|Software', 'Comparative Study', '10.1093/bioinformatics/btg1018', '12855450', 'Comparative analysis of metabolic pathways in different genomes can give insights into the understanding of evolutionary and organizational relationships among species. This type of analysis allows one to measure the evolution of complete processes (with different functional roles) rather than the individual elements of a conventional analysis. We present a new technique for the phylogenetic analysis of metabolic pathways based on the topology of the underlying graphs. A distance measure between graphs is defined using the similarity between nodes of the graphs and the structural relationship between them. This distance measure is applied to the enzyme-enzyme relational graphs derived from metabolic pathways. Using this approach, pathways and group of pathways of different organisms are compared to each other and the resulting distance matrix is used to obtain a phylogenetic tree.'),
(70723, 2003, 'bio', 'Using guide trees to construct multiple-sequence evolutionary HMMs', 'Holmes, I', 'Department of Statistics, University of Oxford. 1 South Parks Road, Oxford OX1 3TG, UK.', 'United Kingdom', 35, 'Algorithms|Cluster Analysis|Evolution, Molecular|Gene Expression Profiling|Gene Expression Regulation|Markov Chains|Models, Genetic|Models, Statistical|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology|Software', 'Comparative Study', '10.1093/bioinformatics/btg1019', '12855451', 'Score-based progressive alignment algorithms do dynamic programming on successive branches of a guide tree. The analogous probabilistic construct is an Evolutionary HMM. This is a multiple-sequence hidden Markov model (HMM) made by combining transducers (conditionally normalised Pair HMMs) on the branches of a phylogenetic tree.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70724, 2003, 'bio', 'Protein structure prediction via combinatorial assembly of sub-structural units', 'Inbar, Yuval|Benyamini, Hadar|Nussinov, Ruth|Wolfson, Haim J', 'School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. inbaryuv@tau.ac.il|School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. inbaryuv@tau.ac.il|School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. inbaryuv@tau.ac.il|School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. inbaryuv@tau.ac.il', 'Israel|Israel|Israel|Israel', 0, 'Algorithms|Binding Sites|Combinatorial Chemistry Techniques|Computer Simulation|Glucosyltransferases|Models, Chemical|Models, Molecular|Protein Binding|Protein Conformation|Protein Structure, Tertiary|Protein Subunits|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg1020', '12855452', 'Following the hierarchical nature of protein folding, we propose a three-stage scheme for the prediction of a protein structure from its sequence. First, the sequence is cut to fragments that are each assigned a structure. Second, the assigned structures are combinatorially assembled to form the overall 3D organization. Third, highly ranked predicted arrangements are completed and refined. This work focuses on the second stage of this scheme: the combinatorial assembly. We present CombDock, a combinatorial docking algorithm. CombDock gets an ordered set of protein sub-structures and predicts the inter-contacts that define their overall organization. We reduce the combinatorial assembly to a graph-theory problem, and give a heuristic polynomial solution to this computationally hard problem. We applied CombDock to various examples of structural units of two types: protein domains and building blocks, which are relatively stable sub-structures of domains. Moreover, we tested CombDock using increasingly distorted input, where the native structural units were replaced by similarly folded units extracted from homologous proteins and, in the more difficult cases, from globally unrelated proteins. The algorithm is robust, showing low sensitivity to input distortion. This suggests that CombDock is a useful tool in protein structure prediction that may be applied to large target proteins.'),
(70725, 2003, 'bio', 'Identification of functional clusters of transcription factor binding motifs in genome sequences: the MSCAN algorithm', 'Johansson, O|Alkema, W|Wasserman, W W|Lagergren, J', 'Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093-0114, USA.|Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093-0114, USA.|Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093-0114, USA.|Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093-0114, USA.', 'United States|United States|United States|United States', 69, 'Algorithms|Amino Acid Motifs|Animals|Cells, Cultured|Cluster Analysis|Culture Techniques|Gene Expression Profiling|Gene Expression Regulation|Humans|Liver|Muscle, Skeletal|Protein Binding|Proteome|Regulatory Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology|Takifugu|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/btg1021', '12855453', 'The identification of regulatory control regions within genomes is a major challenge. Studies have demonstrated that regulating regions can be described as locally dense clusters or modules of cis-acting transcription factor binding sites (TFBS). For well-described biological contexts, it is possible to train predictive algorithms to discern novel modules in genome sequences. However, utility of module detection methods has been severely limited by insufficient training data. For only a few tissues can one obtain sufficient numbers of literature-derived regulatory modules.'),
(70726, 2003, 'bio', 'Complexity management in visualizing protein interaction networks', 'Ju, Byong-Hyon|Han, Kyungsook', 'School of Computer Science & Engineering, Inha University, Inchon 402-751, Korea.|School of Computer Science & Engineering, Inha University, Inchon 402-751, Korea.', '-|-', 7, 'Algorithms|Computer Graphics|Information Storage and Retrieval|Protein Interaction Mapping|Proteins|Signal Transduction|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg1022', '12855454', 'Protein-protein interaction networks often consist of thousands of nodes or more. This severely limits the utility of many graph drawing tools because they become too slow for an interactive analysis of the networks and because they produce cluttered drawings with many edge crossings.'),
(70727, 2003, 'bio', 'GENIA corpus--semantically annotated corpus for bio-textmining', 'Kim, J-D|Ohta, T|Tateisi, Y|Tsujii, J', 'CREST, Japan Science and Technology Corporation, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.|CREST, Japan Science and Technology Corporation, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.|CREST, Japan Science and Technology Corporation, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.|CREST, Japan Science and Technology Corporation, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.', 'Japan|Japan|Japan|Japan', 132, 'Abstracting and Indexing as Topic|Biology|Computational Biology|Database Management Systems|Databases, Bibliographic|Documentation|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Periodicals as Topic|Terminology as Topic', 'Journal Article', '10.1093/bioinformatics/btg1023', '12855455', 'Natural language processing (NLP) methods are regarded as being useful to raise the potential of text mining from biological literature. The lack of an extensively annotated corpus of this literature, however, causes a major bottleneck for applying NLP techniques. GENIA corpus is being developed to provide reference materials to let NLP techniques work for bio-textmining.'),
(70728, 2003, 'bio', 'Predicting phenotype from patterns of annotation', 'King, Oliver D|Lee, Jeffrey C|Dudley, Aimée M|Janse, Daniel M|Church, George M|Roth, Frederick P', 'Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 250 Longwood Avenue, Boston, Massachusetts, 02115, USA.|Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 250 Longwood Avenue, Boston, Massachusetts, 02115, USA.|Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 250 Longwood Avenue, Boston, Massachusetts, 02115, USA.|Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 250 Longwood Avenue, Boston, Massachusetts, 02115, USA.|Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 250 Longwood Avenue, Boston, Massachusetts, 02115, USA.|Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 250 Longwood Avenue, Boston, Massachusetts, 02115, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Databases, Genetic|Documentation|Gene Expression Profiling|Pattern Recognition, Automated|Phenotype|Saccharomyces cerevisiae|Saccharomycetales', 'Comparative Study', '10.1093/bioinformatics/btg1024', '12855456', 'Predicting the outcome of specific experiments (such as the growth of a particular mutant strain in a particular medium) has the potential to allow researchers to devote resources to experiments with higher expected numbers of hits.'),
(70729, 2003, 'bio', 'Detection and validation of single gene inversions', 'Lefebvre, J F|El-Mabrouk, N|Tillier, E|Sankoff, D', 'Département dinformatique et recherche opérationnelle, Université de Montréal, CP 6128 succ. Centre-ville, Montréal, Québec H3C 3J7, Canada.|Département dinformatique et recherche opérationnelle, Université de Montréal, CP 6128 succ. Centre-ville, Montréal, Québec H3C 3J7, Canada.|Département dinformatique et recherche opérationnelle, Université de Montréal, CP 6128 succ. Centre-ville, Montréal, Québec H3C 3J7, Canada.|Département dinformatique et recherche opérationnelle, Université de Montréal, CP 6128 succ. Centre-ville, Montréal, Québec H3C 3J7, Canada.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Chromosome Inversion|Chromosome Mapping|DNA Mutational Analysis|Gene Expression Profiling|Genetic Variation|Genome, Bacterial|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg1025', '12855457', 'The biologically meaningful algorithmic study of genome rearrangement should take into account the distribution of sizes of the rearranged genomic fragments. In particular, it is important to know the prevalence of short inversions in order to understand the patterns of gene order disruption observed in comparative genomics.'),
(70730, 2003, 'bio', 'Predicting protein function from protein/protein interaction data: a probabilistic approach', 'Letovsky, Stanley|Kasif, Simon', 'Bioinformatics Program and Department of Biomedical Engineering, Boston University, 44 Cummington St., Boston, MA 02215, USA. sletovsky@aol.com|Bioinformatics Program and Department of Biomedical Engineering, Boston University, 44 Cummington St., Boston, MA 02215, USA. sletovsky@aol.com', 'United States|United States', 288, 'Algorithms|Databases, Protein|Models, Biological|Models, Statistical|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg1026', '12855458', 'The development of experimental methods for genome scale analysis of molecular interaction networks has made possible new approaches to inferring protein function. This paper describes a method of assigning functions based on a probabilistic analysis of graph neighborhoods in a protein-protein interaction network. The method exploits the fact that graph neighbors are more likely to share functions than nodes which are not neighbors. A binomial model of local neighbor function labeling probability is combined with a Markov random field propagation algorithm to assign function probabilities for proteins in the network.'),
(70731, 2003, 'bio', 'An ENSEMBLE machine learning approach for the prediction of all-alpha membrane proteins', 'Martelli, Pier Luigi|Fariselli, Piero|Casadio, Rita', 'Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy.|Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy.|Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy.', 'Italy|Italy|Italy', 72, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Markov Chains|Membrane Proteins|Models, Chemical|Models, Molecular|Models, Statistical|Molecular Sequence Data|Protein Conformation|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg1027', '12855459', 'All-alpha membrane proteins constitute a functionally relevant subset of the whole proteome. Their content ranges from about 10 to 30% of the cell proteins, based on sequence comparison and specific predictive methods. Due to the paucity of membrane proteins solved with atomic resolution, the training/testing sets of predictive methods for protein topography and topology routinely include very few well-solved structures mixed with a hundred proteins known with low resolution. Moreover, available predictors fail in predicting recently crystallised membrane proteins (Chen et al., 2002). Presently the number of well-solved membrane proteins comprises some 59 chains of low sequence homology. It is therefore possible to train/test predictors only with the set of proteins known with atomic resolution and evaluate more thoroughly the performance of different methods.'),
(70732, 2003, 'bio', 'Talisman--rapid application development for the grid', 'Oinn, Thomas M', 'EMBL European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Essex, CB10 1SD, UK. tmo@ebi.ac.uk', 'United Kingdom', 0, 'Computational Biology|Computer Systems|Computing Methodologies|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Internet|Online Systems|Software|Software Design|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btg1028', '12855460', 'In order to make use of the emerging grid and network services offered by various institutes and mandated by many current research projects, some kind of user accessible client is required. In contrast with attempts to build generic workbenches, Talisman is designed to allow a bioinformatics expert to rapidly build custom applications, immediately visible using standard web technology, for users who wish to concentrate on the biology of their problem rather than the informatics aspects. As a component of the MyGrid project, it is intended to allow access to arbitrary resources, including but not limited to relational, object and flat file data sources, analysis programs and grid based storage, tracking and distributed annotation systems.'),
(70733, 2003, 'bio', 'APDB: a novel measure for benchmarking sequence alignment methods without reference alignments', 'OSullivan, Orla|Zehnder, Mark|Higgins, Des|Bucher, Philipp|Grosdidier, Aurelien|Notredame, Cédric', 'Department of Biochemistry, University College, Cork, Ireland.|Department of Biochemistry, University College, Cork, Ireland.|Department of Biochemistry, University College, Cork, Ireland.|Department of Biochemistry, University College, Cork, Ireland.|Department of Biochemistry, University College, Cork, Ireland.|Department of Biochemistry, University College, Cork, Ireland.', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland', 27, 'Algorithms|Amino Acid Sequence|Benchmarking|Molecular Sequence Data|Reference Standards|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology|Software|Software Validation', 'Comparative Study', '10.1093/bioinformatics/btg1029', '12855461', 'We describe APDB, a novel measure for evaluating the quality of a protein sequence alignment, given two or more PDB structures. This evaluation does not require a reference alignment or a structure superposition. APDB is designed to efficiently and objectively benchmark multiple sequence alignment methods.'),
(70734, 2003, 'bio', 'GeneLoc: exon-based integration of human genome maps', 'Rosen, Naomi|Chalifa-Caspi, Vered|Shmueli, Orit|Adato, Avital|Lapidot, Michal|Stampnitzky, Julie|Safran, Marilyn|Lancet, Doron', 'Weizmann Institute of Science, Rehovot, Israel.|Weizmann Institute of Science, Rehovot, Israel.|Weizmann Institute of Science, Rehovot, Israel.|Weizmann Institute of Science, Rehovot, Israel.|Weizmann Institute of Science, Rehovot, Israel.|Weizmann Institute of Science, Rehovot, Israel.|Weizmann Institute of Science, Rehovot, Israel.|Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 19, 'Chromosome Mapping|Database Management Systems|Databases, Genetic|Exons|Genome, Human|Human Genome Project|Humans|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Systems Integration', 'Evaluation Studies', '10.1093/bioinformatics/btg1030', '12855462', 'Despite the numerous available whole-genome mapping resources, no comprehensive, integrated map of the human genome yet exists.'),
(70735, 2003, 'bio', 'The discovery net system for high throughput bioinformatics', 'Rowe, Anthony|Kalaitzopoulos, Dimitrios|Osmond, Michelle|Ghanem, Moustafa|Guo, Yike', 'Department of Computing Imperial College, 180 Queens Gate, London, SW7 2RH, UK. asr99@doc.ic.ac.uk|Department of Computing Imperial College, 180 Queens Gate, London, SW7 2RH, UK. asr99@doc.ic.ac.uk|Department of Computing Imperial College, 180 Queens Gate, London, SW7 2RH, UK. asr99@doc.ic.ac.uk|Department of Computing Imperial College, 180 Queens Gate, London, SW7 2RH, UK. asr99@doc.ic.ac.uk|Department of Computing Imperial College, 180 Queens Gate, London, SW7 2RH, UK. asr99@doc.ic.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computational Biology|Computing Methodologies|Databases, Bibliographic|Databases, Genetic|Documentation|Information Storage and Retrieval|Internet|Natural Language Processing|Periodicals as Topic|Software|Software Design', 'Evaluation Studies', '10.1093/bioinformatics/btg1031', '12855463', 'Bioinformatics requires Grid technologies and protocols to build high performance applications without focusing on the low level detail of how the individual Grid components operate.'),
(70736, 2003, 'bio', 'Pair hidden Markov models on tree structures', 'Sakakibara, Yasubumi', 'Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, 223-8522, Japan. yasu@bio.keio.ac.jp', 'Japan', 43, 'Algorithms|Base Sequence|Markov Chains|Models, Genetic|Models, Statistical|Molecular Sequence Data|Nucleic Acid Conformation|RNA|RNA, Catalytic|RNA, Transfer|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Stochastic Processes', 'Evaluation Studies', '10.1093/bioinformatics/btg1032', '12855464', 'Computationally identifying non-coding RNA regions on the genome has much scope for investigation and is essentially harder than gene-finding problems for protein-coding regions. Since comparative sequence analysis is effective for non-coding RNA detection, efficient computational methods are expected for structural alignments of RNA sequences. On the other hand, Hidden Markov Models (HMMs) have played important roles for modeling and analysing biological sequences. Especially, the concept of Pair HMMs (PHMMs) have been examined extensively as mathematical models for alignments and gene finding.'),
(70737, 2003, 'bio', 'Processing of natural language queries to a relational database', 'Samsonova, M|Pisarev, A|Blagov, M', 'St. Petersburg State Polytechnical University, 21, Tikhoretsky ave., St. Petersburg, 194064, Russia. samson@spbcas.ru|St. Petersburg State Polytechnical University, 21, Tikhoretsky ave., St. Petersburg, 194064, Russia. samson@spbcas.ru|St. Petersburg State Polytechnical University, 21, Tikhoretsky ave., St. Petersburg, 194064, Russia. samson@spbcas.ru', '-|-|-', 0, 'Animals|Database Management Systems|Databases, Genetic|Drosophila Proteins|Drosophila melanogaster|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Natural Language Processing|User-Computer Interface|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/btg1033', '12855465', 'A new method is developed to query a relational database in natural language (NL).'),
(70738, 2003, 'bio', 'A tool to assist the study of specific features at protein binding sites', 'Santander, Víctor|Portales, Miguel Angel|Melo, Francisco', 'Pontificia Universidad Católica de Chile, Departmento Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Alameda 340, Santiago, Chile.|Pontificia Universidad Católica de Chile, Departmento Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Alameda 340, Santiago, Chile.|Pontificia Universidad Católica de Chile, Departmento Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Alameda 340, Santiago, Chile.', 'Chile|Chile|Chile', 0, 'Binding Sites|Database Management Systems|Databases, Protein|Information Dissemination|Information Storage and Retrieval|Internet|Models, Chemical|Models, Molecular|Protein Binding|Protein Conformation|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btg1034', '12855466', 'The Protein Data Bank contains a large amount of proteins that have been solved with small ligands bound to them. This constitutes a rich source of information for the study of the specific requirements of protein sites to bind small molecules with a favorable free energy. The specific atomic composition and three-dimensional geometric restraints of protein binding sites for different ligands could be easily obtained from there. The development of accurate binding site descriptors in proteins constitutes a valuable tool to assist in the large-scale prediction and annotation of protein function in whole genomes. In this work, an integrated database containing some processed and calculated protein/ligand information is described. It is expected that this database will constitute a useful tool for people working in the prediction of protein function from its structure. The database is accessible from the Internet through a web server located at: http://protein.bio.puc.cl'),
(70739, 2003, 'bio', 'STRUCLA: a WWW meta-server for protein structure comparison and evolutionary classification', 'Sasin, Joanna M|Kurowski, Michal A|Bujnicki, Janusz M', 'Bioinformatics Laboratory, International Institute of Molecular and Cell Biology, Trojdena 4, 02-109 Warsaw, Poland.|Bioinformatics Laboratory, International Institute of Molecular and Cell Biology, Trojdena 4, 02-109 Warsaw, Poland.|Bioinformatics Laboratory, International Institute of Molecular and Cell Biology, Trojdena 4, 02-109 Warsaw, Poland.', 'Poland|Poland|Poland', 9, 'Algorithms|Amino Acid Sequence|Database Management Systems|Databases, Protein|Evolution, Molecular|Information Storage and Retrieval|Internet|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1093/bioinformatics/btg1035', '12855467', 'Evolutionary relationships of proteins have long been derived from the alignment of protein sequences. But from the view of function, most restraints of evolutionary divergence operate at the level of tertiary structure. It has been demonstrated that quantitative measures of dissimilarity in families of structurally similar proteins can be applied to the construction of trees from a comparison of their three-dimensional structures. However, no convenient tool is publicly available to carry out such analyses.'),
(70740, 2003, 'bio', 'Using hidden Markov models to analyze gene expression time course data', 'Schliep, Alexander|Schönhuth, Alexander|Steinhoff, Christine', 'Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestrasse 73, 14195 Berlin, Germany. schliep@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestrasse 73, 14195 Berlin, Germany. schliep@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestrasse 73, 14195 Berlin, Germany. schliep@molgen.mpg.de', 'Germany|Germany|Germany', 158, 'Algorithms|Cell Cycle|Cluster Analysis|Fibroblasts|Gene Expression Profiling|Gene Expression Regulation|Markov Chains|Models, Genetic|Models, Statistical|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Time Factors|User-Computer Interface|Yeasts', 'Comparative Study', '10.1093/bioinformatics/btg1036', '12855468', 'Cellular processes cause changes over time. Observing and measuring those changes over time allows insights into the how and why of regulation. The experimental platform for doing the appropriate large-scale experiments to obtain time-courses of expression levels is provided by microarray technology. However, the proper way of analyzing the resulting time course data is still very much an issue under investigation. The inherent time dependencies in the data suggest that clustering techniques which reflect those dependencies yield improved performance.'),
(70741, 2003, 'bio', 'Discovering molecular pathways from protein interaction and gene expression data', 'Segal, E|Wang, H|Koller, D', 'Computer Science Department, Stanford University, Stanford, CA 94305-9010, USA. eran@cs.stanford.edu|Computer Science Department, Stanford University, Stanford, CA 94305-9010, USA. eran@cs.stanford.edu|Computer Science Department, Stanford University, Stanford, CA 94305-9010, USA. eran@cs.stanford.edu', 'United States|United States|United States', 219, 'Algorithms|Artificial Intelligence|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Models, Statistical|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Systems Integration|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg1037', '12855469', 'In this paper, we describe an approach for identifying pathways from gene expression and protein interaction data. Our approach is based on the assumption that many pathways exhibit two properties: their genes exhibit a similar gene expression profile, and the protein products of the genes often interact. Our approach is based on a unified probabilistic model, which is learned from the data using the EM algorithm. We present results on two Saccharomyces cerevisiae gene expression data sets, combined with a binary protein interaction data set. Our results show that our approach is much more successful than other approaches at discovering both coherent functional groups and entire protein complexes.'),
(70742, 2003, 'bio', 'Genome-wide discovery of transcriptional modules from DNA sequence and gene expression', 'Segal, E|Yelensky, R|Koller, D', 'Computer Science Department of Stanford University, Stanford, CA 94305-9010, USA. eran@cs.stanford.edu|Computer Science Department of Stanford University, Stanford, CA 94305-9010, USA. eran@cs.stanford.edu|Computer Science Department of Stanford University, Stanford, CA 94305-9010, USA. eran@cs.stanford.edu', 'United States|United States|United States', 184, 'Algorithms|Amino Acid Motifs|Artificial Intelligence|Chromosome Mapping|Cluster Analysis|Gene Expression Profiling|Gene Expression Regulation|Genes, Regulator|Genome|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, DNA|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg1038', '12855470', 'In this paper, we describe an approach for understanding transcriptional regulation from both gene expression and promoter sequence data. We aim to identify transcriptional modules--sets of genes that are co-regulated in a set of experiments, through a common motif profile. Using the EM algorithm, our approach refines both the module assignment and the motif profile so as to best explain the expression data as a function of transcriptional motifs. It also dynamically adds and deletes motifs, as required to provide a genome-wide explanation of the expression data. We evaluate the method on two Saccharomyces cerevisiae gene expression data sets, showing that our approach is better than a standard one at recovering known motifs and at generating biologically coherent modules. We also combine our results with binding localization data to obtain regulatory relationships with known transcription factors, and show that many of the inferred relationships have support in the literature.'),
(70743, 2003, 'bio', 'CREME: a framework for identifying cis-regulatory modules in human-mouse conserved segments', 'Sharan, Roded|Ovcharenko, Ivan|Ben-Hur, Asa|Karp, Richard M', 'International Computer Science Institute, 1947 Center St., Suite 600, Berkeley CA-94704, USA. roded@icsi.berkeley.edu|International Computer Science Institute, 1947 Center St., Suite 600, Berkeley CA-94704, USA. roded@icsi.berkeley.edu|International Computer Science Institute, 1947 Center St., Suite 600, Berkeley CA-94704, USA. roded@icsi.berkeley.edu|International Computer Science Institute, 1947 Center St., Suite 600, Berkeley CA-94704, USA. roded@icsi.berkeley.edu', 'United States|United States|United States|United States', 92, 'Algorithms|Animals|Cell Cycle|Cluster Analysis|Conserved Sequence|Gene Expression Profiling|Gene Expression Regulation|Mice|Oxidative Stress|Regulatory Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Software|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg1039', '12855471', 'The binding of transcription factors to specific regulatory sequence elements is a primary mechanism for controlling gene transcription. Recent findings suggest a modular organization of binding sites for transcription factors that cooperate in the regulation of genes. In this work we establish a framework for finding recurrent cis-regulatory modules in the promoters of a selected set of genes and scoring their statistical significance.'),
(70744, 2003, 'bio', 'A probabilistic method to detect regulatory modules', 'Sinha, Saurabh|van Nimwegen, Erik|Siggia, Eric D', 'Center for Studies in Physics and Biology, The Rockefeller University, New York, NY 0021, USA. saurabh@lonnrot.rockefeller.edu|Center for Studies in Physics and Biology, The Rockefeller University, New York, NY 0021, USA. saurabh@lonnrot.rockefeller.edu|Center for Studies in Physics and Biology, The Rockefeller University, New York, NY 0021, USA. saurabh@lonnrot.rockefeller.edu', 'United States|United States|United States', 162, 'Algorithms|Drosophila Proteins|Gene Expression Profiling|Gene Expression Regulation|Likelihood Functions|Markov Chains|Models, Genetic|Models, Statistical|Phylogeny|Regulatory Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Species Specificity', 'Comparative Study', '10.1093/bioinformatics/btg1040', '12855472', 'The discovery of cis-regulatory modules in metazoan genomes is crucial for understanding the connection between genes and organism diversity.'),
(70745, 2003, 'bio', 'myGrid: personalised bioinformatics on the information grid', 'Stevens, Robert D|Robinson, Alan J|Goble, Carole A', 'Department of Computer Science, University of Manchester, Oxford Road, Manchester, UK, M13 9PL.|Department of Computer Science, University of Manchester, Oxford Road, Manchester, UK, M13 9PL.|Department of Computer Science, University of Manchester, Oxford Road, Manchester, UK, M13 9PL.', '-|-|-', 266, 'Computational Biology|Computer Systems|Computing Methodologies|Database Management Systems|Databases, Genetic|Information Dissemination|Information Storage and Retrieval|Internet|Meta-Analysis as Topic|Online Systems|Software|Software Design|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg1041', '12855473', 'The (my)Grid project aims to exploit Grid technology, with an emphasis on the Information Grid, and provide middleware layers that make it appropriate for the needs of bioinformatics. (my)Grid is building high level services for data and application integration such as resource discovery, workflow enactment and distributed query processing. Additional services are provided to support the scientific method and best practice found at the bench but often neglected at the workstation, notably provenance management, change notification and personalisation.'),
(70746, 2003, 'bio', 'Scaling up accurate phylogenetic reconstruction from gene-order data', 'Tang, Jijun|Moret, Bernard M E', 'Department of Computer Science, University of New Mexico, Albuquerque, NM 87131, USA.|Department of Computer Science, University of New Mexico, Albuquerque, NM 87131, USA.', 'Mexico|Mexico', 55, 'Algorithms|Chromosome Mapping|Evolution, Molecular|Gene Expression Profiling|Genome|Phylogeny|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/btg1042', '12855474', 'Phylogenetic reconstruction from gene-order data has attracted increasing attention from both biologists and computer scientists over the last few years. Methods used in reconstruction include distance-based methods (such as neighbor-joining), parsimony methods using sequence-based encodings, Bayesian approaches, and direct optimization. The latter, pioneered by Sankoff and extended by us with the software suite GRAPPA, is the most accurate approach, but cannot handle more than about 15 genomes of limited size (e.g. organelles).'),
(70747, 2003, 'bio', 'Skew in CG content near the transcription start site in Arabidopsis thaliana', 'Tatarinova, Tatiana|Brover, Vyacheslav|Troukhan, Maxim|Alexandrov, Nickolai', 'Ceres, Inc, 3007 Malibu Canyon Road, Malibu, CA 90265, USA.|Ceres, Inc, 3007 Malibu Canyon Road, Malibu, CA 90265, USA.|Ceres, Inc, 3007 Malibu Canyon Road, Malibu, CA 90265, USA.|Ceres, Inc, 3007 Malibu Canyon Road, Malibu, CA 90265, USA.', 'Mali|Mali|Mali|Mali', 29, 'Arabidopsis|Base Composition|Cytosine|DNA Mutational Analysis|Genetic Variation|Genome, Plant|Guanine|Sequence Alignment|Sequence Analysis, DNA|Transcription Initiation Site|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btg1043', '12855475', 'We have discovered a novel statistical feature of Arabidopsis thaliana genome that remarkably correlates with a position of transcription start site--CG skew peak. We hypothesize that the phenomenon can be explained by the higher mutability of unprotected cytosines.'),
(70748, 2003, 'bio', 'Gene structure-based splice variant deconvolution using a microarray platform', 'Wang, Hui|Hubbell, Earl|Hu, Jing-shan|Mei, Gangwu|Cline, Melissa|Lu, Gang|Clark, Tyson|Siani-Rose, Michael A|Ares, Manuel|Kulp, David C|Haussler, David', 'Affymetrix Inc. 3450 Central Expressway, Santa Clara, CA 95051, USA. hui_wang@affymetrix.com|Affymetrix Inc. 3450 Central Expressway, Santa Clara, CA 95051, USA. hui_wang@affymetrix.com|Affymetrix Inc. 3450 Central Expressway, Santa Clara, CA 95051, USA. hui_wang@affymetrix.com|Affymetrix Inc. 3450 Central Expressway, Santa Clara, CA 95051, USA. hui_wang@affymetrix.com|Affymetrix Inc. 3450 Central Expressway, Santa Clara, CA 95051, USA. hui_wang@affymetrix.com|Affymetrix Inc. 3450 Central Expressway, Santa Clara, CA 95051, USA. hui_wang@affymetrix.com|Affymetrix Inc. 3450 Central Expressway, Santa Clara, CA 95051, USA. hui_wang@affymetrix.com|Affymetrix Inc. 3450 Central Expressway, Santa Clara, CA 95051, USA. hui_wang@affymetrix.com|Affymetrix Inc. 3450 Central Expressway, Santa Clara, CA 95051, USA. hui_wang@affymetrix.com|Affymetrix Inc. 3450 Central Expressway, Santa Clara, CA 95051, USA. hui_wang@affymetrix.com|Affymetrix Inc. 3450 Central Expressway, Santa Clara, CA 95051, USA. hui_wang@affymetrix.com', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 80, 'Algorithms|Alternative Splicing|DNA Probes|Drosophila Proteins|Equipment Design|Equipment Failure Analysis|Gene Expression Profiling|Genetic Variation|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Tropomyosin', 'Comparative Study', '10.1093/bioinformatics/btg1044', '12855476', 'Alternative splicing allows a single gene to generate multiple mRNAs, which can be translated into functionally and structurally diverse proteins. One gene can have multiple variants coexisting at different concentrations. Estimating the relative abundance of each variant is important for the study of underlying biological function. Microarrays are standard tools that measure gene expression. But most design and analysis has not accounted for splice variants. Thus splice variant-specific chip designs and analysis algorithms are needed for accurate gene expression profiling.'),
(70749, 2003, 'bio', 'Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis', 'Yamanishi, Y|Vert, J-P|Nakaya, A|Kanehisa, M', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. yoshi@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. yoshi@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. yoshi@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. yoshi@kuicr.kyoto-u.ac.jp', 'Japan|Japan|Japan|Japan', 82, 'Algorithms|Chromosome Mapping|Escherichia coli|Gene Expression Profiling|Gene Expression Regulation|Genomics|Models, Genetic|Models, Statistical|Multigene Family|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Signal Transduction|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/btg1045', '12855477', 'A major issue in computational biology is the reconstruction of pathways from several genomic datasets, such as expression data, protein interaction data and phylogenetic profiles. As a first step toward this goal, it is important to investigate the amount of correlation which exists between these data.'),
(70750, 2003, 'bio', 'Evaluation of text data mining for database curation: lessons learned from the KDD Challenge Cup', 'Yeh, Alexander S|Hirschman, Lynette|Morgan, Alexander A', 'The MITRE Corporation, 202 Burlington Road, Bedford, MA 01730, USA. asy@mitre.org|The MITRE Corporation, 202 Burlington Road, Bedford, MA 01730, USA. asy@mitre.org|The MITRE Corporation, 202 Burlington Road, Bedford, MA 01730, USA. asy@mitre.org', 'United States|United States|United States', 110, 'Abstracting and Indexing as Topic|Acetaminophen|Benchmarking|Biology|Computational Biology|Database Management Systems|Databases, Bibliographic|Documentation|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Periodicals as Topic|Terminology as Topic', 'Evaluation Studies', '10.1093/bioinformatics/btg1046', '12855478', 'The biological literature is a major repository of knowledge. Many biological databases draw much of their content from a careful curation of this literature. However, as the volume of literature increases, the burden of curation increases. Text mining may provide useful tools to assist in the curation process. To date, the lack of standards has made it impossible to determine whether text mining techniques are sufficiently mature to be useful.'),
(70751, 2003, 'bio', 'Extracting synonymous gene and protein terms from biological literature', 'Yu, Hong|Agichtein, Eugene', 'Department of Computer Science, Columbia University, New York, NY, USA. hongu@cs.columbia.edu|Department of Computer Science, Columbia University, New York, NY, USA. hongu@cs.columbia.edu', 'United States|United States', 58, 'Abstracting and Indexing as Topic|Acetaminophen|Algorithms|Biology|Computational Biology|Database Management Systems|Databases, Bibliographic|Documentation|Genes|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Proteins|Terminology as Topic|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/btg1047', '12855479', 'Genes and proteins are often associated with multiple names. More names are added as new functional or structural information is discovered. Because authors can use any one of the known names for a gene or protein, information retrieval and extraction would benefit from identifying the gene and protein terms that are synonyms of the same substance.'),
(70752, 2003, 'bio', 'A comparison of physical mapping algorithms based on the maximum likelihood model', 'Huang, Jinling|Bhandarkar, Suchendra M', 'Department of Computer Science, University of Georgia, Athens, Georgia 30602-7404, USA. tupistra@yahoo.com|Department of Computer Science, University of Georgia, Athens, Georgia 30602-7404, USA. tupistra@yahoo.com', 'Georgia|Georgia', 0, 'Algorithms|Databases, Genetic|Genome, Fungal|Likelihood Functions|Models, Genetic|Models, Statistical|Neurospora crassa|Physical Chromosome Mapping|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg166', '12874040', 'Physical mapping of chromosomes using the maximum likelihood (ML) model is a problem of high computational complexity entailing both discrete optimization to recover the optimal probe order as well as continuous optimization to recover the optimal inter-probe spacings. In this paper, two versions of the genetic algorithm (GA) are proposed, one with heuristic crossover and deterministic replacement and the other with heuristic crossover and stochastic replacement, for the physical mapping problem under the maximum likelihood model. The genetic algorithms are compared with two other discrete optimization approaches, namely simulated annealing (SA) and large-step Markov chains (LSMC), in terms of solution quality and runtime efficiency.'),
(70753, 2003, 'bio', 'Design and assessment of a fast algorithm for identifying specific probes for human and mouse genes', 'Chang, Pei-Chin|Peck, Konan', 'Institute of Biomedical Science, Academia Sinica, Taipei, Taiwan 115, ROC.|Institute of Biomedical Science, Academia Sinica, Taipei, Taiwan 115, ROC.', '-|-', 13, 'Algorithms|Animals|Base Sequence|DNA Probes|Databases, Nucleic Acid|Expressed Sequence Tags|Gene Expression Profiling|Genome, Human|Humans|Mice|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Software Design', 'Comparative Study', '10.1093/bioinformatics/btg162', '12874041', 'Mammalian genomes are highly complex. To identify the unique sequences of each gene in a mammalian gene database containing tens of thousands of DNA sequences is a computation intensive task. With the advent of parallel genetic analysis methods such as microarrays and the availability of more and more whole genome sequences of organisms, an algorithm allowing speedy identification of the unique gene probes for functional studies of individual genes will be a very useful tool.'),
(70754, 2003, 'bio', 'ESTprep: preprocessing cDNA sequence reads', 'Scheetz, Todd E|Trivedi, Nishank|Roberts, Chad A|Kucaba, Tamara|Berger, Brian|Robinson, Natalie L|Birkett, Clayton L|Gavin, Allen J|OLeary, Brian|Braun, Terry A|Bonaldo, Maria F|Robinson, John P|Sheffield, Val C|Soares, Marcelo B|Casavant, Thomas L', 'Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu|Center for Bioinformatics and Computational Biology, The University of Iowa, Iowa City, IA 52242, USA. tscheetz@eng.uiowa.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Base Sequence|DNA, Complementary|Expressed Sequence Tags|Gene Expression Profiling|Molecular Sequence Data|Quality Control|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btg159', '12874042', 'High accuracy of data always governs the large-scale gene discovery projects. The data should not only be trustworthy but should be correctly annotated for various features it contains. Sequence errors are inherent in single-pass sequences such as ESTs obtained from automated sequencing. These errors further complicate the automated identification of EST-related sequencing. A tool is required to prepare the data prior to advanced annotation processing and submission to public databases.'),
(70755, 2003, 'bio', 'New normalization methods for cDNA microarray data', 'Wilson, D L|Buckley, M J|Helliwell, C A|Wilson, I W', 'CSIRO Mathematical and Information Sciences, Locked Bag 17 North Ryde 1670 NSW, Australia. dwilson@gmp.usyd.edu.au|CSIRO Mathematical and Information Sciences, Locked Bag 17 North Ryde 1670 NSW, Australia. dwilson@gmp.usyd.edu.au|CSIRO Mathematical and Information Sciences, Locked Bag 17 North Ryde 1670 NSW, Australia. dwilson@gmp.usyd.edu.au|CSIRO Mathematical and Information Sciences, Locked Bag 17 North Ryde 1670 NSW, Australia. dwilson@gmp.usyd.edu.au', 'Australia|Australia|Australia|Australia', 76, 'Algorithms|Calibration|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Quality Control|Reference Standards|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Spectrometry, Fluorescence', 'Comparative Study', '10.1093/bioinformatics/btg146', '12874043', 'The focus of this paper is on two new normalization methods for cDNA microarrays. After the image analysis has been performed on a microarray and before differentially expressed genes can be detected, some form of normalization must be applied to the microarrays. Normalization removes biases towards one or other of the fluorescent dyes used to label each mRNA sample allowing for proper evaluation of differential gene expression.'),
(70756, 2003, 'bio', 'On the use of permutation in and the performance of a class of nonparametric methods to detect differential gene expression', 'Pan, Wei', 'Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building (MMC 303), Minneapolis, MN 55455-0378, USA. weip@biostat.umm.edu', 'United States', 0, 'Algorithms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Variation|Humans|Leukemia|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Statistics, Nonparametric', 'Comparative Study', '10.1093/bioinformatics/btg167', '12874044', 'Recently a class of nonparametric statistical methods, including the empirical Bayes (EB) method, the significance analysis of microarray (SAM) method and the mixture model method (MMM), have been proposed to detect differential gene expression for replicated microarray experiments conducted under two conditions. All the methods depend on constructing a test statistic Z and a so-called null statistic z. The null statistic z is used to provide some reference distribution for Z such that statistical inference can be accomplished. A common way of constructing z is to apply Z to randomly permuted data. Here we point our that the distribution of z may not approximate the null distribution of Z well, leading to possibly too conservative inference. This observation may apply to other permutation-based nonparametric methods. We propose a new method of constructing a null statistic that aims to estimate the null distribution of a test statistic directly.');
