INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71296, 2004, 'bio', 'Gene annotation from scientific literature using mappings between keyword systems', 'Pérez, Antonio J|Perez-Iratxeta, Carolina|Bork, Peer|Thode, Guillermo|Andrade, Miguel A', 'University of Málaga, Facultad de Ciencias, Departmento de Genetica, Group of Bioinformatics, Campus Universitario de Teatinos, 29071 Málaga, Spain.|University of Málaga, Facultad de Ciencias, Departmento de Genetica, Group of Bioinformatics, Campus Universitario de Teatinos, 29071 Málaga, Spain.|University of Málaga, Facultad de Ciencias, Departmento de Genetica, Group of Bioinformatics, Campus Universitario de Teatinos, 29071 Málaga, Spain.|University of Málaga, Facultad de Ciencias, Departmento de Genetica, Group of Bioinformatics, Campus Universitario de Teatinos, 29071 Málaga, Spain.|University of Málaga, Facultad de Ciencias, Departmento de Genetica, Group of Bioinformatics, Campus Universitario de Teatinos, 29071 Málaga, Spain.', 'Spain|Spain|Spain|Spain|Spain', 13, 'Abstracting and Indexing as Topic|Algorithms|Databases, Protein|Documentation|Gene Expression Profiling|Natural Language Processing|Periodicals as Topic|Proteins|Sequence Analysis, Protein|Terminology as Topic', 'Comparative Study', '10.1093/bioinformatics/bth207', '15059832', 'The description of genes in databases by keywords helps the non-specialist to quickly grasp the properties of a gene and increases the efficiency of computational tools that are applied to gene data (e.g. searching a gene database for sequences related to a particular biological process). However, the association of keywords to genes or protein sequences is a difficult process that ultimately implies examination of the literature related to a gene.'),
(71297, 2004, 'bio', 'F2CS: FSSP to CATH and SCOP prediction server', 'Getz, Gad|Starovolsky, Alina|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.', 'Israel|Israel|Israel', 8, 'Algorithms|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Online Systems|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/bth208', '15059833', 'The F2CS server provides access to the software, F2CS2.00, which implements an automated prediction method of SCOP and CATH classifications of proteins, based on their FSSP Z-scores.'),
(71298, 2004, 'bio', 'Designing and executing scientific workflows with a programmable integrator', 'Chagoyen, M|Kurul, M E|De-Alarcón, P A|Carazo, J M|Gupta, A', 'Biocomputing Unit, Centro Nacional de Biotecnología, Madrid 28049, Spain. monica.chagoyen@cnb.uam.es|Biocomputing Unit, Centro Nacional de Biotecnología, Madrid 28049, Spain. monica.chagoyen@cnb.uam.es|Biocomputing Unit, Centro Nacional de Biotecnología, Madrid 28049, Spain. monica.chagoyen@cnb.uam.es|Biocomputing Unit, Centro Nacional de Biotecnología, Madrid 28049, Spain. monica.chagoyen@cnb.uam.es|Biocomputing Unit, Centro Nacional de Biotecnología, Madrid 28049, Spain. monica.chagoyen@cnb.uam.es', 'Spain|Spain|Spain|Spain|Spain', 6, 'Algorithms|Computational Biology|Databases, Factual|Decision Support Techniques|Information Storage and Retrieval|Programming Languages|Research Design|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth209', '15059834', 'As in many other fields of science, computational methods in molecular biology need to intersperse information access and algorithm execution in a computational workflow. Users often find difficulties when transferring data between data sources and applications. In most cases there is no standard solution for workflow design and execution and tailored scripting mechanisms are implemented in a case by case basis.'),
(71299, 2004, 'bio', 'Efficient selection of unique and popular oligos for large EST databases', 'Zheng, Jie|Close, Timothy J|Jiang, Tao|Lonardi, Stefano', 'Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.|Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.|Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.|Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Base Sequence|DNA Probes|Databases, Nucleic Acid|Expressed Sequence Tags|Molecular Sequence Data|Oligonucleotides|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth210', '15059835', 'Expressed sequence tag (EST) databases have grown exponentially in recent years and now represent the largest collection of genetic sequences. An important application of these databases is that they contain information useful for the design of gene-specific oligonucleotides (or simply, oligos) that can be used in PCR primer design, microarray experiments and genomic library screening.'),
(71300, 2004, 'bio', 'A weighted least-squares approach for inferring phylogenies from incomplete distance matrices', 'Makarenkov, Vladimir|Lapointe, François-Joseph', 'Département dInformatique, Université du Québec à Montréal, C.P. 8888, Succ. Centre-Ville, Montréal, Québec, Canada H3C 3P8. makarenkov.vladimir@uqam.ca|Département dInformatique, Université du Québec à Montréal, C.P. 8888, Succ. Centre-Ville, Montréal, Québec, Canada H3C 3P8. makarenkov.vladimir@uqam.ca', 'Canada|Canada', 41, 'Algorithms|Chromosome Mapping|Evolution, Molecular|Genome|Least-Squares Analysis|Models, Genetic|Models, Statistical|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth211', '15059836', 'The problem of phylogenetic inference from datasets including incomplete or uncertain entries is among the most relevant issues in systematic biology. In this paper, we propose a new method for reconstructing phylogenetic trees from partial distance matrices. The new method combines the usage of the four-point condition and the ultrametric inequality with a weighted least-squares approximation to solve the problem of missing entries. It can be applied to infer phylogenies from evolutionary data including some missing or uncertain information, for instance, when observed nucleotide or protein sequences contain gaps or missing entries.'),
(71301, 2004, 'bio', 'Extraction of fluorescent cell puncta by adaptive fuzzy segmentation', 'Pham, Tuan D|Crane, Denis I|Tran, Tuan H|Nguyen, Tam H', 'School of Computing and Information Technology, Griffith University, Nathan Campus, Australia. t.pham@griffith.edu.au|School of Computing and Information Technology, Griffith University, Nathan Campus, Australia. t.pham@griffith.edu.au|School of Computing and Information Technology, Griffith University, Nathan Campus, Australia. t.pham@griffith.edu.au|School of Computing and Information Technology, Griffith University, Nathan Campus, Australia. t.pham@griffith.edu.au', 'Australia|Australia|Australia|Australia', 25, 'Algorithms|Artificial Intelligence|Cell Line|Cluster Analysis|Fibroblasts|Fuzzy Logic|Humans|Image Interpretation, Computer-Assisted|Microscopy, Fluorescence|Pattern Recognition, Automated|Peroxisomes|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bth213', '15059837', 'The discrimination and measurement of fluorescent-labeled vesicles using microscopic analysis of fixed cells presents a challenge for biologists interested in quantifying the abundance, size and distribution of such vesicles in normal and abnormal cellular situations. In the specific application reported here, we were interested in quantifying changes to the population of a major organelle, the peroxisome, in cells from normal control patients and from patients with a defect in peroxisome biogenesis. In the latter, peroxisomes are present as larger vesicular structures with a more restricted cytoplasmic distribution. Existing image processing methods for extracting fluorescent cell puncta do not provide useful results and therefore, there is a need to develop some new approaches for dealing with such a task effectively.'),
(71302, 2004, 'bio', 'Ligand Depot: a data warehouse for ligands bound to macromolecules', 'Feng, Zukang|Chen, Li|Maddula, Himabindu|Akcan, Ozgur|Oughtred, Rose|Berman, Helen M|Westbrook, John', 'Protein Data Bank, Research Collaboratory for Structural Bioinformatics, Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, NJ 08854, USA.|Protein Data Bank, Research Collaboratory for Structural Bioinformatics, Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, NJ 08854, USA.|Protein Data Bank, Research Collaboratory for Structural Bioinformatics, Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, NJ 08854, USA.|Protein Data Bank, Research Collaboratory for Structural Bioinformatics, Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, NJ 08854, USA.|Protein Data Bank, Research Collaboratory for Structural Bioinformatics, Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, NJ 08854, USA.|Protein Data Bank, Research Collaboratory for Structural Bioinformatics, Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, NJ 08854, USA.|Protein Data Bank, Research Collaboratory for Structural Bioinformatics, Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, NJ 08854, USA.', 'Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey', 125, 'Binding Sites|Biopolymers|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Ligands|Macromolecular Substances|Natural Language Processing|Protein Binding|Protein Interaction Mapping|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth214', '15059838', 'Ligand Depot is an integrated data resource for finding information about small molecules bound to proteins and nucleic acids. The initial release (version 1.0, November, 2003) focuses on providing chemical and structural information for small molecules found as part of the structures deposited in the Protein Data Bank. Ligand Depot accepts keyword-based queries and also provides a graphical interface for performing chemical substructure searches. A wide variety of web resources that contain information on small molecules may also be accessed through Ligand Depot.'),
(71303, 2004, 'bio', 'Bio-Mirror project for public bio-data distribution', 'Gilbert, Don|Ugawa, Yoshihiro|Buchhorn, Markus|Wee, Tan Tin|Mizushima, Akira|Kim, Hyunchul|Chon, Kilnam|Weon, Seyeon|Ma, Juncai|Ichiyanagi, Yoshihiro|Liou, Der-Ming|Keretho, Somnuk|Napis, Suhaimi', 'Department of Biology, Indiana University, Bloomington, IN 47405, USA.|Department of Biology, Indiana University, Bloomington, IN 47405, USA.|Department of Biology, Indiana University, Bloomington, IN 47405, USA.|Department of Biology, Indiana University, Bloomington, IN 47405, USA.|Department of Biology, Indiana University, Bloomington, IN 47405, USA.|Department of Biology, Indiana University, Bloomington, IN 47405, USA.|Department of Biology, Indiana University, Bloomington, IN 47405, USA.|Department of Biology, Indiana University, Bloomington, IN 47405, USA.|Department of Biology, Indiana University, Bloomington, IN 47405, USA.|Department of Biology, Indiana University, Bloomington, IN 47405, USA.|Department of Biology, Indiana University, Bloomington, IN 47405, USA.|Department of Biology, Indiana University, Bloomington, IN 47405, USA.|Department of Biology, Indiana University, Bloomington, IN 47405, USA.', 'India|India|India|India|India|India|India|India|India|India|India|India|India', 7, 'Biology|Computational Biology|Computer Communication Networks|Database Management Systems|Databases, Genetic|Documentation|Information Dissemination|Information Storage and Retrieval|Internet|Systems Integration', 'Journal Article', '10.1093/bioinformatics/bth219', '15059839', 'Timely worldwide distribution of biosequence and bioinformatics data depends on high performance networking and advances in Internet transport methods. The Bio-Mirror project focuses on providing up-to-date distribution of this rapidly growing and changing data. It offers FTP, Web and Rsync access to many high-volume databanks from several sites around the world. Experiments with data grids and other methods offer future improvements in biology data distribution.'),
(71304, 2004, 'bio', 'MuSiC: a tool for multiple sequence alignment with constraints', 'Tsai, Yin Te|Huang, Yen Pin|Yu, Ching Ta|Lu, Chin Lung', 'Department of Computer Science and Information Management, Providence University, Taiwan, ROC.|Department of Computer Science and Information Management, Providence University, Taiwan, ROC.|Department of Computer Science and Information Management, Providence University, Taiwan, ROC.|Department of Computer Science and Information Management, Providence University, Taiwan, ROC.', '-|-|-|-', 25, 'Algorithms|Information Storage and Retrieval|Internet|Programming Languages|Sequence Alignment|Sequence Analysis|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth220', '15059840', 'MuSiC is a web server to perform the constrained alignment of a set of sequences, such that the user-specified residues/nucleotides are aligned with each other. The input of the MuSiC system consists of a set of protein/DNA/RNA sequences and a set of user-specified constraints, each with a fragment of residue/nucleotide that (approximately) appears in all input sequences. The output of MuSiC is a constrained multiple sequence alignment in which the fragments of the input sequences whose residues/nucleotides exhibit a given degree of similarity to a constraint are aligned together. The current MuSiC system is implemented in Java language and can be accessed via a simple web interface.'),
(71305, 2004, 'bio', 'Web-based kinetic modelling using JWS Online', 'Olivier, Brett G|Snoep, Jacky L', 'Department of Biochemistry, University of Stellenbosch, Private Bag X1, Matieland 7602, South Africa.|Department of Biochemistry, University of Stellenbosch, Private Bag X1, Matieland 7602, South Africa.', 'South Africa|South Africa', 220, 'Cell Physiological Phenomena|Computer Simulation|Databases, Factual|Information Storage and Retrieval|Internet|Kinetics|Metabolism|Models, Biological|Online Systems|Signal Transduction|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth200', '15072998', 'JWS Online is a repository of kinetic models, describing biological systems, which can be interactively run and interrogated over the Internet. It is implemented using a client-server strategy where the clients, in the form of web browser based Java applets, act as a graphical interface to the model servers, which perform the required numerical computations.'),
(71306, 2004, 'bio', 'Network-based regulatory pathways analysis', 'Xiong, Momiao|Zhao, Jinying|Xiong, Hao', 'Human Genetic Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA. mxiong@sph.uth.tmc.edu|Human Genetic Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA. mxiong@sph.uth.tmc.edu|Human Genetic Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA. mxiong@sph.uth.tmc.edu', 'United States|United States|United States', 21, 'Algorithms|Computer Simulation|Gene Expression Regulation|Linear Models|Metabolism|Models, Genetic|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/bth201', '15072999', 'A useful approach to unraveling and understanding complex biological networks is to decompose networks into basic functional and structural units. Recent application of convex analysis to metabolic networks leads to the development of network-based metabolic pathway analysis and the decomposition of metabolic networks into metabolic extreme pathways that are true functional units of metabolic systems. Metabolic extreme pathways are derived from limited knowledge of the metabolic networks, but provide an integrated predictive description of metabolic networks. It is important to extend the concept of network-based metabolic pathways to genetic networks and develop mathematical procedures for network-based regulatory pathway analysis.'),
(71307, 2004, 'bio', 'Probabilistic nucleotide assembling method for sequencing by hybridization', 'Endo, Takaho A', 'Division of Molecular Life Sciences, Department of Genetic Information, School of Medicine, Tokai University, Bouseidai, Isehara, Kanagawa, 259-1193, Japan. endo@genetix-h.com', 'Japan', 17, 'Algorithms|Base Sequence|Computer Simulation|Databases, Genetic|In Situ Hybridization|Models, Genetic|Models, Statistical|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth202', '15073000', 'Developing a new method of assembling small sequences based on sequencing by hybridization with many positive and negative faults. First, an interpretation of a generic traveling salesman problem is provided (i.e. finding the shortest route for visiting many cities), using genetic algorithms. Second, positive errors are excluded before assembly by a sanitization process.'),
(71308, 2004, 'bio', 'STING Contacts: a web-based application for identification and analysis of amino acid contacts within protein structure and across protein interfaces', 'Mancini, A L|Higa, R H|Oliveira, A|Dominiquini, F|Kuser, P R|Yamagishi, M E B|Togawa, R C|Neshich, G', 'Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 23, 'Algorithms|Amino Acids|Binding Sites|Computer Simulation|Internet|Models, Chemical|Models, Molecular|Online Systems|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bth203', '15073001', 'Amino acid contacts in terms of atomic interactions are essential factors to be considered in the analysis of the structure of a protein and its complexes. Consequently, molecular biologists do require specific tools for the identification and visualization of all such contacts. Graphical contacts (GC) and interface forming residue graphical contacts (IFRgc) presented here, calculate atomic contacts among amino acids based on a table of predefined pairs of the atom types and their distances, and then display them using number of different forms. The inventory of currently listed contact types by GC and IFRgc include hydrogen bonds (in nine different flavors), hydrophobic interactions, charge-charge interactions, aromatic stacking and disulfide bonds. Such extensive catalog of the interactions, representing the forces that govern protein folding, stability and binding, is the key feature of these two applications. GC and IFRgc are part of STING Millennium Suite.'),
(71309, 2004, 'bio', 'Speeding up whole-genome alignment by indexing frequency vectors', 'Kahveci, Tamer|Ljosa, Vebjorn|Singh, Ambuj K', 'Department of Computer Science, University of California, Santa Barbara, Santa Barbara, CA 93106-5110, USA. tamer@cs.ucsb.edu|Department of Computer Science, University of California, Santa Barbara, Santa Barbara, CA 93106-5110, USA. tamer@cs.ucsb.edu|Department of Computer Science, University of California, Santa Barbara, Santa Barbara, CA 93106-5110, USA. tamer@cs.ucsb.edu', 'United States|United States|United States', 15, 'Databases, Genetic|Gene Frequency|Genome|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth212', '15073002', 'Many biological applications require the comparison of large genome strings. Current techniques suffer from high computational and I/O costs.'),
(71310, 2004, 'bio', 'GeConT: gene context analysis', 'Ciria, R|Abreu-Goodger, C|Morett, E|Merino, E', 'Departamento de Biología Celular y Biocatálisis, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, 62210 Morelos, México.|Departamento de Biología Celular y Biocatálisis, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, 62210 Morelos, México.|Departamento de Biología Celular y Biocatálisis, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, 62210 Morelos, México.|Departamento de Biología Celular y Biocatálisis, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, 62210 Morelos, México.', '-|-|-|-', 45, 'Chromosome Mapping|Documentation|Information Storage and Retrieval|Internet|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth216', '15073003', 'The fact that adjacent genes in bacteria are often functionally related is widely known. GeConT (Gene Context Tool) is a web interface designed to visualize genome context of a gene or a group of genes and their orthologs in all the completely sequenced genomes. The graphical information of GeConT can be used to analyze genome annotation, functional ortholog identification or to verify the genomic context congruence of any set of genes that share a common property.'),
(71311, 2004, 'bio', 'Combining pattern discovery and discriminant analysis to predict gene co-regulation', 'Simonis, N|Wodak, S J|Cohen, G N|van Helden, J', 'Service de Conformation des Macromolécules Biologiques et Bioinformatique, Centre de Biologie Structurale et Bioinformatique, CP 263, Université Libre de Bruxelles, Bld. du Triomphe B-1050 Bruxelles, Belgium. nicolas@scmb.ulb.ac.be|Service de Conformation des Macromolécules Biologiques et Bioinformatique, Centre de Biologie Structurale et Bioinformatique, CP 263, Université Libre de Bruxelles, Bld. du Triomphe B-1050 Bruxelles, Belgium. nicolas@scmb.ulb.ac.be|Service de Conformation des Macromolécules Biologiques et Bioinformatique, Centre de Biologie Structurale et Bioinformatique, CP 263, Université Libre de Bruxelles, Bld. du Triomphe B-1050 Bruxelles, Belgium. nicolas@scmb.ulb.ac.be|Service de Conformation des Macromolécules Biologiques et Bioinformatique, Centre de Biologie Structurale et Bioinformatique, CP 263, Université Libre de Bruxelles, Bld. du Triomphe B-1050 Bruxelles, Belgium. nicolas@scmb.ulb.ac.be', 'Belgium|Belgium|Belgium|Belgium', 24, 'Algorithms|Computer Simulation|Discriminant Analysis|Gene Expression Regulation|Genes, Regulator|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth252', '15073004', 'Several pattern discovery methods have been proposed to detect over-represented motifs in upstream sequences of co-regulated genes, and are for example used to predict cis-acting elements from clusters of co-expressed genes. The clusters to be analyzed are often noisy, containing a mixture of co-regulated and non-co-regulated genes. We propose a method to discriminate co-regulated from non-co-regulated genes on the basis of counts of pattern occurrences in their non-coding sequences.'),
(71312, 2004, 'bio', 'PerlPrimer: cross-platform, graphical primer design for standard, bisulphite and real-time PCR', 'Marshall, Owen J', 'Murdoch Childrens Research Institute, Royal Childrens Hospital, Flemington Road, Parkville, Vic., 3052, Australia. owen.marshall@mcri.edu.au', 'Australia', 435, 'Algorithms|Chromosome Mapping|DNA Primers|Oligonucleotide Array Sequence Analysis|Online Systems|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA|Software|Sulfites|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth254', '15073005', 'PerlPrimer is a cross-platform graphical user interface application for the design of primers for standard, bisulphite and real-time PCR, and sequencing. The program incorporates highly accurate melting-temperature and primer-dimer prediction algorithms with powerful tools such as sequence retrieval from Ensembl and the ability to BLAST search primer pairs. It aims to automate and simplify the process of primer design.'),
(71313, 2004, 'bio', 'Sequence patterns derived from the automated prediction of functional residues in structurally-aligned homologous protein families', 'Miguel, Ricardo Núñez', 'Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, United Kingdom. Ricardo@cryst.bioc.cam.ac.uk', 'United Kingdom', 11, 'Algorithms|Amino Acids|Conserved Sequence|Databases, Protein|Models, Molecular|Pattern Recognition, Automated|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bth255', '15073006', 'Most proteins have evolved to perform specific functions that are dependent on the adoption of well-defined three-dimensional (3D) structures. Specific patterns of conserved residues in amino acid sequences of divergently evolved proteins are frequently observed, these may reflect evolutionary restraints arising both from the need to maintain tertiary structure and the requirement to conserve residues more directly involved in function. Databases of such sequence patterns are valuable in identifying distant homologues, in predicting function and in the study of evolution.'),
(71314, 2004, 'bio', 'GEPIS--quantitative gene expression profiling in normal and cancer tissues', 'Zhang, Yan|Eberhard, David A|Frantz, Gretchen D|Dowd, Patrick|Wu, Thomas D|Zhou, Yan|Watanabe, Colin|Luoh, Shiuh-Ming|Polakis, Paul|Hillan, Kenneth J|Wood, William I|Zhang, Zemin', 'Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA.|Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA.|Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA.|Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA.|Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA.|Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA.|Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA.|Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA.|Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA.|Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA.|Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, USA.|Department of Bioinformatics, Genentech Inc., South San Francisco, CA 94080, 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', 22, 'Algorithms|Biomarkers, Tumor|Chromosome Mapping|Expressed Sequence Tags|Gene Expression Profiling|Genetic Testing|Humans|Internet|Neoplasms|Online Systems|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth256', '15073007', 'Expression profiling in diverse tissues is fundamental to understanding gene function as well as therapeutic target identification. The vast collection of expressed sequence tags (ESTs) and the associated tissue source information provides an attractive opportunity for studying gene expression.'),
(71315, 2004, 'bio', 'PUNS: transcriptomic- and genomic-in silico PCR for enhanced primer design', 'Boutros, Paul C|Okey, Allan B', 'Department of Pharmacology, University of Toronto, Medical Sciences Building, 1 Kings College Circle, Toronto, Ontario, M5S-1A8 Canada. Paul.Boutros@utoronto.ca|Department of Pharmacology, University of Toronto, Medical Sciences Building, 1 Kings College Circle, Toronto, Ontario, M5S-1A8 Canada. Paul.Boutros@utoronto.ca', 'Canada|Canada', 22, 'Algorithms|Chromosome Mapping|DNA Primers|Oligonucleotide Array Sequence Analysis|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA|Software|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/bth257', '15073008', 'We developed a CGI/Perl-based web server to perform in silico polymerase chain reaction (PCR) on PCR primer sequences. The PUNS (Primer-UniGene Selectivity) server simulates PCR reactions by running BLASTN analysis on user-entered primer pairs against both the transcriptome and the genome to assess primer specificity. PUNS is particularly suited for the identification of highly selective primers for quantitative microarray validation.'),
(71316, 2004, 'bio', 'G-PRIMER: greedy algorithm for selecting minimal primer set', 'Wang, Jiren|Li, Kuo-Bin|Sung, Wing-Kin', 'BioInformatics Institute, 30 Biopolis Street, #07-01 Matrix, Singapore 138671. jiren@bii.a-star.edu.sg|BioInformatics Institute, 30 Biopolis Street, #07-01 Matrix, Singapore 138671. jiren@bii.a-star.edu.sg|BioInformatics Institute, 30 Biopolis Street, #07-01 Matrix, Singapore 138671. jiren@bii.a-star.edu.sg', 'Singapore|Singapore|Singapore', 20, 'Algorithms|Chromosome Mapping|DNA Primers|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth259', '15073009', 'G-PRIMER, a web-based primer design program, has been developed to compute a minimal primer set specifically annealed to all the open reading frames in a given microbial genome. This program has been successfully used in the microarray experiment for analyzing the expression of genes in the Xanthomonas campestris genome.'),
(71317, 2004, 'bio', 'Data mining in bioinformatics using Weka', 'Frank, Eibe|Hall, Mark|Trigg, Len|Holmes, Geoffrey|Witten, Ian H', 'Department of Computer Science, University of Waikato, Private Bag 3105, Hamilton, New Zealand. eibe@cs.waikato.ac.nz|Department of Computer Science, University of Waikato, Private Bag 3105, Hamilton, New Zealand. eibe@cs.waikato.ac.nz|Department of Computer Science, University of Waikato, Private Bag 3105, Hamilton, New Zealand. eibe@cs.waikato.ac.nz|Department of Computer Science, University of Waikato, Private Bag 3105, Hamilton, New Zealand. eibe@cs.waikato.ac.nz|Department of Computer Science, University of Waikato, Private Bag 3105, Hamilton, New Zealand. eibe@cs.waikato.ac.nz', 'New Zealand|New Zealand|New Zealand|New Zealand|New Zealand', 613, 'Algorithms|Artificial Intelligence|Computational Biology|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Natural Language Processing|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth261', '15073010', 'The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it.'),
(71318, 2004, 'bio', 'The PDB-Preview database: a repository of in-silico models of on-hold PDB entries', 'Fischer, Daniel|Paxc5x9b, Jakub|Rychlewski, Leszek', 'Buffalo Center of Excellence in Bioinformatics, University of Buffalo, 901 Washington Street Ste. 300, Buffalo, NY 14203, USA.|Buffalo Center of Excellence in Bioinformatics, University of Buffalo, 901 Washington Street Ste. 300, Buffalo, NY 14203, USA.|Buffalo Center of Excellence in Bioinformatics, University of Buffalo, 901 Washington Street Ste. 300, Buffalo, NY 14203, USA.', 'United States|United States|United States', 3, 'Computer Simulation|Database Management Systems|Databases, Protein|Information Dissemination|Information Storage and Retrieval|Internet|Models, Molecular|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth262', '15073011', 'The PDB-Preview database is a dynamic web repository of in-silico predicted three-dimensional (3D) models of experimentally determined structures that are deposited into the PDB but are not yet publicly released, and are kept on-hold. The PDB-Preview database is automatically generated on a weekly basis by the bioinfo.pl meta-server, which uses top-of-the-line fold-recognition methods. The PDB-Preview provides biologists with preliminary fold assignments well before the experimentally determined 3D structures are released.'),
(71319, 2004, 'bio', 'Constructing an enzyme-centric view of metabolism', 'Horne, A B|Hodgman, T C|Spence, H D|Dalby, A R', 'School of Biological and Chemical Sciences, University of Exeter, Washington Singer Laboratories, Exeter, Devon, EX4 4PS, UK.|School of Biological and Chemical Sciences, University of Exeter, Washington Singer Laboratories, Exeter, Devon, EX4 4PS, UK.|School of Biological and Chemical Sciences, University of Exeter, Washington Singer Laboratories, Exeter, Devon, EX4 4PS, UK.|School of Biological and Chemical Sciences, University of Exeter, Washington Singer Laboratories, Exeter, Devon, EX4 4PS, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 40, 'Computer Simulation|Databases, Protein|Enzymes|Metabolism|Models, Biological|Multienzyme Complexes|Protein Interaction Mapping|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/bth199', '15073012', 'The current paradigm for viewing metabolism, such as the Boehringer Chart or KEGG, takes a metabolite-centric view that is not ideal for genomics analysis because the same enzyme can appear in multiple places. Therefore an enzyme-centric view is also required.'),
(71320, 2004, 'bio', 'Educating biologists in the 21st century: bioinformatics scientists versus bioinformatics technicians', 'Pevzner, Pavel A', 'School of Biological and Chemical Sciences, University of Exeter, Washington Singer Laboratories, Exeter, Devon, EX4 4PS, UK.', 'United Kingdom', 31, 'Algorithms|Biology|Computational Biology|Curriculum|Education, Professional|Mathematics|Medical Laboratory Personnel|Science|United States|Universities', 'Comparative Study', '10.1093/bioinformatics/bth217', '15073013', '-'),
(71321, 2004, 'bio', 'An examination of the conservation of surface patch polarity for proteins', 'Shanahan, H P|Thornton, J M', 'European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD,UK. shanahan@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD,UK. shanahan@ebi.ac.uk', 'United Kingdom|United Kingdom', 4, 'Algorithms|Amino Acid Sequence|Amino Acid Substitution|Computer Simulation|Conserved Sequence|Hydrophobic and Hydrophilic Interactions|Models, Chemical|Models, Molecular|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Solubility|Static Electricity|Structure-Activity Relationship|Surface Properties', 'Comparative Study', '10.1093/bioinformatics/bth218', '15073014', 'The solubility of a protein is crucial for its function and is therefore an evolutionary constraint. As the solubility of a protein is related to the distribution of polar and hydrophobic residues on its solvent accessible surface, such a constraint should provide a valuable insight into the evolution of protein surfaces. We examine how the surfaces of proteins have evolved by considering how the average hydrophobicities of patches of surface residues vary across homologous proteins. We derive distributions for the average hydrophobicity/philicity of surface patches at a residue-based level-which we refer to as the residue hydrophobic density. This is computed for a set of 28 monomeric proteins and their homologues. The resulting distributions are compared with a set of randomized sequences, with the same residue content.'),
(71322, 2004, 'bio', 'Bellerophon: a program to detect chimeric sequences in multiple sequence alignments', 'Huber, Thomas|Faulkner, Geoffrey|Hugenholtz, Philip', 'ComBinE group, Advanced Computational Modelling Centre, The University of Queensland, Brisbane 4072, Australia.|ComBinE group, Advanced Computational Modelling Centre, The University of Queensland, Brisbane 4072, Australia.|ComBinE group, Advanced Computational Modelling Centre, The University of Queensland, Brisbane 4072, Australia.', 'Australia|Australia|Australia', 1300, 'Algorithms|Chimera|Conserved Sequence|Evolution, Molecular|Internet|Phylogeny|Polymerase Chain Reaction|Protein Isoforms|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth226', '15073015', 'Bellerophon is a program for detecting chimeric sequences in multiple sequence datasets by an adaption of partial treeing analysis. Bellerophon was specifically developed to detect 16S rRNA gene chimeras in PCR-clone libraries of environmental samples but can be applied to other nucleotide sequence alignments.'),
(71323, 2004, 'bio', 'MedPost: a part-of-speech tagger for bioMedical text', 'Smith, L|Rindflesch, T|Wilbur, W J', 'Computational Biology Branch, National Center for Biotechnology Information.|Computational Biology Branch, National Center for Biotechnology Information.|Computational Biology Branch, National Center for Biotechnology Information.', '-|-|-', 135, 'Abstracting and Indexing as Topic|Biology|Documentation|Information Storage and Retrieval|MEDLINE|Medicine|Natural Language Processing|Periodicals as Topic|Semantics|Software|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/bth227', '15073016', 'We present a part-of-speech tagger that achieves over 97% accuracy on MEDLINE citations.'),
(71324, 2004, 'bio', 'Alignment of RNA base pairing probability matrices', 'Hofacker, Ivo L|Bernhart, Stephan H F|Stadler, Peter F', 'Institut für Theoretische Chemie und Molekulare Strukturbiologie, Universität Wien, Währingerstrasse 17, Vienna, Austria. ivo@tbi.univie.ac.at|Institut für Theoretische Chemie und Molekulare Strukturbiologie, Universität Wien, Währingerstrasse 17, Vienna, Austria. ivo@tbi.univie.ac.at|Institut für Theoretische Chemie und Molekulare Strukturbiologie, Universität Wien, Währingerstrasse 17, Vienna, Austria. ivo@tbi.univie.ac.at', 'Austria|Austria|Austria', 158, 'Algorithms|Base Pairing|Base Sequence|Conserved Sequence|Models, Chemical|Models, Genetic|Models, Statistical|Molecular Sequence Data|RNA|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/bth229', '15073017', 'Many classes of functional RNA molecules are characterized by highly conserved secondary structures but little detectable sequence similarity. Reliable multiple alignments can therefore be constructed only when the shared structural features are taken into account. Since multiple alignments are used as input for many subsequent methods of data analysis, structure-based alignments are an indispensable necessity in RNA bioinformatics.'),
(71325, 2004, 'bio', 'A novel method for estimating ancestral amino acid composition and its application to proteins of the Last Universal Ancestor', 'Brooks, D J|Fresco, J R|Singh, M', 'Department of Genetics, Washington University School of Medicine, St Louis, MO 63110, USA.|Department of Genetics, Washington University School of Medicine, St Louis, MO 63110, USA.|Department of Genetics, Washington University School of Medicine, St Louis, MO 63110, USA.', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Amino Acid Substitution|Animals|Biological Evolution|Conserved Sequence|Evolution, Molecular|Genetic Code|Genetics, Population|Humans|Likelihood Functions|Models, Genetic|Models, Statistical|Molecular Sequence Data|Phylogeny|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/bth235', '15073018', 'Knowledge of how proteomic amino acid composition has changed over time is important for constructing realistic models of protein evolution and increasing our understanding of molecular evolutionary history. The proteomic amino acid composition of the Last Universal Ancestor (LUA) of life is of particular interest, since that might provide insight into the early evolution of proteins and the nature of the LUA itself.'),
(71326, 2004, 'bio', 'Probabilistic representation of gene regulatory networks', 'Mao, Linyong|Resat, Haluk', 'Computational Biosciences Group, Pacific Northwest National Laboratory, PO Box 999, Mail Stop K1-92, Richland, WA 99352, USA.|Computational Biosciences Group, Pacific Northwest National Laboratory, PO Box 999, Mail Stop K1-92, Richland, WA 99352, USA.', 'United States|United States', 16, 'Algorithms|Cell Physiological Phenomena|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Signal Transduction|Stochastic Processes|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bth236', '15073019', 'Recent experiments have established unambiguously that biological systems can have significant cell-to-cell variations in gene expression levels even in isogenic populations. Computational approaches to studying gene expression in cellular systems should capture such biological variations for a more realistic representation.'),
(71327, 2004, 'bio', 'Proteins associated with diseases show enhanced sequence correlation between charged residues', 'Dima, Ruxandra I|Thirumalai, D', 'Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742, USA. dimar@Glue.umd.edu|Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742, USA. dimar@Glue.umd.edu', 'United States|United States', 22, 'Algorithms|Amino Acid Sequence|Amino Acids|Amyloid beta-Peptides|Base Sequence|Biomarkers|Gene Expression Profiling|Humans|Hydrophobic and Hydrophilic Interactions|Models, Molecular|Neurodegenerative Diseases|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Static Electricity|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/bth245', '15073020', 'Function of proteins or a network of interacting proteins often involves communication between residues that are well separated in sequence. The classic example is the participation of distant residues in allosteric regulation. Bioinformatic and structural analysis methods have been introduced to infer residues that are correlated. Recently, increasing attention has been paid to obtain the sequence properties that determine the tendency of disease-related proteins (Abeta peptides, prion proteins, transthyretin, etc.) to aggregate and form fibrils. Motivated in part by the need to identify sequence characteristics that indicate a tendency to aggregate, we introduce a general method that probes covariations in charged residues along the sequence in a given protein family. The method, which involves computing the sequence correlation entropy (SCE) using the quenched probability P(sk)(i,j) of finding a residue pair at a given sequence separation, sk, allows us to classify protein families in terms of their SCE. Our general approach may be a useful way in obtaining evolutionary covariations of amino acid residues on a genome wide level.'),
(71328, 2004, 'bio', 'Supertree algorithms for ancestral divergence dates and nested taxa', 'Semple, Charles|Daniel, Philip|Hordijk, Wim|Page, Roderic D M|Steel, Mike', 'Biomathematics Research Centre, Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand. c.semple@math.canterbury.ac.nz|Biomathematics Research Centre, Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand. c.semple@math.canterbury.ac.nz|Biomathematics Research Centre, Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand. c.semple@math.canterbury.ac.nz|Biomathematics Research Centre, Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand. c.semple@math.canterbury.ac.nz|Biomathematics Research Centre, Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand. c.semple@math.canterbury.ac.nz', 'New Zealand|New Zealand|New Zealand|New Zealand|New Zealand', 0, 'Algorithms|Biological Evolution|Genetic Variation|Genetics, Population|Models, Genetic|Pedigree|Phylogeny', 'Evaluation Studies', '10.1093/bioinformatics/bth246', '15073021', 'Supertree methods have been often identified as a possible approach to the reconstruction of the Tree of Life. However, a limitation of such methods is that, typically, they use just leaf-labelled phylogenetic trees to infer the resulting supertree.'),
(71329, 2004, 'bio', 'An interactive triple-helical collagen builder', 'Rainey, Jan K|Goh, M Cynthia', 'Protein Engineering Network of Centres of Excellence, University of Alberta, Edmonton, AB, T6G 2S2 Canada. jrainey@biochem.ualberta.ca|Protein Engineering Network of Centres of Excellence, University of Alberta, Edmonton, AB, T6G 2S2 Canada. jrainey@biochem.ualberta.ca', 'Canada|Canada', 74, 'Algorithms|Collagen|Computer Simulation|Models, Molecular|Protein Conformation|Protein Structure, Secondary|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth247', '15073022', 'To facilitate the building of triple-helical polypeptide structures, we provide an interactive, platform-independent Tcl/Tk script. User specified amino acid sequences are parsed to obtain localized melting temperature estimates corresponding to helical propensity. These propensities may be graphically examined prior to their automated use in combination with two separate statistical parameter sets to build the complete polypeptide backbone and, if desired, predict side-chain terminal atom locations.'),
(71330, 2004, 'bio', 'POLYVIEW: a flexible visualization tool for structural and functional annotations of proteins', 'Porollo, Aleksey A|Adamczak, Rafal|Meller, Jaroslaw', 'Childrens Hospital Research Foundation, 3333 Burnet Avenue, Cincinnati, OH 45229, USA.|Childrens Hospital Research Foundation, 3333 Burnet Avenue, Cincinnati, OH 45229, USA.|Childrens Hospital Research Foundation, 3333 Burnet Avenue, Cincinnati, OH 45229, USA.', 'United States|United States|United States', 97, 'Algorithms|Computer Graphics|Databases, Protein|Documentation|Models, Molecular|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth248', '15073023', 'The POLYVIEW visualization server can be used to generate protein sequence annotations, including secondary structures, relative solvent accessibilities, functional motifs and polymorphic sites. Two-dimensional graphical representations in a customizable format may be generated for both known protein structures and predictions obtained using protein structure prediction servers. POLYVIEW may be used for automated generation of pictures with structural and functional annotations for publications and proteomic on-line resources.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71331, 2004, 'bio', 'BAPS 2: enhanced possibilities for the analysis of genetic population structure', 'Corander, Jukka|Waldmann, Patrik|Marttinen, Pekka|Sillanpää, Mikko J', 'Rolf Nevanlinna Institute, P.O. Box 4, Fin-00014 University of Helsinki, Finland. jukka.corander@rni.helsinki.fi|Rolf Nevanlinna Institute, P.O. Box 4, Fin-00014 University of Helsinki, Finland. jukka.corander@rni.helsinki.fi|Rolf Nevanlinna Institute, P.O. Box 4, Fin-00014 University of Helsinki, Finland. jukka.corander@rni.helsinki.fi|Rolf Nevanlinna Institute, P.O. Box 4, Fin-00014 University of Helsinki, Finland. jukka.corander@rni.helsinki.fi', 'Finland|Finland|Finland|Finland', 0, 'Algorithms|Chromosome Mapping|Gene Frequency|Genetic Markers|Genetic Testing|Genetic Variation|Genetics, Population|Humans|Markov Chains|Models, Genetic|Models, Statistical|Monte Carlo Method|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth250', '15073024', 'Bayesian statistical methods based on simulation techniques have recently been shown to provide powerful tools for the analysis of genetic population structure. We have previously developed a Markov chain Monte Carlo (MCMC) algorithm for characterizing genetically divergent groups based on molecular markers and geographical sampling design of the dataset. However, for large-scale datasets such algorithms may get stuck to local maxima in the parameter space. Therefore, we have modified our earlier algorithm to support multiple parallel MCMC chains, with enhanced features that enable considerably faster and more reliable estimation compared to the earlier version of the algorithm. We consider also a hierarchical tree representation, from which a Bayesian model-averaged structure estimate can be extracted. The algorithm is implemented in a computer program that features a user-friendly interface and built-in graphics. The enhanced features are illustrated by analyses of simulated data and an extensive human molecular dataset.'),
(71332, 2004, 'bio', 'Pedro: a configurable data entry tool for XML', 'Garwood, Kevin L|Taylor, Chris F|Runte, Kai J|Brass, Andy|Oliver, Stephen G|Paton, Norman W', 'Department of Computer Science, University of Manchester, UK. garwood@cs.man.ac.uk|Department of Computer Science, University of Manchester, UK. garwood@cs.man.ac.uk|Department of Computer Science, University of Manchester, UK. garwood@cs.man.ac.uk|Department of Computer Science, University of Manchester, UK. garwood@cs.man.ac.uk|Department of Computer Science, University of Manchester, UK. garwood@cs.man.ac.uk|Department of Computer Science, University of Manchester, UK. garwood@cs.man.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 22, 'Computer Graphics|Database Management Systems|Databases, Genetic|Documentation|Information Storage and Retrieval|Natural Language Processing|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth251', '15073025', 'Pedro is a Java application that dynamically generates data entry forms for data models expressed in XML Schema, producing XML data files that validate against this schema. The software uses an intuitive tree-based navigation system, can supply context-sensitive help to users and features a sophisticated interface for populating data fields with terms from controlled vocabularies. The software also has the ability to import records from tab delimited text files and features various validation routines.'),
(71333, 2004, 'bio', 'ArrayNorm: comprehensive normalization and analysis of microarray data', 'Pieler, R|Sanchez-Cabo, F|Hackl, H|Thallinger, G G|Trajanoski, Z', 'Institute of Genomics and Bioinformatics and Christian Doppler Laboratory for Genomics and Bioinformatics, Graz University of Technology, 8010 Graz, Austria.|Institute of Genomics and Bioinformatics and Christian Doppler Laboratory for Genomics and Bioinformatics, Graz University of Technology, 8010 Graz, Austria.|Institute of Genomics and Bioinformatics and Christian Doppler Laboratory for Genomics and Bioinformatics, Graz University of Technology, 8010 Graz, Austria.|Institute of Genomics and Bioinformatics and Christian Doppler Laboratory for Genomics and Bioinformatics, Graz University of Technology, 8010 Graz, Austria.|Institute of Genomics and Bioinformatics and Christian Doppler Laboratory for Genomics and Bioinformatics, Graz University of Technology, 8010 Graz, Austria.', 'Austria|Austria|Austria|Austria|Austria', 30, 'Algorithms|Gene Expression Profiling|Internet|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth174', '15073026', 'ArrayNorm is a user-friendly, versatile and platform-independent Java application for the visualization, normalization and analysis of two-color microarray data. A variety of normalization options were implemented to remove the systematic and random errors in the data, taking into account the experimental design and the particularities of every slide. In addition, ArrayNorm provides a module for statistical identification of genes with significant changes in expression.'),
(71334, 2004, 'bio', 'A geometric approach to determine association and coherence of the activation times of cell-cycling genes under differing experimental conditions', 'Liu, Delong|Weinberg, Clarice R|Peddada, Shyamal D', 'Biostatistics Branch, MD:A3-03, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, USA.|Biostatistics Branch, MD:A3-03, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, USA.|Biostatistics Branch, MD:A3-03, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, USA.', 'United States|United States|United States', 7, 'Algorithms|Cell Cycle|Cell Cycle Proteins|Gene Expression Profiling|Gene Expression Regulation|Genes, cdc|Oligonucleotide Array Sequence Analysis|Statistics as Topic|Time Factors', 'Evaluation Studies', '10.1093/bioinformatics/bth274', '15087309', 'Differing arresting agents and protocols can be used to synchronize cells in cultures to specific phases of the cell when studying cell-cycle gene expressions. Often, data derived from individual experiments are analyzed separately, since no appropriate statistical methodology is available at the moment to analyze the data from all such experiments simultaneously. The focus of this paper is to determine the association and coherence of the relative activation times of cell-cycling genes under different experimental conditions. Using a circular-circular regression model, we define two parameters, a rotation parameter for the angular difference between cells arresting times (phases) in two cell-cycle experiments, and an association parameter to describe the correspondence between the cycle times of maximal expression (phase angles) for a set of genes studied in two experiments. Further, we propose a procedure to assess coherence across multiple experiments, i.e. to what extent the circular ordering of the phase angles of genes is maintained across multiple experiments. Coherence of genes across experiments suggests that functionally these genes tend to respond in a stereotypically sequenced way under different experimental conditions. Our proposed methodology is illustrated by applying it to a HeLa cell-cycle gene-expression data.'),
(71335, 2004, 'bio', 'A System for Automated Bacterial (genome) Integrated Annotation--SABIA', 'Almeida, Luiz G P|Paixão, Roger|Souza, Rangel C|Costa, Gisele C da|Barrientos, Frank J A|Santos, M Trindade dos|Almeida, Darcy F de|Vasconcelos, Ana Tereza R', 'Laboratório Nacional de Computação Científica LNCC/MCT, Rua Getúlio Vargas 333, Quitandinha, Petrópolis, RJ, 25651-070, Brazil.|Laboratório Nacional de Computação Científica LNCC/MCT, Rua Getúlio Vargas 333, Quitandinha, Petrópolis, RJ, 25651-070, Brazil.|Laboratório Nacional de Computação Científica LNCC/MCT, Rua Getúlio Vargas 333, Quitandinha, Petrópolis, RJ, 25651-070, Brazil.|Laboratório Nacional de Computação Científica LNCC/MCT, Rua Getúlio Vargas 333, Quitandinha, Petrópolis, RJ, 25651-070, Brazil.|Laboratório Nacional de Computação Científica LNCC/MCT, Rua Getúlio Vargas 333, Quitandinha, Petrópolis, RJ, 25651-070, Brazil.|Laboratório Nacional de Computação Científica LNCC/MCT, Rua Getúlio Vargas 333, Quitandinha, Petrópolis, RJ, 25651-070, Brazil.|Laboratório Nacional de Computação Científica LNCC/MCT, Rua Getúlio Vargas 333, Quitandinha, Petrópolis, RJ, 25651-070, Brazil.|Laboratório Nacional de Computação Científica LNCC/MCT, Rua Getúlio Vargas 333, Quitandinha, Petrópolis, RJ, 25651-070, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 69, 'Algorithms|Chromosome Mapping|Databases, Genetic|Documentation|Genome, Bacterial|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth273', '15087310', 'A web-based software suite, SABIA (System for Automated Bacterial Integrated Annotation), is described that provides a comprehensive computational support for the assembly and annotation of whole bacterial genomes from the data derived from sequencing projects.'),
(71336, 2004, 'bio', 'MathSBML: a package for manipulating SBML-based biological models', 'Shapiro, Bruce E|Hucka, Michael|Finney, Andrew|Doyle, John', 'Jet Propulsion Laboratory, California Institute of Technology, Mail Stop 126-347, 4800 Oak Grove Drive, Pasadena, CA 91109, USA. bshapiro@caltech.edu|Jet Propulsion Laboratory, California Institute of Technology, Mail Stop 126-347, 4800 Oak Grove Drive, Pasadena, CA 91109, USA. bshapiro@caltech.edu|Jet Propulsion Laboratory, California Institute of Technology, Mail Stop 126-347, 4800 Oak Grove Drive, Pasadena, CA 91109, USA. bshapiro@caltech.edu|Jet Propulsion Laboratory, California Institute of Technology, Mail Stop 126-347, 4800 Oak Grove Drive, Pasadena, CA 91109, USA. bshapiro@caltech.edu', 'United States|United States|United States|United States', 38, 'Cell Physiological Phenomena|Computer Simulation|Database Management Systems|Information Storage and Retrieval|Models, Biological|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/bth271', '15087311', 'MathSBML is a Mathematica package designed for manipulating Systems Biology Markup Language (SBML) models. It converts SBML models into Mathematica data structures and provides a platform for manipulating and evaluating these models. Once a model is read by MathSBML, it is fully compatible with standard Mathematica functions such as NDSolve (a differential-algebraic equations solver). MathSBML also provides an application programming interface for viewing, manipulating, running numerical simulations, exporting SBML models, and converting SBML models in to other formats, such as XPP, HTML and FORTRAN. By accessing the full breadth of Mathematica functionality, MathSBML is fully extensible to SBML models of any size or complexity.'),
(71337, 2004, 'bio', 'Metabolite fingerprinting: detecting biological features by independent component analysis', 'Scholz, M|Gatzek, S|Sterling, A|Fiehn, O|Selbig, J', 'Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany. scholz@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany. scholz@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany. scholz@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany. scholz@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, 14424 Potsdam, Germany. scholz@mpimp-golm.mpg.de', 'Germany|Germany|Germany|Germany|Germany', 194, 'Algorithms|Arabidopsis|Arabidopsis Proteins|Gene Expression Profiling|Microchip Analytical Procedures|Microfluidic Analytical Techniques|Models, Biological|Models, Statistical|Principle-Based Ethics|Spectrometry, Mass, Electrospray Ionization', 'Comparative Study', '10.1093/bioinformatics/bth270', '15087312', 'Metabolite fingerprinting is a technology for providing information from spectra of total compositions of metabolites. Here, spectra acquisitions by microchip-based nanoflow-direct-infusion QTOF mass spectrometry, a simple and high throughput technique, is tested for its informative power. As a simple test case we are using Arabidopsis thaliana crosses. The question is how metabolite fingerprinting reflects the biological background. In many applications the classical principal component analysis (PCA) is used for detecting relevant information. Here a modern alternative is introduced-the independent component analysis (ICA). Due to its independence condition, ICA is more suitable for our questions than PCA. However, ICA has not been developed for a small number of high-dimensional samples, therefore a strategy is needed to overcome this limitation.'),
(71338, 2004, 'bio', 'Analysis of longitudinal metabolomics data', 'Jansen, Jeroen J|Hoefsloot, Huub C J|Boelens, Hans F M|van der Greef, Jan|Smilde, Age K', 'Biosystems Data Analysis, Faculty of Sciences, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands.|Biosystems Data Analysis, Faculty of Sciences, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands.|Biosystems Data Analysis, Faculty of Sciences, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands.|Biosystems Data Analysis, Faculty of Sciences, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands.|Biosystems Data Analysis, Faculty of Sciences, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 63, 'Algorithms|Animals|Computer Simulation|Gene Expression Profiling|Macaca mulatta|Magnetic Resonance Spectroscopy|Models, Biological|Principal Component Analysis|Protein Interaction Mapping|Proteins|Signal Transduction|Time Factors|Urinalysis', 'Comparative Study', '10.1093/bioinformatics/bth268', '15087313', 'Metabolomics datasets are generally large and complex. Using principal component analysis (PCA), a simplified view of the variation in the data is obtained. The PCA model can be interpreted and the processes underlying the variation in the data can be analysed. In metabolomics, often a priori information is present about the data. Various forms of this information can be used in an unsupervised data analysis with weighted PCA (WPCA). A WPCA model will give a view on the data that is different from the view obtained using PCA, and it will add to the interpretation of the information in a metabolomics dataset.'),
(71339, 2004, 'bio', 'A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression', 'Li, Tao|Zhang, Chengliang|Ogihara, Mitsunori', 'Computer Science Department, University of Rochester, Rochester, NY 14627-0226, USA.|Computer Science Department, University of Rochester, Rochester, NY 14627-0226, USA.|Computer Science Department, University of Rochester, Rochester, NY 14627-0226, USA.', 'United States|United States|United States', 466, 'Algorithms|Artificial Intelligence|Gene Expression Profiling|Humans|Leukemia|Multivariate Analysis|Neoplasm Proteins|Pattern Recognition, Automated|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth267', '15087314', 'This paper studies the problem of building multiclass classifiers for tissue classification based on gene expression. The recent development of microarray technologies has enabled biologists to quantify gene expression of tens of thousands of genes in a single experiment. Biologists have begun collecting gene expression for a large number of samples. One of the urgent issues in the use of microarray data is to develop methods for characterizing samples based on their gene expression. The most basic step in the research direction is binary sample classification, which has been studied extensively over the past few years. This paper investigates the next step-multiclass classification of samples based on gene expression. The characteristics of expression data (e.g. large number of genes with small sample size) makes the classification problem more challenging. The process of building multiclass classifiers is divided into two components: (i) selection of the features (i.e. genes) to be used for training and testing and (ii) selection of the classification method. This paper compares various feature selection methods as well as various state-of-the-art classification methods on various multiclass gene expression datasets. Our study indicates that multiclass classification problem is much more difficult than the binary one for the gene expression datasets. The difficulty lies in the fact that the data are of high dimensionality and that the sample size is small. The classification accuracy appears to degrade very rapidly as the number of classes increases. In particular, the accuracy was very low regardless of the choices of the methods for large-class datasets (e.g. NCI60 and GCM). While increasing the number of samples is a plausible solution to the problem of accuracy degradation, it is important to develop algorithms that are able to analyze effectively multiple-class expression data for these special datasets.'),
(71340, 2004, 'bio', 'How independent are the appearances of n-mers in different genomes?', 'Fofanov, Yuriy|Luo, Yi|Katili, Charles|Wang, Jim|Belosludtsev, Yuri|Powdrill, Thomas|Belapurkar, Chetan|Fofanov, Viacheslav|Li, Tong-Bin|Chumakov, Sergey|Pettitt, B Montgomery', 'Department of Computer Science, University of Houston, TX 77204-3010, USA. yfofanov@uh.edu|Department of Computer Science, University of Houston, TX 77204-3010, USA. yfofanov@uh.edu|Department of Computer Science, University of Houston, TX 77204-3010, USA. yfofanov@uh.edu|Department of Computer Science, University of Houston, TX 77204-3010, USA. yfofanov@uh.edu|Department of Computer Science, University of Houston, TX 77204-3010, USA. yfofanov@uh.edu|Department of Computer Science, University of Houston, TX 77204-3010, USA. yfofanov@uh.edu|Department of Computer Science, University of Houston, TX 77204-3010, USA. yfofanov@uh.edu|Department of Computer Science, University of Houston, TX 77204-3010, USA. yfofanov@uh.edu|Department of Computer Science, University of Houston, TX 77204-3010, USA. yfofanov@uh.edu|Department of Computer Science, University of Houston, TX 77204-3010, USA. yfofanov@uh.edu|Department of Computer Science, University of Houston, TX 77204-3010, USA. yfofanov@uh.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 46, 'Algorithms|Base Sequence|Chromosome Mapping|Conserved Sequence|DNA Fingerprinting|Evolution, Molecular|Models, Genetic|Models, Statistical|Molecular Sequence Data|Oligonucleotides|Sequence Alignment|Sequence Analysis, DNA|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/bth266', '15087315', 'Analysis of statistical properties of DNA sequences is important for evolutional biology as well as for DNA probe and PCR technologies. These technologies, in turn, can be used for organism identification, which implies applications in the diagnosis of infectious diseases, environmental studies, etc.'),
(71341, 2004, 'bio', 'Sfixem--graphical sequence feature display in Java', 'Chalk, Alistair M|Wennerberg, Martin|Sonnhammer, Erik L L', 'Center for Genomics and Bioinformatics, Karolinska Institutet, 17177 Stockholm, Sweden. Alistair.Chalk@cgb.ki.se|Center for Genomics and Bioinformatics, Karolinska Institutet, 17177 Stockholm, Sweden. Alistair.Chalk@cgb.ki.se|Center for Genomics and Bioinformatics, Karolinska Institutet, 17177 Stockholm, Sweden. Alistair.Chalk@cgb.ki.se', 'Sweden|Sweden|Sweden', 2, 'Algorithms|Computer Graphics|Information Storage and Retrieval|Programming Languages|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth265', '15087316', 'Sfixem is an sequence feature series (SFS) visualization tool implemented in Java. It is designed to visualize data from sequence analysis programs, allowing the user to view multiple sets of computationally generated analysis to assist the analysis process. SFS is used as the data exchange format.'),
(71342, 2004, 'bio', 'Explicit formulation of different receptor-G-protein interactions and effector regulation', 'Kukkonen, Jyrki P', 'Department of Neuroscience, Unit of Physiology, Uppsala University, BMC, P.O. Box 572, SE-75123 Uppsala, Sweden. jyrki.kukkonen@fysiologi.uu.se', 'Sweden', 5, 'Adaptation, Physiological|Binding Sites|Computer Simulation|GTP-Binding Proteins|Models, Biological|Models, Chemical|Protein Binding|Protein Interaction Mapping|Receptors, G-Protein-Coupled|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bth263', '15087317', 'G-protein-coupled receptors (GPCRs) can create different intracellular signals depending on which G-proteins they couple to and which intracellular signal-integrators, such as adenylyl cyclases, are expressed in the cell. One and the same GPCR can activate multiple G-protein species, generating signals, which either inhibit or amplify each other. Because of this complexity, extraction of mechanistic information from concentration-response curves is not straightforward.'),
(71343, 2004, 'bio', 'The SRS 3D module: integrating structures, sequences and features', 'ODonoghue, Seán I|Meyer, Joachim E W|Schafferhans, Andrea|Fries, Karsten', 'LION bioscience AG, Waldhofer Strasse 98, 69123 Heidelberg, Germany. contact@lionbioscience.com|LION bioscience AG, Waldhofer Strasse 98, 69123 Heidelberg, Germany. contact@lionbioscience.com|LION bioscience AG, Waldhofer Strasse 98, 69123 Heidelberg, Germany. contact@lionbioscience.com|LION bioscience AG, Waldhofer Strasse 98, 69123 Heidelberg, Germany. contact@lionbioscience.com', 'Germany|Germany|Germany|Germany', 14, 'Database Management Systems|Databases, Protein|Information Storage and Retrieval|Models, Molecular|Protein Conformation|Proteins|Sequence Analysis, Protein|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth260', '15087318', 'In this paper we present SRS 3D, a new service that allows users to easily and rapidly find all related structures for a given target sequence, structures can then be viewed together with sequences, alignments and sequence features (currently from UniProt, InterPro and PDB). Extensive user feedback confirms that SRS 3D is intuitive and useful especially for those not expert in structures.'),
(71344, 2004, 'bio', 'An online database for the detection of novel archaeal sequences in human ESTs', 'Saunders, Neil F W|Curmi, Paul M G|Cavicchioli, Ricardo', 'School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, Australia. neil.saunders@unsw.edu.au|School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, Australia. neil.saunders@unsw.edu.au|School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, Australia. neil.saunders@unsw.edu.au', 'Australia|Australia|Australia', 0, 'Algorithms|Archaea|Conserved Sequence|Databases, Genetic|Evolution, Molecular|Expressed Sequence Tags|Genetic Testing|Genome, Archaeal|Genome, Human|Humans|Information Storage and Retrieval|Internet|Online Systems|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Evaluation Studies', '10.1093/bioinformatics/bth249', '15087319', 'We have developed a rapid, automated screening system and online database to detect foreign sequences of archaeal origin in human expressed sequence tags. The aim of the screening is to detect transcripts that may be derived from novel, putative archaeal pathogens or symbionts.'),
(71345, 2004, 'bio', 'SAD--a normalized structural alignment database: improving sequence-structure alignments', 'Marsden, Brian|Abagyan, Ruben', 'The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA. marsden@scripps.edu|The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA. marsden@scripps.edu', 'United States|United States', 8, 'Algorithms|Amino Acid Sequence|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis|Sequence Homology, Amino Acid', 'Evaluation Studies', '10.1093/bioinformatics/bth244', '15087320', 'We present a structural alignment database that is specifically targeted for use in derivation and optimization of sequence-structure alignment algorithms for homology modeling. We have paid attention to ensure that fold-space is properly sampled, that the structures involved in alignments are of significant resolution (better than 2.5 A) and the alignments are accurate and reliable.'),
(71346, 2004, 'bio', 'Sequence optimization as an alternative to de novo analysis of tandem mass spectrometry data', 'Heredia-Langner, Alejandro|Cannon, William R|Jarman, Kenneth D|Jarman, Kristin H', 'Statistical and Mathematical Sciences, Northwest National Laboratory, Richland, WA 99352, USA. Alejandro-Heredia_Langner@pnl.gov|Statistical and Mathematical Sciences, Northwest National Laboratory, Richland, WA 99352, USA. Alejandro-Heredia_Langner@pnl.gov|Statistical and Mathematical Sciences, Northwest National Laboratory, Richland, WA 99352, USA. Alejandro-Heredia_Langner@pnl.gov|Statistical and Mathematical Sciences, Northwest National Laboratory, Richland, WA 99352, USA. Alejandro-Heredia_Langner@pnl.gov', 'United States|United States|United States|United States', 27, 'Algorithms|Amino Acid Sequence|Complex Mixtures|Mass Spectrometry|Molecular Sequence Data|Peptides|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bth242', '15087321', 'Peptide identification following tandem mass spectrometry (MS/MS) is usually achieved by searching for the best match between the mass spectrum of an unidentified peptide and model spectra generated from peptides in a sequence database. This methodology will be successful only if the peptide under investigation belongs to an available database. Our objective is to develop and test the performance of a heuristic optimization algorithm capable of dealing with some features commonly found in actual MS/MS spectra that tend to stop simpler deterministic solution approaches.'),
(71347, 2004, 'bio', 'PINdb: a database of nuclear protein complexes from human and yeast', 'Luc, Phuong-Van|Tempst, Paul', 'Molecular Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.|Molecular Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.', 'United States|United States', 34, 'Abstracting and Indexing as Topic|Database Management Systems|Databases, Protein|Fungal Proteins|Humans|Information Storage and Retrieval|Internet|Multiprotein Complexes|Natural Language Processing|Nuclear Proteins|Periodicals as Topic|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth114', '15087322', 'Proteins Interacting in the Nucleus database (PINdb) is a database of protein complexes purified from the nucleus of human and yeast cells. It is compiled from the published literature and existing databases. Currently, PINdb contains mostly protein complexes that may be involved in gene transcription. To facilitate comparative analyses and identification of protein complexes, the compositional information is integrated with standardized gene nomenclature, annotation and protein sequences from public databases. The PINdb web interface provides a number of tools for (1) comparison of protein complexes, (2) search for a protein complex by its published name or by a partial list of its components and (3) browsing specific subsets or a functional classification of the complexes. Availablity: http://pin.mskcc.org'),
(71348, 2004, 'bio', 'ProteoMix: an integrated and flexible system for interactively analyzing large numbers of protein sequences', 'Chikayama, Eisuke|Kurotani, Atsushi|Kuroda, Yutaka|Yokoyama, Shigeyuki', 'Protein Research Group, RIKEN Genomic Sciences Center, 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan.|Protein Research Group, RIKEN Genomic Sciences Center, 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan.|Protein Research Group, RIKEN Genomic Sciences Center, 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan.|Protein Research Group, RIKEN Genomic Sciences Center, 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan.', 'Japan|Japan|Japan|Japan', 7, 'Database Management Systems|Databases, Protein|Information Storage and Retrieval|Programming Languages|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth276', '15105278', 'ProteoMix is a suite of JAVA programs for identifying, annotating and predicting regions of interest in large sets of amino acid sequences, according to systematic and consistent criteria. It is based on two concepts (1) the integration of results from different sequence analysis tools increases the prediction reliability, and (2) the integration protocol is critical and needs to be easily adaptable in a case-by-case manner. ProteoMix was designed to analyze simultaneously multiple protein sequences using several bioinformatics tools, merge the results of the analyses using logical functions and display them on an integrated viewer. In addition, new sequences can be added seamlessly to an analysis performed on an initial set of sequences. ProteoMix has a modular design, and bioinformatics tools are run on remote servers accessed using the Internet Simple Object Access Protocol (SOAP), ensuring the swift implementation of additional tools. ProteoMix has a user-friendly interactive graphical user interface environment and runs on PCs with Microsoft OS.'),
(71349, 2004, 'bio', 'GDPC: connecting researchers with multiple integrated data sources', 'Casstevens, Terry M|Buckler, Edward S', 'Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853-2703, USA. terry_casstevens@hotmail.com|Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853-2703, USA. terry_casstevens@hotmail.com', 'United States|United States', 7, 'Database Management Systems|Databases, Genetic|Genetic Variation|Information Dissemination|Information Storage and Retrieval|Internet|Phenotype|Programming Languages|Research|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth277', '15105279', 'The goal of this project is to simplify access to genomic diversity and phenotype data, thereby encouraging reuse of this data. The Genomic Diversity and Phenotype Connection (GDPC) accomplishes this by retrieving data from one or more data sources and by allowing researchers to analyze integrated data in a standard format. GDPC is written in JAVA and provides (1) data sources available as web services that transfer XML formatted data via the SOAP protocol, (2) a JAVA API for programmatic access to data sources, and (3) a front-end application that allows users to manage data sources, retrieve data based on filters, sort/group data based on property values and save/open the data as XML files.'),
(71350, 2004, 'bio', 'PaVESy: Pathway Visualization and Editing System', 'Lüdemann, Alexander|Weicht, Daniel|Selbig, Joachim|Kopka, Joachim', 'Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany. luedemann@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany. luedemann@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany. luedemann@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany. luedemann@mpimp-golm.mpg.de', 'Germany|Germany|Germany|Germany', 28, 'Database Management Systems|Databases, Factual|Documentation|Gene Expression Regulation|Information Storage and Retrieval|Models, Biological|Signal Transduction|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth278', '15105280', 'A data managing system for editing and visualization of biological pathways is presented. The main component of PaVESy (Pathway Visualization and Editing System) is a relational SQL database system. The database design allows storage of biological objects, such as metabolites, proteins, genes and respective relations, which are required to assemble metabolic and regulatory biological interactions. The database model accommodates highly flexible annotation of biological objects by user-defined attributes. In addition, specific roles of objects are derived from these attributes in the context of user-defined interactions, e.g. in the course of pathway generation or during editing of the database content. Furthermore, the user may organize and arrange the database content within a folder structure and is free to group and annotate database objects of interest within customizable subsets. Thus, we allow an individualized view on the database content and facilitate user customization. A JAVA-based class library was developed, which serves as the database programming interface to PaVESy. This API provides classes, which implement the concepts of object persistence in SQL databases, such as entries, interactions, annotations, folders and subsets. We created editing and visualization tools for navigation in and visualization of the database content. User approved pathway assemblies are stored and may be retrieved for continued modification, annotation and export. Data export is interfaced with a range of network visualization programs, such as Pajek or other software allowing import of SBML or GML data format.'),
(71351, 2004, 'bio', 'YAdumper: extracting and translating large information volumes from relational databases to structured flat files', 'Fernández, José M|Valencia, Alfonso', 'Protein Design Group, National Center for Biotechnology, CNB-CSIC Cantoblanco, Madrid 28049, Spain. jmfernandez@cnb.uam.es|Protein Design Group, National Center for Biotechnology, CNB-CSIC Cantoblanco, Madrid 28049, Spain. jmfernandez@cnb.uam.es', 'Spain|Spain', 1, 'Algorithms|Computational Biology|Database Management Systems|Databases, Factual|Electronic Data Processing|Information Dissemination|Information Storage and Retrieval|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth243', '15117748', 'Downloading the information stored in relational databases into XML and other flat formats is a common task in bioinformatics. This periodical dumping of information requires considerable CPU time, disk and memory resources. YAdumper has been developed as a purpose-specific tool to deal with the integral structured information download of relational databases. YAdumper is a Java application that organizes database extraction following an XML template based on an external Document Type Declaration. Compared with other non-native alternatives, YAdumper substantially reduces memory requirements and considerably improves writing performance.'),
(71352, 2004, 'bio', 'HPID: the Human Protein Interaction Database', 'Han, Kyungsook|Park, Byungkyu|Kim, Hyongguen|Hong, Jinsun|Park, Jong', 'School of Computer Science and Engineering, Inha University, Inchon 402-751, Korea. khan@inha.ac.kr|School of Computer Science and Engineering, Inha University, Inchon 402-751, Korea. khan@inha.ac.kr|School of Computer Science and Engineering, Inha University, Inchon 402-751, Korea. khan@inha.ac.kr|School of Computer Science and Engineering, Inha University, Inchon 402-751, Korea. khan@inha.ac.kr|School of Computer Science and Engineering, Inha University, Inchon 402-751, Korea. khan@inha.ac.kr', '-|-|-|-|-', 64, 'Algorithms|Databases, Protein|Genome, Human|Humans|Information Storage and Retrieval|Protein Interaction Mapping|Proteome|Sequence Alignment|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth253', '15117749', 'The Human Protein Interaction Database (http://www.hpid.org) was designed (1) to provide human protein interaction information pre-computed from existing structural and experimental data, (2) to predict potential interactions between proteins submitted by users and (3) to provide a depository for new human protein interaction data from users. Two types of interaction are available from the pre-computed data: (1) interactions at the protein superfamily level and (2) those transferred from the interactions of yeast proteins. Interactions at the superfamily level were obtained by locating known structural interactions of the PDB in the SCOP domains and identifying homologs of the domains in the human proteins. Interactions transferred from yeast proteins were obtained by identifying homologs of the yeast proteins in the human proteins. For each human protein in the database and each query submitted by users, the protein superfamilies and yeast proteins assigned to the protein are shown, along with their interacting partners. We have also developed a set of web-based programs so that users can visualize and analyze protein interaction networks in order to explore the networks further.'),
(71353, 2004, 'bio', 'SIMCOAL 20: a program to simulate genomic diversity over large recombining regions in a subdivided population with a complex history', 'Laval, Guillaume|Excoffier, Laurent', 'Computational and Molecular Population Genetics, Zoological Institute, University of Bern, Baltzerstrasse 6, Bern CH-3012, Switzerland. guillaume.laval@zoo.unibe.ch|Computational and Molecular Population Genetics, Zoological Institute, University of Bern, Baltzerstrasse 6, Bern CH-3012, Switzerland. guillaume.laval@zoo.unibe.ch', 'Switzerland|Switzerland', 201, 'Algorithms|Biological Evolution|Chromosome Mapping|Computer Simulation|Genetic Variation|Genetics, Population|Models, Genetic|Models, Statistical|Polymorphism, Single Nucleotide|Recombination, Genetic', 'Journal Article', '10.1093/bioinformatics/bth264', '15117750', 'We present an extension of the program SIMCOAL, which allows for simulation of the genomic diversity of samples drawn from a set of populations with arbitrary patterns of migrations and complex demographic histories, including bottlenecks and various modes of demographic expansion. The main additions to the previous version include the possibility of arbitrary and heterogeneous recombination rates between adjacent loci and multiple coalescent events per generation, allowing for the simulation of very large samples and recombining genomic regions, together with the simulation of single nucleotide polymorphism data with frequency ascertainment bias.'),
(71354, 2004, 'bio', 'Efficient combination of multiple word models for improved sequence comparison', 'Huang, Xiaoqiu|Ye, Liang|Chou, Hui-Hsien|Yang, I-Hsuan|Chao, Kun-Mao', 'Department of Computer Science, Iowa State University, Ames, IA 50011-1040, USA. xqhuang@cs.iastate.edu|Department of Computer Science, Iowa State University, Ames, IA 50011-1040, USA. xqhuang@cs.iastate.edu|Department of Computer Science, Iowa State University, Ames, IA 50011-1040, USA. xqhuang@cs.iastate.edu|Department of Computer Science, Iowa State University, Ames, IA 50011-1040, USA. xqhuang@cs.iastate.edu|Department of Computer Science, Iowa State University, Ames, IA 50011-1040, USA. xqhuang@cs.iastate.edu', 'United States|United States|United States|United States|United States', 8, 'Algorithms|Gene Expression Profiling|Models, Genetic|Models, Statistical|Natural Language Processing|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth279', '15117751', 'Studies of efficient and sensitive sequence comparison methods are driven by a need to find homologous regions of weak similarity between large genomes.'),
(71355, 2004, 'bio', 'Interactively optimizing signal-to-noise ratios in expression profiling: project-specific algorithm selection and detection p-value weighting in Affymetrix microarrays', 'Seo, Jinwook|Bakay, Marina|Chen, Yi-Wen|Hilmer, Sara|Shneiderman, Ben|Hoffman, Eric P', 'Research Center for Genetic Medicine, Childrens National Medical Center, MD, USA.|Research Center for Genetic Medicine, Childrens National Medical Center, MD, USA.|Research Center for Genetic Medicine, Childrens National Medical Center, MD, USA.|Research Center for Genetic Medicine, Childrens National Medical Center, MD, USA.|Research Center for Genetic Medicine, Childrens National Medical Center, MD, USA.|Research Center for Genetic Medicine, Childrens National Medical Center, MD, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Cluster Analysis|Computer-Aided Design|Equipment Design|Equipment Failure Analysis|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Sequence Alignment|Sequence Analysis, DNA|Software|Stochastic Processes|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth280', '15117752', 'The most commonly utilized microarrays for mRNA profiling (Affymetrix) include probe sets of a series of perfect match and mismatch probes (typically 22 oligonucleotides per probe set). There are an increasing number of reported probe set algorithms that differ in their interpretation of a probe set to derive a single normalized signal representative of expression of each mRNA. These algorithms are known to differ in accuracy and sensitivity, and optimization has been done using a small set of standardized control microarray data. We hypothesized that different mRNA profiling projects have varying sources and degrees of confounding noise, and that these should alter the choice of a specific probe set algorithm. Also, we hypothesized that use of the Microarray Suite (MAS) 5.0 probe set detection p-value as a weighting function would improve the performance of all probe set algorithms.'),
(71356, 2004, 'bio', 'Class discovery and classification of tumor samples using mixture modeling of gene expression data--a unified approach', 'Alexandridis, Roxana|Lin, Shili|Irwin, Mark', 'Department of Statistics, Ohio State University, 1958 Neil Avenue, Columbus, OH 43210, USA.|Department of Statistics, Ohio State University, 1958 Neil Avenue, Columbus, OH 43210, USA.|Department of Statistics, Ohio State University, 1958 Neil Avenue, Columbus, OH 43210, USA.', 'United States|United States|United States', 0, 'Algorithms|Gene Expression Profiling|Genetic Testing|Humans|Leukemia|Models, Genetic|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bth281', '15117753', 'The DNA microarray technology has been increasingly used in cancer research. In the literature, discovery of putative classes and classification to known classes based on gene expression data have been largely treated as separate problems. This paper offers a unified approach to class discovery and classification, which we believe is more appropriate, and has greater applicability, in practical situations.'),
(71357, 2004, 'bio', 'Identification of DNA regulatory motifs using Bayesian variable selection', 'Tadesse, Mahlet G|Vannucci, Marina|Liò, Pietro', 'Department of Biostatistics and Epidemiology, University of Pennsylvania, PA 19104, USA.|Department of Biostatistics and Epidemiology, University of Pennsylvania, PA 19104, USA.|Department of Biostatistics and Epidemiology, University of Pennsylvania, PA 19104, USA.', 'United States|United States|United States', 30, 'Algorithms|Amino Acid Motifs|Bayes Theorem|Chromosome Mapping|Gene Expression Profiling|Gene Expression Regulation, Fungal|Genes, Regulator|Genetic Variation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth282', '15117754', 'Understanding the mechanisms that determine gene expression regulation is an important and challenging problem. A common approach consists of identifying DNA-binding sites from a collection of co-regulated genes and their nearby non-coding DNA sequences. Here, we consider a regression model that linearly relates gene expression levels to a sequence matching score of nucleotide patterns. We use Bayesian models and stochastic search techniques to select transcription factor binding site candidates, as an alternative to stepwise regression procedures used by other investigators.'),
(71358, 2004, 'bio', 'The database of epoxide hydrolases and haloalkane dehalogenases: one structure, many functions', 'Barth, Sandra|Fischer, Markus|Schmid, Rolf D|Pleiss, Jürgen', 'Institute of Technical Biochemistry, University of Stuttgart, Allmandring 31, D-70569 Stuttgart, Germany.|Institute of Technical Biochemistry, University of Stuttgart, Allmandring 31, D-70569 Stuttgart, Germany.|Institute of Technical Biochemistry, University of Stuttgart, Allmandring 31, D-70569 Stuttgart, Germany.|Institute of Technical Biochemistry, University of Stuttgart, Allmandring 31, D-70569 Stuttgart, Germany.', 'Germany|Germany|Germany|Germany', 17, 'Amino Acid Motifs|Amino Acid Sequence|Binding Sites|Conserved Sequence|Databases, Protein|Documentation|Epoxide Hydrolases|Hydrolases|Molecular Sequence Data|Protein Binding|Protein Conformation|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship|Substrate Specificity', 'Journal Article', '10.1093/bioinformatics/bth284', '15117755', 'The epoxide hydrolases and haloalkane dehalogenases database (EH/HD) integrates sequence and structure of a highly diverse protein family, including mainly the Asp-hydrolases of EHs and HDs but also proteins, such as Ser-hydrolases non-heme peroxidases, prolyl iminopetidases and 2-hydroxymuconic semialdehyde hydrolases. These proteins have a highly conserved structure, but display a remarkable diversity in sequence and function. A total of 305 protein entries were assigned to 14 homologous families, forming two superfamilies. Annotated multisequence alignments and phylogenetic trees are provided for each homologous family and superfamily. Experimentally derived structures of 19 proteins are superposed and consistently annotated. Sequence and structure of all 305 proteins were systematically analysed. Thus, deeper insight is gained into the role of a highly conserved sequence motifs and structural elements.'),
(71359, 2004, 'bio', 'A mixture model-based strategy for selecting sets of genes in multiclass response microarray experiments', 'Broët, Philippe|Lewin, Alex|Richardson, Sylvia|Dalmasso, Cyril|Magdelenat, Henri', 'INSERM U472, 16 Avenue Paul Vaillant Couturier, 94807 Villejuif Cedex, France. broet@vjf.inserm.fr|INSERM U472, 16 Avenue Paul Vaillant Couturier, 94807 Villejuif Cedex, France. broet@vjf.inserm.fr|INSERM U472, 16 Avenue Paul Vaillant Couturier, 94807 Villejuif Cedex, France. broet@vjf.inserm.fr|INSERM U472, 16 Avenue Paul Vaillant Couturier, 94807 Villejuif Cedex, France. broet@vjf.inserm.fr|INSERM U472, 16 Avenue Paul Vaillant Couturier, 94807 Villejuif Cedex, France. broet@vjf.inserm.fr', 'France|France|France|France|France', 47, 'Algorithms|Breast Neoplasms|Gene Expression Profiling|Humans|Models, Genetic|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis', 'Comparative Study', '10.1093/bioinformatics/bth285', '15117756', 'Multiclass response (MCR) experiments are those in which there are more than two classes to be compared. In these experiments, though the null hypothesis is simple, there are typically many patterns of gene expression changes across the different classes that led to complex alternatives. In this paper, we propose a new strategy for selecting genes in MCR that is based on a flexible mixture model for the marginal distribution of a modified F-statistic. Using this model, false positive and negative discovery rates can be estimated and combined to produce a rule for selecting a subset of genes. Moreover, the method proposed allows calculation of these rates for any predefined subset of genes.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71360, 2004, 'bio', 'Predicting allergenic proteins using wavelet transform', 'Li, Kuo-Bin|Issac, Praveen|Krishnan, Arun', 'Bioinformatics Institute, 30 Biopolis Street, Singapore 138671, Singapore. kuobin@bii.a-star.edu.sg|Bioinformatics Institute, 30 Biopolis Street, Singapore 138671, Singapore. kuobin@bii.a-star.edu.sg|Bioinformatics Institute, 30 Biopolis Street, Singapore 138671, Singapore. kuobin@bii.a-star.edu.sg', 'Singapore|Singapore|Singapore', 0, 'Algorithms|Allergens|Amino Acid Motifs|Cluster Analysis|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bth286', '15117757', 'With many transgenic proteins introduced today, the ability to predict their potential allergenicity has become an important issue. Previous studies were based on either sequence similarity or the protein motifs identified from known allergen databases. The similarity-based approaches, although being able to produce high recalls, usually have low prediction precisions. Previous motif-based approaches have been shown to be able to improve the precisions on cross-validation experiments. In this study, a system that combines the advantages of similarity-based and motif-based prediction is described.'),
(71361, 2004, 'bio', 'RRE: a tool for the extraction of non-coding regions surrounding annotated genes from genomic datasets', 'Lazzarato, F|Franceschinis, G|Botta, M|Cordero, F|Calogero, R A', 'Department of Informatics, University of Piemonte Orientale Amedeo Avogadro, Spalto Marengo 33, Alessandria, Italy.|Department of Informatics, University of Piemonte Orientale Amedeo Avogadro, Spalto Marengo 33, Alessandria, Italy.|Department of Informatics, University of Piemonte Orientale Amedeo Avogadro, Spalto Marengo 33, Alessandria, Italy.|Department of Informatics, University of Piemonte Orientale Amedeo Avogadro, Spalto Marengo 33, Alessandria, Italy.|Department of Informatics, University of Piemonte Orientale Amedeo Avogadro, Spalto Marengo 33, Alessandria, Italy.', 'Italy|Italy|Italy|Italy|Italy', 11, 'Chromosome Mapping|Database Management Systems|Databases, Nucleic Acid|Documentation|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Software|Untranslated Regions', 'Journal Article', '10.1093/bioinformatics/bth287', '15117758', 'RRE allows the extraction of non-coding regions surrounding a coding sequence [i.e. gene upstream region, 5-untranslated region (5-UTR), introns, 3-UTR, downstream region] from annotated genomic datasets available at NCBI.'),
(71362, 2004, 'bio', 'Genome wide identification and classification of alternative splicing based on EST data', 'Gupta, S|Zink, D|Korn, B|Vingron, M|Haas, S A', 'Computational Molecular Biology Max Planck Institute for Molecular Genetics, Ihnestrasse 73, D-14195 Berlin, Germany. gupta@molgen.mpg.de|Computational Molecular Biology Max Planck Institute for Molecular Genetics, Ihnestrasse 73, D-14195 Berlin, Germany. gupta@molgen.mpg.de|Computational Molecular Biology Max Planck Institute for Molecular Genetics, Ihnestrasse 73, D-14195 Berlin, Germany. gupta@molgen.mpg.de|Computational Molecular Biology Max Planck Institute for Molecular Genetics, Ihnestrasse 73, D-14195 Berlin, Germany. gupta@molgen.mpg.de|Computational Molecular Biology Max Planck Institute for Molecular Genetics, Ihnestrasse 73, D-14195 Berlin, Germany. gupta@molgen.mpg.de', 'Germany|Germany|Germany|Germany|Germany', 64, 'Algorithms|Alternative Splicing|Artificial Intelligence|Chromosome Mapping|Chromosomes, Human|Consensus Sequence|Expressed Sequence Tags|Humans|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth288', '15117759', 'Alternative splicing is currently seen to explain the vast disparity between the number of predicted genes in the human genome and the highly diverse proteome. The mapping of expressed sequences tag (EST) consensus sequences derived from the GeneNest database onto the genome provides an efficient way of predicting exon-intron boundaries, gene structure and alternative splicing events. However, the alternative splicing events are obscured by a large number of putatively artificial exon boundaries arising due to genomic contamination or alignment errors. The current work describes a methodology to associate quality values to the predicted exon-intron boundaries. High quality exon-intron boundaries are used to predict constitutive and alternative splicing ranked by confidence values, aiming to facilitate large-scale analysis of alternative splicing and splicing in general.'),
(71363, 2004, 'bio', 'Gene-Ontology-based clustering of gene expression data', 'Adryan, Boris|Schuh, Reinhard', 'Department of Molecular Developmental Biology, Max-Planck-Institute for Biophysical Chemistry, 37077 Göttingen, Germany. boris.adryan@mpi-bpc.mpg.de|Department of Molecular Developmental Biology, Max-Planck-Institute for Biophysical Chemistry, 37077 Göttingen, Germany. boris.adryan@mpi-bpc.mpg.de', 'Germany|Germany', 40, 'Cluster Analysis|Database Management Systems|Databases, Protein|Documentation|Gene Expression Profiling|Proteins|Software|Terminology as Topic|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth289', '15117760', 'The expected correlation between genetic co-regulation and affiliation to a common biological process is not necessarily the case when numerical cluster algorithms are applied to gene expression data. GO-Cluster uses the tree structure of the Gene Ontology database as a framework for numerical clustering, and thus allowing a simple visualization of gene expression data at various levels of the ontology tree.'),
(71364, 2004, 'bio', 'Analyzing time series gene expression data', 'Bar-Joseph, Ziv', 'School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15217, USA. zivbj@cs.cmu.edu', 'United States', 0, 'Adaptation, Physiological|Algorithms|Animals|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Signal Transduction|Time Factors', 'Journal Article', '10.1093/bioinformatics/bth283', '15130923', 'Time series expression experiments are an increasingly popular method for studying a wide range of biological systems. However, when analyzing these experiments researchers face many new computational challenges. Algorithms that are specifically designed for time series experiments are required so that we can take advantage of their unique features (such as the ability to infer causality from the temporal response pattern) and address the unique problems they raise (e.g. handling the different non-uniform sampling rates).'),
(71365, 2004, 'bio', 'WebSIDD: server for predicting stress-induced duplex destabilized (SIDD) sites in superhelical DNA', 'Bi, Chengpeng|Benham, Craig J', 'UC Davis Genome Center, University of California, One Shields Avenue, Davis, CA 95616, USA.|UC Davis Genome Center, University of California, One Shields Avenue, Davis, CA 95616, USA.', 'United States|United States', 0, 'Algorithms|Computing Methodologies|DNA|DNA Damage|Internet|Models, Chemical|Models, Molecular|Nucleic Acid Conformation|Nucleic Acid Denaturation|Online Systems|Oxidative Stress|Sequence Analysis, DNA|Software|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bth304', '15130924', 'WebSIDD is a Web-based service designed to predict locations and extents of stress-induced duplex destabilization (SIDD) that occur in a double-stranded DNA molecule of specified base sequence, on which a specified level of superhelical stress is imposed. The algorithm calculates the approximate equilibrium statistical mechanical distribution of a population of identical molecules among its accessible states. The user inputs the DNA sequence, and the program outputs the calculated transition probability and destabilization energy of each base pair in the sequence. As options, the user can specify the temperature and the level of superhelicity. The values of all structural and energy parameters used in the calculation have been experimentally measured. WebSIDD should prove useful for finding SIDD-susceptible sites in genomic sequences, and correlating their occurrence with locations involved in regulatory and pathological processes. This strategy already has illuminated the roles of SIDD in diverse biological regulatory processes, including transcriptional initiation and termination, and the eukaryotic nuclear scaffold attachments that partition chromosomes into domains.'),
(71366, 2004, 'bio', 'SWAPSC: sliding window analysis procedure to detect selective constraints', 'Fares, Mario A', 'Department of Biology, National University of Ireland, Maynooth, Co. Kildare, Ireland. mario.fares@may.ie', 'Ireland', 32, 'Algorithms|DNA Mutational Analysis|Databases, Nucleic Acid|Databases, Protein|Evolution, Molecular|Genetic Variation|Information Storage and Retrieval|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/bth303', '15130925', 'Sliding-window analysis procedure to detect selective constraints (SWAPSC) is a software system to dissect the constraints on the evolution of protein-coding genes. The program estimates rates of nucleotide substitutions at specific codon regions in each branch of a phylogenetic tree. The program uses several sets of simulated sequence alignments to estimate the probability of synonymous and non-synonymous nucleotide substitutions. Thereafter, a statistical analysis is conducted to determine the optimum window size to detect selective constraints. Finally, the optimum window size is slid along the real alignment and a test for significance of the estimated number of synonymous and non-synonymous nucleotide substitutions in each sliding step is conducted. A number of friendly useful output files is generated.'),
(71367, 2004, 'bio', 'LUCY2: an interactive DNA sequence quality trimming and vector removal tool', 'Li, Song|Chou, Hui-Hsien', 'Department of Computer Science, Iowa State University, Ames, IA 50011, USA.|Department of Computer Science, Iowa State University, Ames, IA 50011, USA.', 'United States|United States', 89, 'Algorithms|Artifacts|Genetic Vectors|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth302', '15130926', 'Lucy2 is a raw DNA sequence trimming and visualization tool based on the popular command-line Lucy1. Users can change parameters, trim multiple sequences and visualize the results within an integrated, easy-to-use graphical user interface. Lucy2 is designed specifically for non-programmers to use, and is currently available on Windows, Linux and MacOS X. Source code is also available for porting to the other platforms.'),
(71368, 2004, 'bio', 'Heterogeneity detector: finding heterogeneous positions in Phred/Phrap assemblies', 'Lee, W H|Vega, V B', 'Genome Institute of Singapore, Information and Mathematical Sciences, Singapore, 138672, Singapore. leewhc@gis.a-star.edu.sg|Genome Institute of Singapore, Information and Mathematical Sciences, Singapore, 138672, Singapore. leewhc@gis.a-star.edu.sg', 'Singapore|Singapore', 0, 'Algorithms|Base Pair Mismatch|Consensus Sequence|DNA Mutational Analysis|Genetic Heterogeneity|SARS Virus|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Comparative Study', '10.1093/bioinformatics/bth301', '15130927', 'A modification to Phred and program to detect heterogeneous positions, which is particularly useful in the identification of mutations and other abnormalities in Phred/Phrap genome assemblies.'),
(71369, 2004, 'bio', 'TargetDB: a target registration database for structural genomics projects', 'Chen, Li|Oughtred, Rose|Berman, Helen M|Westbrook, John', 'Research Collaboratory for Structural Bioinformatics, Protein Data Bank, Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, NJ 08854, USA.|Research Collaboratory for Structural Bioinformatics, Protein Data Bank, Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, NJ 08854, USA.|Research Collaboratory for Structural Bioinformatics, Protein Data Bank, Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, NJ 08854, USA.|Research Collaboratory for Structural Bioinformatics, Protein Data Bank, Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway, NJ 08854, USA.', 'Jersey|Jersey|Jersey|Jersey', 140, 'Amino Acid Sequence|Database Management Systems|Databases, Protein|Genomics|Information Storage and Retrieval|Molecular Sequence Data|Proteins|Research|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth300', '15130928', 'TargetDB is a centralized target registration database that includes protein target data from the NIH structural genomics centers and a number of international sites. TargetDB, which is hosted by the Protein Data Bank (RCSB PDB), provides status information on target sequences and tracks their progress through the various stages of protein production and structure determination. A simple search form permits queries based on contributing site, target ID, protein name, sequence, status and other data. The progress of individual targets or entire structural genomics projects may be tracked over time, and target data from all contributing centers may also be downloaded in the XML format.'),
(71370, 2004, 'bio', 'A collaborative database of inbred mouse strain characteristics', 'Grubb, Stephen C|Churchill, Gary A|Bogue, Molly A', 'The Jackson Laboratory, Bar Harbor, ME 04609, USA. phenome@jax.org|The Jackson Laboratory, Bar Harbor, ME 04609, USA. phenome@jax.org|The Jackson Laboratory, Bar Harbor, ME 04609, USA. phenome@jax.org', 'United States|United States|United States', 74, 'Animals|Database Management Systems|Databases, Genetic|Female|Genome|Information Dissemination|Information Storage and Retrieval|Male|Mice|Mice, Inbred Strains|Phenotype|Proteome|Species Specificity', 'Journal Article', '10.1093/bioinformatics/bth299', '15130929', 'A database and website (MPD: Mouse Phenome Database) have been developed to serve as a consolidated home for mouse strain characterization data being generated by the scientific community. Physiological, anatomical and behavioral data are being collected and integrated into a common framework for tabulation by strain and sex. Genotypic data are being collected as well. The current focus is on a set of 40 inbred strains. The MPD as of February 2004 contains approximately 500 phenotypic parameters relevant to human health, voluntarily contributed by several dozen investigators and laboratories.'),
(71371, 2004, 'bio', 'Eigenvalue analysis of amino acid substitution matrices reveals a sharp transition of the mode of sequence conservation in proteins', 'Kinjo, Akira R|Nishikawa, Ken', 'Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Mishima, 411-8540, Japan. akinjo@genes.nig.ac.jp|Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Mishima, 411-8540, Japan. akinjo@genes.nig.ac.jp', 'Japan|Japan', 25, 'Algorithms|Amino Acid Substitution|Amino Acids|Conserved Sequence|Hydrophobic and Hydrophilic Interactions|Mutation|Numerical Analysis, Computer-Assisted|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bth297', '15130930', 'The pattern of amino acid substitutions and sequence conservation over many structure-based alignments of protein sequences was analyzed as a function of percentage sequence identity. The statistics of the amino acid substitutions were converted into the form of log-odds amino acid substitution matrices to which eigenvalue decomposition was applied. It was found that the most important component of the substitution matrices exhibited a sharp transition at the sequence identity of 30-35%, which coincides with the twilight zone. Above the transition point, the most dominant component is related to the mutability of amino acids and it acts to disfavor any substitutions, whereas below the transition point, the most dominant component is related to the hydrophobicity of amino acids and substitutions between residues of similar hydrophobic character are positively favored. Implications for protein evolution and sequence analysis are discussed.'),
(71372, 2004, 'bio', 'ASIAN: a website for network inference', 'Aburatani, Sachiyo|Goto, Kousuke|Saito, Shigeru|Fumoto, Masaki|Imaizumi, Akira|Sugaya, Nobuyoshi|Murakami, Hiroo|Sato, Makihiko|Toh, Hiroyuki|Horimoto, Katsuhisa', 'Laboratory of Biostatistics, Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.|Laboratory of Biostatistics, Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.|Laboratory of Biostatistics, Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.|Laboratory of Biostatistics, Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.|Laboratory of Biostatistics, Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.|Laboratory of Biostatistics, Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.|Laboratory of Biostatistics, Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.|Laboratory of Biostatistics, Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.|Laboratory of Biostatistics, Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.|Laboratory of Biostatistics, Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 13, 'Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Internet|Models, Biological|Models, Statistical|Proteome|Signal Transduction|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth296', '15130931', 'We constructed a website for inferring a network by applying the graphical Gaussian model, from a large amount of data, including redundant information. The available tools on the website are based on a system, named ASIAN (Automatic System for Inferring A Network), in combination with the two methods in our previous papers, which were designed to analyze gene expression profiles on a genomic scale. One of the remarkable features of the website is its ability to infer a network, concomitant with hierarchical clustering and the following estimation of cluster boundaries.'),
(71373, 2004, 'bio', 'THEA: ontology-driven analysis of microarray data', 'Pasquier, C|Girardot, F|Jevardat de Fombelle, K|Christen, R', 'Institute of Signaling, Developmental Biology and Cancer Research, Laboratory of Virtual Biology, CNRS UMR 6543 Parc Valnore, Nice 06108, Cedex 02, France. claude.pasquier@unice.fr|Institute of Signaling, Developmental Biology and Cancer Research, Laboratory of Virtual Biology, CNRS UMR 6543 Parc Valnore, Nice 06108, Cedex 02, France. claude.pasquier@unice.fr|Institute of Signaling, Developmental Biology and Cancer Research, Laboratory of Virtual Biology, CNRS UMR 6543 Parc Valnore, Nice 06108, Cedex 02, France. claude.pasquier@unice.fr|Institute of Signaling, Developmental Biology and Cancer Research, Laboratory of Virtual Biology, CNRS UMR 6543 Parc Valnore, Nice 06108, Cedex 02, France. claude.pasquier@unice.fr', 'France|France|France|France', 21, 'Abstracting and Indexing as Topic|Database Management Systems|Databases, Protein|Documentation|Drosophila Proteins|Gene Expression Profiling|Information Storage and Retrieval|Natural Language Processing|Oligonucleotide Array Sequence Analysis|Sequence Analysis, Protein|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth295', '15130932', 'Microarray technology makes it possible to measure thousands of variables and to compare their values under hundreds of conditions. Once microarray data are quantified, normalized and classified, the analysis phase is essentially a manual and subjective task based on visual inspection of classes in the light of the vast amount of information available. Currently, data interpretation clearly constitutes the bottleneck of such analyses and there is an obvious need for tools able to fill the gap between data processed with mathematical methods and existing biological knowledge.'),
(71374, 2004, 'bio', 'A statistical framework for genomic data fusion', 'Lanckriet, Gert R G|De Bie, Tijl|Cristianini, Nello|Jordan, Michael I|Noble, William Stafford', 'Department of Electrical Engineering and Computer Science, University of California, Berkeley 94720, USA.|Department of Electrical Engineering and Computer Science, University of California, Berkeley 94720, USA.|Department of Electrical Engineering and Computer Science, University of California, Berkeley 94720, USA.|Department of Electrical Engineering and Computer Science, University of California, Berkeley 94720, USA.|Department of Electrical Engineering and Computer Science, University of California, Berkeley 94720, USA.', 'United States|United States|United States|United States|United States', 468, 'Algorithms|Artificial Intelligence|Chromosome Mapping|Databases, Genetic|Databases, Protein|Fungal Proteins|Gene Expression Profiling|Genomics|Information Storage and Retrieval|Membrane Proteins|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Proteins|Ribosomal Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Systems Integration', 'Comparative Study', '10.1093/bioinformatics/bth294', '15130933', 'During the past decade, the new focus on genomics has highlighted a particular challenge: to integrate the different views of the genome that are provided by various types of experimental data.'),
(71375, 2004, 'bio', 'GO-Mapper: functional analysis of gene expression data using the expression level as a score to evaluate Gene Ontology terms', 'Smid, Marcel|Dorssers, Lambert C J', 'Department of Pathology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000DR Rotterdam, The Netherlands.|Department of Pathology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000DR Rotterdam, The Netherlands.', 'Netherlands|Netherlands', 37, 'Algorithms|Animals|Databases, Protein|Documentation|Gene Expression Profiling|Humans|Mice|Natural Language Processing|Oligonucleotide Array Sequence Analysis|Proteins|Software|Structure-Activity Relationship|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth293', '15130934', 'Retrieval of information on biological processes from large-scale expression data is still a time-consuming task. An automated analysis utilizing all expression information would greatly increase our understanding of the samples under study.'),
(71376, 2004, 'bio', 'A dynamically growing self-organizing tree (DGSOT) for hierarchical clustering gene expression profiles', 'Luo, Feng|Khan, Latifur|Bastani, Farokh|Yen, I-Ling|Zhou, Jizhong', 'Department of Computer Science, University of Texas at Dallas, Richardson, TX 75252, USA.|Department of Computer Science, University of Texas at Dallas, Richardson, TX 75252, USA.|Department of Computer Science, University of Texas at Dallas, Richardson, TX 75252, USA.|Department of Computer Science, University of Texas at Dallas, Richardson, TX 75252, USA.|Department of Computer Science, University of Texas at Dallas, Richardson, TX 75252, USA.', 'United States|United States|United States|United States|United States', 62, 'Algorithms|Artificial Intelligence|Cell Cycle Proteins|Cluster Analysis|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae Proteins', 'Comparative Study', '10.1093/bioinformatics/bth292', '15130935', 'The increasing use of microarray technologies is generating large amounts of data that must be processed in order to extract useful and rational fundamental patterns of gene expression. Hierarchical clustering technology is one method used to analyze gene expression data, but traditional hierarchical clustering algorithms suffer from several drawbacks (e.g. fixed topology structure, mis-clustered data which cannot be reevaluated). In this paper, we introduce a new hierarchical clustering algorithm that overcomes some of these drawbacks.'),
(71377, 2004, 'bio', 'Distribution of information in biomedical abstracts and full-text publications', 'Schuemie, M J|Weeber, M|Schijvenaars, B J A|van Mulligen, E M|van der Eijk, C C|Jelier, R|Mons, B|Kors, J A', 'Department of Medical Informatics, Erasmus University Medical Center Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands. m.schuemie@erasmusmc.nl|Department of Medical Informatics, Erasmus University Medical Center Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands. m.schuemie@erasmusmc.nl|Department of Medical Informatics, Erasmus University Medical Center Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands. m.schuemie@erasmusmc.nl|Department of Medical Informatics, Erasmus University Medical Center Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands. m.schuemie@erasmusmc.nl|Department of Medical Informatics, Erasmus University Medical Center Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands. m.schuemie@erasmusmc.nl|Department of Medical Informatics, Erasmus University Medical Center Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands. m.schuemie@erasmusmc.nl|Department of Medical Informatics, Erasmus University Medical Center Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands. m.schuemie@erasmusmc.nl|Department of Medical Informatics, Erasmus University Medical Center Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands. m.schuemie@erasmusmc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 69, 'Abstracting and Indexing as Topic|Bibliometrics|Biomedical Research|Genes|Information Dissemination|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Periodicals as Topic|Terminology as Topic', 'Comparative Study', '10.1093/bioinformatics/bth291', '15130936', 'Full-text documents potentially hold more information than their abstracts, but require more resources for processing. We investigated the added value of full text over abstracts in terms of information content and occurrences of gene symbol--gene name combinations that can resolve gene-symbol ambiguity.'),
(71378, 2004, 'bio', 'Incremental generation of summarized clustering hierarchy for protein family analysis', 'Chen, Chien-Yu|Oyang, Yen-Jen|Juan, Hsueh-Fen', 'Department of Computer Science and Information Engineering, National Taiwan University, Taipei 106, Taiwan, ROC. cychen@mars.csie.ntu.edu.tw|Department of Computer Science and Information Engineering, National Taiwan University, Taipei 106, Taiwan, ROC. cychen@mars.csie.ntu.edu.tw|Department of Computer Science and Information Engineering, National Taiwan University, Taipei 106, Taiwan, ROC. cychen@mars.csie.ntu.edu.tw', '-|-|-', 4, 'Algorithms|Animals|Cluster Analysis|Databases, Protein|Evolution, Molecular|Humans|Mice|Pattern Recognition, Automated|Proteins|Rats|Sequence Alignment|Sequence Analysis, Protein|Software|Species Specificity', 'Comparative Study', '10.1093/bioinformatics/bth290', '15130937', 'Protein sequence clustering has been widely exploited to facilitate in-depth analysis of protein functions and families. For some applications of protein sequence clustering, it is highly desirable that a hierarchical structure, also referred to as dendrogram, which shows how proteins are clustered at various levels, is generated. However, as the sizes of contemporary protein databases continue to grow at rapid rates, it is of great interest to develop some summarization mechanisms so that the users can browse the dendrogram and/or search for the desired information more effectively.'),
(71379, 2004, 'bio', 'Gene co-expression network topology provides a framework for molecular characterization of cellular state', 'Carter, Scott L|Brechbühler, Christian M|Griffin, Michael|Bond, Andrew T', 'Xpogen, Inc., 1340 Centre Street, Newton Centre, MA 02459, USA.|Xpogen, Inc., 1340 Centre Street, Newton Centre, MA 02459, USA.|Xpogen, Inc., 1340 Centre Street, Newton Centre, MA 02459, USA.|Xpogen, Inc., 1340 Centre Street, Newton Centre, MA 02459, USA.', 'United States|United States|United States|United States', 229, 'Algorithms|Cell Physiological Phenomena|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Biological|Oligonucleotide Array Sequence Analysis|Signal Transduction|Software', 'Comparative Study', '10.1093/bioinformatics/bth234', '15130938', 'Gene expression data have become an instrumental resource in describing the molecular state associated with various cellular phenotypes and responses to environmental perturbations. The utility of expression profiling has been demonstrated in partitioning clinical states, predicting the class of unknown samples and in assigning putative functional roles to previously uncharacterized genes based on profile similarity. However, gene expression profiling has had only limited success in identifying therapeutic targets. This is partly due to the fact that current methods based on fold-change focus only on single genes in isolation, and thus cannot convey causal information. In this paper, we present a technique for analysis of expression data in a graph-theoretic framework that relies on associations between genes. We describe the global organization of these networks and biological correlates of their structure. We go on to present a novel technique for the molecular characterization of disparate cellular states that adds a new dimension to the fold-based methods and conclude with an example application to a human medulloblastoma dataset.'),
(71380, 2004, 'bio', 'A neural network method for prediction of beta-turn types in proteins using evolutionary information', 'Kaur, Harpreet|Raghava, G P S', 'Institute of Microbial Technology, Sector-39A, Chandigarh, India.|Institute of Microbial Technology, Sector-39A, Chandigarh, India.', 'India|India', 90, 'Algorithms|Databases, Protein|Models, Chemical|Neural Networks (Computer)|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth322', '15145798', 'The prediction of beta-turns is an important element of protein secondary structure prediction. Recently, a highly accurate neural network based method Betatpred2 has been developed for predicting beta-turns in proteins using position-specific scoring matrices (PSSM) generated by PSI-BLAST and secondary structure information predicted by PSIPRED. However, the major limitation of Betatpred2 is that it predicts only beta-turn and non-beta-turn residues and does not provide any information of different beta-turn types. Thus, there is a need to predict beta-turn types using an approach based on multiple sequence alignment, which will be useful in overall tertiary structure prediction.'),
(71381, 2004, 'bio', 'GeneRecords: a relational database for GenBank flat file parsing and data manipulation in personal computers', 'DAddabbo, P|Lenzi, L|Facchin, F|Casadei, R|Canaider, S|Vitale, L|Frabetti, F|Carinci, P|Zannotti, M|Strippoli, P', 'Center for Research into Molecular Genetics Fondazione CARISBO, Institute of Histology and General Embriology, University of Bologna, Via Belmeloro, 8-40126 Bologna, Italy.|Center for Research into Molecular Genetics Fondazione CARISBO, Institute of Histology and General Embriology, University of Bologna, Via Belmeloro, 8-40126 Bologna, Italy.|Center for Research into Molecular Genetics Fondazione CARISBO, Institute of Histology and General Embriology, University of Bologna, Via Belmeloro, 8-40126 Bologna, Italy.|Center for Research into Molecular Genetics Fondazione CARISBO, Institute of Histology and General Embriology, University of Bologna, Via Belmeloro, 8-40126 Bologna, Italy.|Center for Research into Molecular Genetics Fondazione CARISBO, Institute of Histology and General Embriology, University of Bologna, Via Belmeloro, 8-40126 Bologna, Italy.|Center for Research into Molecular Genetics Fondazione CARISBO, Institute of Histology and General Embriology, University of Bologna, Via Belmeloro, 8-40126 Bologna, Italy.|Center for Research into Molecular Genetics Fondazione CARISBO, Institute of Histology and General Embriology, University of Bologna, Via Belmeloro, 8-40126 Bologna, Italy.|Center for Research into Molecular Genetics Fondazione CARISBO, Institute of Histology and General Embriology, University of Bologna, Via Belmeloro, 8-40126 Bologna, Italy.|Center for Research into Molecular Genetics Fondazione CARISBO, Institute of Histology and General Embriology, University of Bologna, Via Belmeloro, 8-40126 Bologna, Italy.|Center for Research into Molecular Genetics Fondazione CARISBO, Institute of Histology and General Embriology, University of Bologna, Via Belmeloro, 8-40126 Bologna, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 6, 'Database Management Systems|Databases, Genetic|Documentation|Information Storage and Retrieval|Microcomputers|Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth321', '15145799', 'Extracting the desired data from a database entry for later analysis is a constant need in the biological sequence analysis community, GeneRecords 1.0 is a solution for GenBank biological flat file parsing, as it implements a structured representation of each feature and feature qualifier in GenBank following import in a common database managing system usable in a personal computer (Macintosh and Windows environments). This collection of related databases enables the local management of GenBank records, allowing indexing, retrieval and analysis of both information and sequences on a personal computer.'),
(71382, 2004, 'bio', 'Prediction of similarly acting cis-regulatory modules by subsequence profiling and comparative genomics in Drosophila melanogaster and Dpseudoobscura', 'Grad, Yonatan H|Roth, Frederick P|Halfon, Marc S|Church, George M', 'The Lipper Center for Computational Genetics, Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, Massachusetts, 02115, USA.|The Lipper Center for Computational Genetics, Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, Massachusetts, 02115, USA.|The Lipper Center for Computational Genetics, Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, Massachusetts, 02115, USA.|The Lipper Center for Computational Genetics, Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, Massachusetts, 02115, USA.', 'United States|United States|United States|United States', 50, 'Algorithms|Animals|Chromosome Mapping|Consensus Sequence|DNA Footprinting|Drosophila|Gene Expression Profiling|Gene Expression Regulation, Developmental|Genes, Regulator|Phylogeny|Regulatory Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Species Specificity', 'Comparative Study', '10.1093/bioinformatics/bth320', '15145800', 'To date, computational searches for cis-regulatory modules (CRMs) have relied on two methods. The first, phylogenetic footprinting, has been used to find CRMs in non-coding sequence, but does not directly link DNA sequence with spatio-temporal patterns of expression. The second, based on searches for combinations of transcription factor (TF) binding motifs, has been employed in genome-wide discovery of similarly acting enhancers, but requires prior knowledge of the set of TFs acting at the CRM and the TFs binding motifs.'),
(71383, 2004, 'bio', 'The Global Error Assessment (GEA) model for the selection of differentially expressed genes in microarray data', 'Mansourian, Robert|Mutch, David M|Antille, Nicolas|Aubert, Jerome|Fogel, Paul|Le Goff, Jean-Marc|Moulin, Julie|Petrov, Anton|Rytz, Andreas|Voegel, Johannes J|Roberts, Matthew-Alan', 'Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland.|Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland.|Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland.|Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland.|Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland.|Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland.|Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland.|Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland.|Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland.|Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland.|Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 0, 'Algorithms|Analysis of Variance|Animals|Cell Line|Gene Expression Profiling|Gene Expression Regulation|Humans|Interferon-gamma|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Skin|Software|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/bth319', '15145801', 'Microarray technology has become a powerful research tool in many fields of study, however, the cost of microarrays often results in the use of a low number of replicates (k). Under circumstances where k is low, it becomes difficult to perform standard statistical tests to extract the most biologically significant experimental results. Other more advanced statistical tests have been developed, however, their use and interpretation often remain difficult to implement in routine biological research. The present work outlines a method that achieves sufficient statistical power for selecting differentially expressed genes under conditions of low k, while remaining as an intuitive and computationally efficient procedure.'),
(71384, 2004, 'bio', 'A Bayesian connectivity-based approach to constructing probabilistic gene regulatory networks', 'Zhou, Xiaobo|Wang, Xiaodong|Pal, Ranadip|Ivanov, Ivan|Bittner, Michael|Dougherty, Edward R', 'Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Bayes Theorem|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Melanoma|Models, Biological|Models, Statistical|Monte Carlo Method|Neural Networks (Computer)|Nonlinear Dynamics|Signal Transduction|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth318', '15145802', 'We have hypothesized that the construction of transcriptional regulatory networks using a method that optimizes connectivity would lead to regulation consistent with biological expectations. A key expectation is that the hypothetical networks should produce a few, very strong attractors, highly similar to the original observations, mimicking biological state stability and determinism. Another central expectation is that, since it is expected that the biological control is distributed and mutually reinforcing, interpretation of the observations should lead to a very small number of connection schemes.'),
(71385, 2004, 'bio', 'Transcription/replication collisions cause bacterial transcription units to be longer on the leading strand of replication', 'Omont, Nicolas|Képès, François', 'ATGC, CNRS UMR 8071/genopole, 523 Terrasses de lAgora, 91000 Evry, France.|ATGC, CNRS UMR 8071/genopole, 523 Terrasses de lAgora, 91000 Evry, France.', 'France|France', 0, 'Bacillus subtilis|Chromosome Mapping|Chromosomes, Bacterial|Computer Simulation|Escherichia coli|Models, Genetic|Models, Statistical|Replicon|Sequence Analysis, DNA|Transcription, Genetic', 'Comparative Study', '10.1093/bioinformatics/bth317', '15145803', 'The costs of head-on versus codirectional collisions between the replication complex and the much slower transcription complex on the circular bacterial chromosomes are much debated. Although it is established that the number of genes on the leading strand is higher than on the lagging strand of replication, the consequences of collisions on the length of transcription units are unknown.'),
(71386, 2004, 'bio', 'FigSearch: a figure legend indexing and classification system', 'Liu, Fang|Jenssen, Tor-Kristian|Nygaard, Vegard|Sack, John|Hovig, Eivind', 'Department of Tumor Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Montebello, 0310 Oslo, Norway.|Department of Tumor Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Montebello, 0310 Oslo, Norway.|Department of Tumor Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Montebello, 0310 Oslo, Norway.|Department of Tumor Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Montebello, 0310 Oslo, Norway.|Department of Tumor Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Montebello, 0310 Oslo, Norway.', 'Norway|Norway|Norway|Norway|Norway', 27, 'Abstracting and Indexing as Topic|Computer Graphics|Database Management Systems|Databases, Bibliographic|Information Storage and Retrieval|Internet|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Protein Interaction Mapping|Signal Transduction|Terminology as Topic|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bth316', '15145804', 'FigSearch is a prototype text-mining and classification system for figures from any corpus of full-text biological papers. The system allows users to search for figures that contain genes of interest and illustrate protein interactions. The retrieved figures are ranked by a score representing the likelihood to be of a certain type, in this case, schematic illustrations of protein interactions and signaling events. The system contains a Web interface for search, a module for classification of figures based on vector representations of figure legends and a module for indexing gene names. In a preliminary validation, the FigSearch system showed satisfactory performance according to domain experts in providing the most relevant graphical representations. This strategy may be easily extended to other figure types. Moreover, as more full-text data become available, such a system will find increased usefulness in identifying and presenting compressed biological knowledge.'),
(71387, 2004, 'bio', 'TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders', 'Majoros, W H|Pertea, M|Salzberg, S L', 'Bioinformatics Department, The Institute for Genomic Research, Rockville, MD 20850, USA. bmajoros@tigr.org|Bioinformatics Department, The Institute for Genomic Research, Rockville, MD 20850, USA. bmajoros@tigr.org|Bioinformatics Department, The Institute for Genomic Research, Rockville, MD 20850, USA. bmajoros@tigr.org', 'United States|United States|United States', 457, 'Algorithms|Animals|Aspergillus fumigatus|Eukaryotic Cells|Gene Expression Profiling|Markov Chains|Models, Genetic|Models, Statistical|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software|Toxoplasma', 'Comparative Study', '10.1093/bioinformatics/bth315', '15145805', 'We describe two new Generalized Hidden Markov Model implementations for ab initio eukaryotic gene prediction. The C/C++ source code for both is available as open source and is highly reusable due to their modular and extensible architectures. Unlike most of the currently available gene-finders, the programs are re-trainable by the end user. They are also re-configurable and include several types of probabilistic submodels which can be independently combined, such as Maximal Dependence Decomposition trees and interpolated Markov models. Both programs have been used at TIGR for the annotation of the Aspergillus fumigatus and Toxoplasma gondii genomes.'),
(71388, 2004, 'bio', 'Thermodynamics of enzyme-catalyzed reactions--a database for quantitative biochemistry', 'Goldberg, Robert N|Tewari, Yadu B|Bhat, Talapady N', 'Biotechnology Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA.|Biotechnology Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA.|Biotechnology Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA.', 'United States|United States|United States', 0, 'Biochemistry|Catalysis|Database Management Systems|Databases, Factual|Documentation|Enzyme Activation|Enzymes|Information Storage and Retrieval|Kinetics|Natural Language Processing|Quantitative Structure-Activity Relationship|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/bth314', '15145806', 'The Thermodynamics of Enzyme-catalyzed Reactions Database (TECRDB) is a comprehensive collection of thermodynamic data on enzyme-catalyzed reactions. The data, which consist of apparent equilibrium constants and calorimetrically determined molar enthalpies of reaction, are the primary experimental results obtained from thermodynamic studies of biochemical reactions. The results from approximately 1000 published papers containing data on approximately 400 different enzyme-catalyzed reactions constitute the essential information in the database. The information is managed using Oracle and is available on the Web.'),
(71389, 2004, 'bio', 'Rainbow: a toolbox for phylogenetic supertree construction and analysis', 'Chen, D|Eulenstein, O|Fernández-Baca, D', 'Department of Computer Science, Iowa State University, Ames, IA 50011, USA. duhong@iastate.edu|Department of Computer Science, Iowa State University, Ames, IA 50011, USA. duhong@iastate.edu|Department of Computer Science, Iowa State University, Ames, IA 50011, USA. duhong@iastate.edu', 'United States|United States|United States', 21, 'Algorithms|Cluster Analysis|Computer Graphics|DNA Mutational Analysis|Oligonucleotide Array Sequence Analysis|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth313', '15145807', 'Rainbow is a program that provides a graphic user interface to construct supertrees using different methods. It also provides tools to analyze the quality of the supertrees produced. Rainbow is available for Mac OS X, Windows and Linux.'),
(71390, 2004, 'bio', 'Mining gene expression data for positive and negative co-regulated gene clusters', 'Ji, Liping|Tan, Kian-Lee', 'Department Computer Science, National University of Singapore, 3 Science Drive 2, Singapore 117543, Singapore. jiliping@comp.nus.edu.sg|Department Computer Science, National University of Singapore, 3 Science Drive 2, Singapore 117543, Singapore. jiliping@comp.nus.edu.sg', 'Singapore|Singapore', 43, 'Algorithms|Cluster Analysis|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Software|Statistics as Topic|Yeasts', 'Comparative Study', '10.1093/bioinformatics/bth312', '15145808', 'Analysis of gene expression data can provide insights into the positive and negative co-regulation of genes. However, existing methods such as association rule mining are computationally expensive and the quality and quantities of the rules are sensitive to the support and confidence values. In this paper, we introduce the concept of positive and negative co-regulated gene cluster (PNCGC) that more accurately reflects the co-regulation of genes, and propose an efficient algorithm to extract PNCGCs.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71391, 2004, 'bio', 'Exhaustive whole-genome tandem repeats search', 'Krishnan, Arun|Tang, Francis', 'Bioinformatics Institute, 30 Biopolis Street, No. 07-01, Matrix, Singapore 138671, Singapore. arun@bii.a-star.edu.sg|Bioinformatics Institute, 30 Biopolis Street, No. 07-01, Matrix, Singapore 138671, Singapore. arun@bii.a-star.edu.sg', 'Singapore|Singapore', 35, 'Algorithms|Chromosome Mapping|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Tandem Repeat Sequences', 'Comparative Study', '10.1093/bioinformatics/bth311', '15145809', 'Approximate tandem repeats (ATR) occur frequently in the genomes of organisms, and are a source of polymorphisms observed in individuals, and thus are of interest to those studying genetic disorders. Though extensive work has been done in order to identify ATRs, there are inherent limitations with the current approaches in terms of the number of pattern sizes that can be searched or the size of the input length.'),
(71392, 2004, 'bio', 'A mixture model for estimating the local false discovery rate in DNA microarray analysis', 'Liao, J G|Lin, Yong|Selvanayagam, Zachariah E|Shih, Weichung Joe', 'Biometrics Division, School of Public Health and The Cancer Institute of New Jersey, University of Medicine and Dentistry of New Jersey, 683 Hoes Lane West, Piscataway, NJ 08854, USA. liaojg@umdnj.edu|Biometrics Division, School of Public Health and The Cancer Institute of New Jersey, University of Medicine and Dentistry of New Jersey, 683 Hoes Lane West, Piscataway, NJ 08854, USA. liaojg@umdnj.edu|Biometrics Division, School of Public Health and The Cancer Institute of New Jersey, University of Medicine and Dentistry of New Jersey, 683 Hoes Lane West, Piscataway, NJ 08854, USA. liaojg@umdnj.edu|Biometrics Division, School of Public Health and The Cancer Institute of New Jersey, University of Medicine and Dentistry of New Jersey, 683 Hoes Lane West, Piscataway, NJ 08854, USA. liaojg@umdnj.edu', 'Jersey|Jersey|Jersey|Jersey', 0, 'Algorithms|Artifacts|Computer Simulation|False Positive Reactions|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Testing|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Stochastic Processes|Uterine Cervical Neoplasms', 'Clinical Trial', '10.1093/bioinformatics/bth310', '15145810', 'Statistical methods based on controlling the false discovery rate (FDR) or positive false discovery rate (pFDR) are now well established in identifying differentially expressed genes in DNA microarray. Several authors have recently raised the important issue that FDR or pFDR may give misleading inference when specific genes are of interest because they average the genes under consideration with genes that show stronger evidence for differential expression. The paper proposes a flexible and robust mixture model for estimating the local FDR which quantifies how plausible each specific gene expresses differentially.'),
(71393, 2004, 'bio', 'Correcting log ratios for signal saturation in cDNA microarrays', 'Dodd, Lori E|Korn, Edward L|McShane, Lisa M|Chandramouli, G V R|Chuang, Eric Y', 'Biometric Research Branch, DCTD, National Cancer Institute, Bethesda, MD 20892-7434, USA. doddl@mail.nih.gov|Biometric Research Branch, DCTD, National Cancer Institute, Bethesda, MD 20892-7434, USA. doddl@mail.nih.gov|Biometric Research Branch, DCTD, National Cancer Institute, Bethesda, MD 20892-7434, USA. doddl@mail.nih.gov|Biometric Research Branch, DCTD, National Cancer Institute, Bethesda, MD 20892-7434, USA. doddl@mail.nih.gov|Biometric Research Branch, DCTD, National Cancer Institute, Bethesda, MD 20892-7434, USA. doddl@mail.nih.gov', 'United States|United States|United States|United States|United States', 24, 'Algorithms|Artifacts|Cell Line, Tumor|Gene Expression Profiling|Humans|Image Enhancement|Male|Microscopy, Fluorescence|Oligonucleotide Array Sequence Analysis|Prostatic Neoplasms|Signal Processing, Computer-Assisted|Spectrometry, Fluorescence|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/bth309', '15145811', 'Pixel saturation occurs when the pixel intensity exceeds a threshold and the recorded pixel intensity is truncated. Microarray experiments are commonly afflicted with saturated pixels. As a result, estimators of gene expression are biased, with the amount of bias increasing as a function of the proportion of pixels saturated. Saturation is directly related to the photomultiplier tube (PMT) voltage settings and RNA abundance and is not necessarily associated with poor array or poor spot quality. When choosing PMT settings, higher PMT settings are desired because of improved signal-to-noise ratios of low-intensity spots. This improved signal is somewhat offset by saturation of high-intensity spots. In practice, spots with saturated pixels are discarded or the biased value is used. Neither of these approaches is appealing, particularly the former approach when a highly expressed gene is discarded because of saturation.'),
(71394, 2004, 'bio', 'An efficient algorithm for optimizing whole genome alignment with noise', 'Wong, Prudence W H|Lam, T W|Lu, N|Ting, H F|Yiu, S M', 'Department of Computer Science, University of Hong Kong, Hong Kong. whwong@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong. whwong@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong. whwong@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong. whwong@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong. whwong@cs.hku.hk', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong', 2, 'Algorithms|Chromosome Mapping|Cluster Analysis|Conserved Sequence|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Sequence Homology, Nucleic Acid|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/bth308', '15145812', 'This paper is concerned with algorithms for aligning two whole genomes so as to identify regions that possibly contain conserved genes. Motivated by existing heuristic-based software tools, we initiate the study of an optimization problem that attempts to uncover conserved genes with a global concern. Another interesting feature in our formulation is the tolerance of noise, which also complicates the optimization problem. A brute-force approach takes time exponential in the noise level.'),
(71395, 2004, 'bio', 'ClutrFree: cluster tree visualization and interpretation', 'Bidaut, Ghislain|Ochs, Michael F', 'Division of Population Science, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, PA 19111, USA.|Division of Population Science, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, PA 19111, USA.', 'United States|United States', 16, 'Algorithms|Cluster Analysis|Computer Graphics|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth307', '15145813', 'ClutrFree facilitates the visualization and interpretation of clusters or patterns computed from microarray data through a graphical user interface that displays patterns, membership information of the genes and annotation statistics simultaneously. ClutrFree creates a tree linking the patterns based on similarity, permitting the navigation among patterns identified by different algorithms or by the same algorithm with different parameters, and aids the inferring of conclusions from a microarray experiment.'),
(71396, 2004, 'bio', 'Prokaryotic diversity of the Saccharomyces cerevisiae Atx1p-mediated copper pathway', 'van Bakel, Harm|Huynen, Martijn|Wijmenga, Cisca', 'Complex Genetics Group, Department of Biomedical Genetics, Stratenum 2.117, University Medical Center Utrecht, PO Box 80030, 3508 TA Utrecht, The Netherlands.|Complex Genetics Group, Department of Biomedical Genetics, Stratenum 2.117, University Medical Center Utrecht, PO Box 80030, 3508 TA Utrecht, The Netherlands.|Complex Genetics Group, Department of Biomedical Genetics, Stratenum 2.117, University Medical Center Utrecht, PO Box 80030, 3508 TA Utrecht, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 11, 'Algorithms|Carrier Proteins|Copper|Evolution, Molecular|Gene Expression Profiling|Gene Expression Regulation, Fungal|Genetic Variation|Internet|Operon|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Analysis, Protein|Signal Transduction|Software|Structure-Activity Relationship|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth298', '15145814', 'Several genes involved in the cellular import of copper and its subsequent incorporation into the high-affinity iron transport complex in Saccharomyces cerevisiae are known to be conserved between eukaryotes and prokaryotes. However, the degree to which these genes share their functional context as members of the same pathway in the prokaryotic domain is less clear.'),
(71397, 2004, 'bio', 'Dblox: a genome-wide test for ancient segmental duplication', 'Friedman, Robert|Ekollu, Vikram|Rose, John R|Hughes, Austin L', 'Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA.|Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA.|Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA.|Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|Evolution, Molecular|Gene Duplication|Gene Expression Profiling|Genes|Genes, Duplicate|Models, Genetic|Models, Statistical|Proteins|Sequence Alignment|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth275', '15145815', 'Dblox and RDblox provide a simple statistical test for duplicated genomic structure, the same programs can also be used to identify putatively duplicated regions. The method focuses on ancient duplication events involving protein-coding genes.'),
(71398, 2004, 'bio', 'Algorithms for sequence analysis via mutagenesis', 'Keith, Jonathan M|Adams, Peter|Bryant, Darryn|Cochran, Duncan A E|Lala, Gita H|Mitchelson, Keith R', 'Department of Mathematics, University of Queensland, St. Lucia, Australia. j.keith1@mailbox.uq.edu.au|Department of Mathematics, University of Queensland, St. Lucia, Australia. j.keith1@mailbox.uq.edu.au|Department of Mathematics, University of Queensland, St. Lucia, Australia. j.keith1@mailbox.uq.edu.au|Department of Mathematics, University of Queensland, St. Lucia, Australia. j.keith1@mailbox.uq.edu.au|Department of Mathematics, University of Queensland, St. Lucia, Australia. j.keith1@mailbox.uq.edu.au|Department of Mathematics, University of Queensland, St. Lucia, Australia. j.keith1@mailbox.uq.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia', 7, 'Algorithms|Animals|Computer Simulation|DNA Mutational Analysis|Dictyostelium|Models, Genetic|Models, Statistical|Mutagenesis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth258', '15145816', 'Despite many successes of conventional DNA sequencing methods, some DNAs remain difficult or impossible to sequence. Unsequenceable regions occur in the genomes of many biologically important organisms, including the human genome. Such regions range in length from tens to millions of bases, and may contain valuable information such as the sequences of important genes. The authors have recently developed a technique that renders a wide range of problematic DNAs amenable to sequencing. The technique is known as sequence analysis via mutagenesis (SAM). This paper presents a number of algorithms for analysing and interpreting data generated by this technique.'),
(71399, 2004, 'bio', 'Pathway Miner: extracting gene association networks from molecular pathways for predicting the biological significance of gene expression microarray data', 'Pandey, Ritu|Guru, Raghavendra K|Mount, David W', 'Bioinformatics Core, Arizona Cancer Center, University of Arizona, Tucson, AZ 85724, USA.|Bioinformatics Core, Arizona Cancer Center, University of Arizona, Tucson, AZ 85724, USA.|Bioinformatics Core, Arizona Cancer Center, University of Arizona, Tucson, AZ 85724, USA.', 'United States|United States|United States', 87, 'Algorithms|Computer Graphics|Computer Simulation|Gene Expression Regulation|Internet|Models, Biological|Oligonucleotide Array Sequence Analysis|Online Systems|Protein Interaction Mapping|Signal Transduction|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth215', '15145817', 'We have developed a web-based system (Pathway Miner) for visualizing gene expression profiles in the context of biological pathways. Pathway Miner catalogs genes based on their role in metabolic, cellular and regulatory pathways. A Fisher exact test is provided as an option to rank pathways. The genes are mapped onto pathways and gene product association networks are extracted for genes that co-occur in pathways. The networks can be filtered for analysis based on user-selected options.'),
(71400, 2004, 'bio', 'An object model and database for functional genomics', 'Jones, Andrew|Hunt, Ela|Wastling, Jonathan M|Pizarro, Angel|Stoeckert, Christian J', 'Department of Computing Science, University of Glasgow, Glasgow, UK. jonesa@dcs.gla.ac.uk|Department of Computing Science, University of Glasgow, Glasgow, UK. jonesa@dcs.gla.ac.uk|Department of Computing Science, University of Glasgow, Glasgow, UK. jonesa@dcs.gla.ac.uk|Department of Computing Science, University of Glasgow, Glasgow, UK. jonesa@dcs.gla.ac.uk|Department of Computing Science, University of Glasgow, Glasgow, UK. jonesa@dcs.gla.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 34, 'Abstracting and Indexing as Topic|Base Sequence|Database Management Systems|Databases, Protein|Documentation|Gene Expression Profiling|Gene Expression Regulation|Genomics|Information Storage and Retrieval|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Proteins|Proteomics|Software Design', 'Journal Article', '10.1093/bioinformatics/bth130', '15145818', 'Large-scale functional genomics analysis is now feasible and presents significant challenges in data analysis, storage and querying. Data standards are required to enable the development of public data repositories and to improve data sharing. There is an established data format for microarrays (microarray gene expression markup language, MAGE-ML) and a draft standard for proteomics (PEDRo). We believe that all types of functional genomics experiments should be annotated in a consistent manner, and we hope to open up new ways of comparing multiple datasets used in functional genomics.'),
(71401, 2004, 'bio', 'Correcting the loss of cell-cycle synchrony in clustering analysis of microarray data using weights', 'Duan, Fenghai|Zhang, Heping', 'Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520-8034, USA.|Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520-8034, USA.', 'United States|United States', 6, 'Algorithms|Biological Clocks|Cell Cycle|Cluster Analysis|Gene Expression Profiling|Gene Expression Regulation, Fungal|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sensitivity and Specificity|Time Factors', 'Comparative Study', '10.1093/bioinformatics/bth169', '15166015', 'Due to the existence of the loss of synchrony in cell-cycle data sets, standard clustering methods (e.g. k-means), which group open reading frames (ORFs) based on similar expression levels, are deficient unless the temporal pattern of the expression levels of the ORFs is taken into account.'),
(71402, 2004, 'bio', 'DBRF-MEGN method: an algorithm for deducing minimum equivalent gene networks from large-scale gene expression profiles of gene deletion mutants', 'Kyoda, Koji|Baba, Kotaro|Onami, Shuichi|Kitano, Hiroaki', 'Kitano Symbiotic Systems Project, ERATO, Japan Science and Technology Corporation, Shibuya, Tokyo 150-0001, Japan.|Kitano Symbiotic Systems Project, ERATO, Japan Science and Technology Corporation, Shibuya, Tokyo 150-0001, Japan.|Kitano Symbiotic Systems Project, ERATO, Japan Science and Technology Corporation, Shibuya, Tokyo 150-0001, Japan.|Kitano Symbiotic Systems Project, ERATO, Japan Science and Technology Corporation, Shibuya, Tokyo 150-0001, Japan.', 'Japan|Japan|Japan|Japan', 0, 'Algorithms|Gene Deletion|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Mutagenesis, Site-Directed|Saccharomyces cerevisiae Proteins|Signal Transduction|Software', 'Comparative Study', '10.1093/bioinformatics/bth306', '15166016', 'Large-scale gene expression profiles measured in gene deletion mutants are invaluable sources for identifying gene regulatory networks. Signed directed graph (SDG) is the most common representation of gene networks in genetics and cell biology. However, no practical procedure that deduces SDGs consistent with such profiles has been developed.'),
(71403, 2004, 'bio', 'Mining gene expression data based on template theory', 'Yang, Zheng Rong', 'School of Engineering and Computer Science, Exeter University, Exeter EX4 4QF, UK. Z.R.Yang@exeter.ac.uk', 'United Kingdom', 2, 'Algorithms|Artificial Intelligence|Cluster Analysis|Gene Expression Profiling|Information Storage and Retrieval|Models, Genetic|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth323', '15166017', 'It is understood that clustering genes are useful for exploring scientific knowledge from DNA microarray gene expression data. The explored knowledge can be finally used for annotating biological function for novel genes. Representing the explored knowledge in an efficient manner is then closely related to the classification accuracy. However, this issue has not yet been paid the attention it deserves.'),
(71404, 2005, 'bio', 'Whole-genome prokaryotic phylogeny', 'Henz, Stefan R|Huson, Daniel H|Auch, Alexander F|Nieselt-Struwe, Kay|Schuster, Stephan C', 'Center for Bioinformatics Tübingen (ZBIT), Sand 14, Tübingen 72076, Germany.|Center for Bioinformatics Tübingen (ZBIT), Sand 14, Tübingen 72076, Germany.|Center for Bioinformatics Tübingen (ZBIT), Sand 14, Tübingen 72076, Germany.|Center for Bioinformatics Tübingen (ZBIT), Sand 14, Tübingen 72076, Germany.|Center for Bioinformatics Tübingen (ZBIT), Sand 14, Tübingen 72076, Germany.', 'Germany|Germany|Germany|Germany|Germany', 138, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|DNA, Bacterial|Databases, Genetic|Evolution, Molecular|Genetic Variation|Genome, Bacterial|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/bth324', '15166018', 'Current understanding of the phylogeny of prokaryotes is based on the comparison of the highly conserved small ssu-rRNA subunit and similar regions. Although such molecules have proved to be very useful phylogenetic markers, mutational saturation is a problem, due to their restricted lengths. Now, a growing number of complete prokaryotic genomes are available. This paper addresses the problem of determining a prokaryotic phylogeny utilizing the comparison of complete genomes. We introduce a new strategy, GBDP, genome blast distance phylogeny, and show that different variants of this approach robustly produce phylogenies that are biologically sound, when applied to 91 prokaryotic genomes. In this approach, first Blast is used to compare genomes, then a distance matrix is computed, and finally a tree- or network-reconstruction method such as UPGMA, Neighbor-Joining, BioNJ or Neighbor-Net is applied.'),
(71405, 2004, 'bio', 'CoPS: Comprehensive Peptide Signature database', 'Prakash, Tulika|Khandelwal, Mamta|Dasgupta, Dipayan|Dash, Debasis|Brahmachari, Samir K', 'G.N.R. Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology, (Formerly Centre for Biochemical Technology), CSIR, Delhi University Campus, Mall Road, Delhi 110 007, India.|G.N.R. Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology, (Formerly Centre for Biochemical Technology), CSIR, Delhi University Campus, Mall Road, Delhi 110 007, India.|G.N.R. Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology, (Formerly Centre for Biochemical Technology), CSIR, Delhi University Campus, Mall Road, Delhi 110 007, India.|G.N.R. Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology, (Formerly Centre for Biochemical Technology), CSIR, Delhi University Campus, Mall Road, Delhi 110 007, India.|G.N.R. Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology, (Formerly Centre for Biochemical Technology), CSIR, Delhi University Campus, Mall Road, Delhi 110 007, India.', 'India|India|India|India|India', 9, 'Bacterial Proteins|Chromosome Mapping|Database Management Systems|Databases, Protein|Humans|Information Storage and Retrieval|Peptides|Sequence Analysis, Protein|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bth325', '15166019', 'We present the development of a Comprehensive database of 12 076 invariant Peptide Signatures (CoPS) derived from 52 bacterial genomes with a minimum occurrence in at least seven organisms. These peptides were observed in functionally similar proteins and are distributed over nearly 1250 different functional proteins. The database provides function, structure and occurrence in biochemical pathways of the proteins containing these signature peptides. It houses additional information on the signature peptides, such as identical match in other motif/pattern (e.g. PROSITE, BLOCKS, PRINTS and Pfam) databases and the database of interacting proteins, human proteome and mutation effect on these signature peptides. There is a wide applicability of this database in the identification of critical functional residues in proteins. The database also facilitates the identification of folding nucleus/structural determinants in proteins and functional assignment to yet unknown proteins. We demonstrate functional assignment to 2605 hypothetical proteins in bacterial genomes and 112 unknown proteins in human using this database.'),
(71406, 2004, 'bio', 'ICBS: a database of interactions between protein chains mediated by beta-sheet formation', 'Dou, Yimeng|Baisnée, Pierre-François|Pollastri, Gianluca|Pécout, Yann|Nowick, James|Baldi, Pierre', 'School of Information and Computer Science, University of California, Irvine, CA 92697, USA.|School of Information and Computer Science, University of California, Irvine, CA 92697, USA.|School of Information and Computer Science, University of California, Irvine, CA 92697, USA.|School of Information and Computer Science, University of California, Irvine, CA 92697, USA.|School of Information and Computer Science, University of California, Irvine, CA 92697, USA.|School of Information and Computer Science, University of California, Irvine, CA 92697, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Binding Sites|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Models, Chemical|Protein Binding|Protein Interaction Mapping|Protein Structure, Secondary|Proteins|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth326', '15166020', 'Interchain beta-sheet (ICBS) interactions occur widely in protein quaternary structures, interactions between proteins and protein aggregation. These interactions play a central role in many biological processes and in diseases ranging from AIDS and cancer to anthrax and Alzheimers.'),
(71407, 2004, 'bio', 'Faster cyclic loess: normalizing RNA arrays via linear models', 'Ballman, Karla V|Grill, Diane E|Oberg, Ann L|Therneau, Terry M', 'Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, MN 55905, USA. ballman@mayo.edu|Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, MN 55905, USA. ballman@mayo.edu|Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, MN 55905, USA. ballman@mayo.edu|Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, MN 55905, USA. ballman@mayo.edu', 'United States|United States|United States|United States', 124, 'Algorithms|Artifacts|Gene Expression Profiling|Genetic Variation|Linear Models|Models, Genetic|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis|RNA|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, RNA', 'Comparative Study', '10.1093/bioinformatics/bth327', '15166021', 'Our goal was to develop a normalization technique that yields results similar to cyclic loess normalization and with speed comparable to quantile normalization.'),
(71408, 2004, 'bio', 'Command line tool for calculating theoretical MS spectra for given sequences', 'Boehm, Andreas M|Grosse-Coosmann, Florian|Sickmann, Albert', 'Protein Mass Spectrometry and Functional Proteomics Group, Rudolf-Virchow-Center for Experimental Biomedicine, Universitaet Wuerzburg, Versbacher Strasse 9, D-97078 Wuerzburg, Germany.|Protein Mass Spectrometry and Functional Proteomics Group, Rudolf-Virchow-Center for Experimental Biomedicine, Universitaet Wuerzburg, Versbacher Strasse 9, D-97078 Wuerzburg, Germany.|Protein Mass Spectrometry and Functional Proteomics Group, Rudolf-Virchow-Center for Experimental Biomedicine, Universitaet Wuerzburg, Versbacher Strasse 9, D-97078 Wuerzburg, Germany.', 'Germany|Germany|Germany', 0, 'Algorithms|Computer Simulation|Mass Spectrometry|Models, Chemical|Online Systems|Proteins|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth328', '15166022', 'Scientists usually want to verify the ion matching process of algorithms that look up peptide sequences in DNA or protein databases. The verification step is often done numerically or visually. Not all search algorithms present the appropriate theoretical spectrum information within their results. Thus, the theoretical spectrum for each result should be calculated from the sequence of the matched peptide. We present an operating-system-independent command line tool for this purpose that can be integrated easily into complex as well as existing environments, and can be used to present the theoretical spectrum to the user in either graphical or tabular format by third party products.'),
(71409, 2004, 'bio', 'BacTregulators: a database of transcriptional regulators in bacteria and archaea', 'Martínez-Bueno, Manuel|Molina-Henares, Antonio J|Pareja, Eduardo|Ramos, Juan L|Tobes, Raquel', 'Department of Plant Biochemistry and Molecular and Cellular Biology, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas, E-18008 Granada, Spain.|Department of Plant Biochemistry and Molecular and Cellular Biology, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas, E-18008 Granada, Spain.|Department of Plant Biochemistry and Molecular and Cellular Biology, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas, E-18008 Granada, Spain.|Department of Plant Biochemistry and Molecular and Cellular Biology, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas, E-18008 Granada, Spain.|Department of Plant Biochemistry and Molecular and Cellular Biology, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas, E-18008 Granada, Spain.', 'Spain|Spain|Spain|Spain|Spain', 28, 'Archaea|Archaeal Proteins|Bacteria|Bacterial Proteins|Database Management Systems|Databases, Genetic|Documentation|Gene Expression Regulation, Archaeal|Gene Expression Regulation, Bacterial|Information Storage and Retrieval|Internet|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bth330', '15166024', 'The BacTregulators database is intended to collect and to integrate information on proteins belonging to defined families of transcriptional regulators in prokaryotes.'),
(71410, 2004, 'bio', 'Qxpak: a versatile mixed model application for genetical genomics and QTL analyses', 'Pérez-Enciso, M|Misztal, I', 'Institut Catalá de Reçerca i Estudis Avançats, Pg Lluis Companys 23, 08010 Barcelona, Spain. miguel.perez@uab.es|Institut Catalá de Reçerca i Estudis Avançats, Pg Lluis Companys 23, 08010 Barcelona, Spain. miguel.perez@uab.es', 'Spain|Spain', 111, 'Algorithms|Chromosome Mapping|Models, Genetic|Models, Statistical|Polymorphism, Genetic|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth331', '15166025', 'Current methodology and software for quantitative trait loci (QTL) analyses do not use all available information and are inadequate to deal with the huge amount of QTL analyses to be needed in forecoming genetical genomics studies.'),
(71411, 2004, 'bio', 'Data mining techniques to study the disulfide-bonding state in proteins: signal peptide is a strong descriptor', 'Tessier, Dominique|Bardiaux, Benjamin|Larré, Colette|Popineau, Yves', 'Unité de Recherche sur les Protéines Végétales et leurs Interactions, INRA Rue de la Géraudière, BP 71627, 44316 Nantes Cedex 3, France. tessier@nantes.inra.fr|Unité de Recherche sur les Protéines Végétales et leurs Interactions, INRA Rue de la Géraudière, BP 71627, 44316 Nantes Cedex 3, France. tessier@nantes.inra.fr|Unité de Recherche sur les Protéines Végétales et leurs Interactions, INRA Rue de la Géraudière, BP 71627, 44316 Nantes Cedex 3, France. tessier@nantes.inra.fr|Unité de Recherche sur les Protéines Végétales et leurs Interactions, INRA Rue de la Géraudière, BP 71627, 44316 Nantes Cedex 3, France. tessier@nantes.inra.fr', 'France|France|France|France', 5, 'Binding Sites|Database Management Systems|Databases, Protein|Disulfides|Documentation|Endoplasmic Reticulum|Information Storage and Retrieval|Natural Language Processing|Protein Binding|Protein Sorting Signals|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bth332', '15166026', 'In the eucaryotic cell, the formation of disulfide bonds takes place in general inside the endoplasmic reticulum which provides a unique folding environment. The DisulfideDB database gathers information about this biological process with structural, evolutionary and neighborhood information on cysteines in proteins. Mining this information with an association rule discovery program permits to extract some strong rules for the prediction of the disulfide-bonding state of cysteines.'),
(71412, 2004, 'bio', 'Regulatory motif finding by logic regression', 'Keles, Sündüz|van der Laan, Mark J|Vulpe, Chris', 'Division of Biostatistics, University of California, Berkeley, CA 94720, USA. sunduz@stat.berkeley.edu|Division of Biostatistics, University of California, Berkeley, CA 94720, USA. sunduz@stat.berkeley.edu|Division of Biostatistics, University of California, Berkeley, CA 94720, USA. sunduz@stat.berkeley.edu', 'United States|United States|United States', 46, 'Algorithms|Amino Acid Motifs|Binding Sites|Cell Cycle Proteins|Conserved Sequence|Logistic Models|Models, Chemical|Protein Binding|Proteins|Regression Analysis|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/bth333', '15166027', 'Multiple transcription factors coordinately control transcriptional regulation of genes in eukaryotes. Although many computational methods consider the identification of individual transcription factor binding sites (TFBSs), very few focus on the interactions between these sites. We consider finding TFBSs and their context specific interactions using microarray gene expression data. We devise a hybrid approach called LogicMotif composed of a TFBS identification method combined with the new regression methodology logic regression. LogicMotif has two steps: First, potential binding sites are identified from transcription control regions of genes of interest. Various available methods can be used in this step when the genes of interest can be divided into groups such as up-and downregulated. For this step, we also develop a simple univariate regression and extension method MFURE to extract candidate TFBSs from a large number of genes in the availability of microarray gene expression data. MFURE provides an alternative method for this step when partitioning of the genes into disjoint groups is not preferred. This first step aims to identify individual sites within gene groups of interest or sites that are correlated with the gene expression outcome. In the second step, logic regression is used to build a predictive model of outcome of interest (either gene expression or up- and down-regulation) using these potential sites. This 2-fold approach creates a rich diverse set of potential binding sites in the first step and builds regression or classification models in the second step using logic regression that is particularly good at identifying complex interactions.'),
(71413, 2004, 'bio', 'Automatic annotation of organellar genomes with DOGMA', 'Wyman, Stacia K|Jansen, Robert K|Boore, Jeffrey L', 'Department of Computer Sciences, Institute of Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712, USA. stacia@cs.utexas.edu|Department of Computer Sciences, Institute of Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712, USA. stacia@cs.utexas.edu|Department of Computer Sciences, Institute of Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712, USA. stacia@cs.utexas.edu', 'United States|United States|United States', 2133, 'Animals|Chloroplasts|Chromosome Mapping|Database Management Systems|Databases, Genetic|Documentation|Information Storage and Retrieval|Mitochondria|Organelles|Sequence Alignment|Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth352', '15180927', 'The Dual Organellar GenoMe Annotator (DOGMA) automates the annotation of organellar (plant chloroplast and animal mitochondrial) genomes. It is a Web-based package that allows the use of BLAST searches against a custom database, and conservation of basepairing in the secondary structure of animal mitochondrial tRNAs to identify and annotate genes. DOGMA provides a graphical user interface for viewing and editing annotations. Annotations are stored on our password-protected server to enable repeated sessions of working on the same genome. Finished annotations can be extracted for direct submission to GenBank.'),
(71414, 2004, 'bio', 'Protein complex prediction via cost-based clustering', 'King, A D|Przulj, N|Jurisica, I', 'Department of Computer Science, University of Toronto, Toronto, M5S 3G4, Canada.|Department of Computer Science, University of Toronto, Toronto, M5S 3G4, Canada.|Department of Computer Science, University of Toronto, Toronto, M5S 3G4, Canada.', 'Canada|Canada|Canada', 513, 'Algorithms|Animals|Caenorhabditis elegans Proteins|Cluster Analysis|Computer Simulation|Drosophila Proteins|Models, Biological|Multienzyme Complexes|Protein Interaction Mapping|Proteins|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bth351', '15180928', 'Understanding principles of cellular organization and function can be enhanced if we detect known and predict still undiscovered protein complexes within the cells protein-protein interaction (PPI) network. Such predictions may be used as an inexpensive tool to direct biological experiments. The increasing amount of available PPI data necessitates an accurate and scalable approach to protein complex identification.'),
(71415, 2004, 'bio', 'An entity tagger for recognizing acquired genomic variations in cancer literature', 'McDonald, Ryan T|Winters, R Scott|Mandel, Mark|Jin, Yang|White, Peter S|Pereira, Fernando', 'Department of Computer and Information Science, University of Pennsylvania, 3330 Walnut Street, Philadelphia, PA 19104, USA.|Department of Computer and Information Science, University of Pennsylvania, 3330 Walnut Street, Philadelphia, PA 19104, USA.|Department of Computer and Information Science, University of Pennsylvania, 3330 Walnut Street, Philadelphia, PA 19104, USA.|Department of Computer and Information Science, University of Pennsylvania, 3330 Walnut Street, Philadelphia, PA 19104, USA.|Department of Computer and Information Science, University of Pennsylvania, 3330 Walnut Street, Philadelphia, PA 19104, USA.|Department of Computer and Information Science, University of Pennsylvania, 3330 Walnut Street, Philadelphia, PA 19104, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Database Management Systems|Databases, Bibliographic|Genetic Predisposition to Disease|Genetic Variation|Genome|Information Storage and Retrieval|Natural Language Processing|Neoplasms|Pattern Recognition, Automated|Periodicals as Topic|Software|User-Computer Interface|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/bth350', '15180929', 'VTag is an application for identifying the type, genomic location and genomic state-change of acquired genomic aberrations described in text. The application uses a machine learning technique called conditional random fields. VTag was tested with 345 training and 200 evaluation documents pertaining to cancer genetics. Our experiments resulted in 0.8541 precision, 0.7870 recall and 0.8192 F-measure on the evaluation set.'),
(71416, 2004, 'bio', 'Java Treeview--extensible visualization of microarray data', 'Saldanha, Alok J', 'Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA. alokito@users.sourceforge.net', 'United States', 0, 'Color|Computer Graphics|Databases, Bibliographic|Gene Expression Profiling|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Programming Languages|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth349', '15180930', 'Open source software encourages innovation by allowing users to extend the functionality of existing applications. Treeview is a popular application for the visualization of microarray data, but is closed-source and platform-specific, which limits both its current utility and suitability as a platform for further development. Java Treeview is an open-source, cross-platform rewrite that handles very large datasets well, and supports extensions to the file format that allow the results of additional analysis to be visualized and compared. The combination of a general file format and open source makes Java Treeview an attractive choice for solving a class of visualization problems. An applet version is also available that can be used on any website with no special server-side setup.'),
(71417, 2004, 'bio', 'lga972: a cross-platform application for optimizing LD studies using a genetic algorithm', 'Robles, Jaime R|van den Oord, Edwin J C G', 'Virginia Institute for Psychiatric and Behavioral Genetics, Medical College of Virginia of Virginia Commonwealth University, Richmond, VA 23298-0126, USA. jrobles@vcu.edu|Virginia Institute for Psychiatric and Behavioral Genetics, Medical College of Virginia of Virginia Commonwealth University, Richmond, VA 23298-0126, USA. jrobles@vcu.edu', 'United States|United States', 0, 'Algorithms|Chromosome Mapping|Computer Graphics|DNA Mutational Analysis|Genotype|Information Storage and Retrieval|Linkage Disequilibrium|Models, Genetic|Reproducibility of Results|Research Design|Sample Size|Sensitivity and Specificity|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth348', '15180931', 'lga972 is a user-friendly cross-platform application with a graphical interface for determining the design features of two-stage genetic linkage disequilibrium studies that minimize the genotyping burden.'),
(71418, 2004, 'bio', 'Picky: oligo microarray design for large genomes', 'Chou, Hui-Hsien|Hsia, An-Ping|Mooney, Denise L|Schnable, Patrick S', 'Virginia Institute for Psychiatric and Behavioral Genetics, Medical College of Virginia of Virginia Commonwealth University, Richmond, VA 23298-0126, USA. jrobles@vcu.edu|Virginia Institute for Psychiatric and Behavioral Genetics, Medical College of Virginia of Virginia Commonwealth University, Richmond, VA 23298-0126, USA. jrobles@vcu.edu|Virginia Institute for Psychiatric and Behavioral Genetics, Medical College of Virginia of Virginia Commonwealth University, Richmond, VA 23298-0126, USA. jrobles@vcu.edu|Virginia Institute for Psychiatric and Behavioral Genetics, Medical College of Virginia of Virginia Commonwealth University, Richmond, VA 23298-0126, USA. jrobles@vcu.edu', 'United States|United States|United States|United States', 76, 'Algorithms|Chromosome Mapping|Computer-Aided Design|Equipment Design|Equipment Failure Analysis|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth347', '15180932', 'Many large genomes are getting sequenced nowadays. Biologists are eager to start microarray analysis taking advantage of all known genes of a species, but existing microarray design tools were very inefficient for large genomes. Also, many existing tools operate in a batch mode that does not assure best designs.'),
(71419, 2004, 'bio', 'Visualizations for taxonomic and phylogenetic trees', 'Parr, Cynthia Sims|Lee, Bongshin|Campbell, Dana|Bederson, Benjamin B', 'Human-Computer Interaction Lab, University of Maryland, College Park, MD 20742, USA. csparr@umd.edu|Human-Computer Interaction Lab, University of Maryland, College Park, MD 20742, USA. csparr@umd.edu|Human-Computer Interaction Lab, University of Maryland, College Park, MD 20742, USA. csparr@umd.edu|Human-Computer Interaction Lab, University of Maryland, College Park, MD 20742, USA. csparr@umd.edu', 'United States|United States|United States|United States', 22, 'Algorithms|Animals|Classification|Computer Graphics|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Phylogeny|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth345', '15180933', 'Despite substantial efforts to develop and populate the back-ends of biological databases, front-ends to these systems often rely on taxonomic expertise. This research applies techniques from human-computer interaction research to the biodiversity domain.'),
(71420, 2004, 'bio', 'Supervised machine learning techniques for the classification of metabolic disorders in newborns', 'Baumgartner, C|Böhm, C|Baumgartner, D|Marini, G|Weinberger, K|Olgemöller, B|Liebl, B|Roscher, A A', 'Research Group for Biomedical Data Mining, University for Health Sciences, Medical Informatics and Technology, Innrain 98, A-6020 Innsbruck, Austria. christian.baumgartner@umit.at|Research Group for Biomedical Data Mining, University for Health Sciences, Medical Informatics and Technology, Innrain 98, A-6020 Innsbruck, Austria. christian.baumgartner@umit.at|Research Group for Biomedical Data Mining, University for Health Sciences, Medical Informatics and Technology, Innrain 98, A-6020 Innsbruck, Austria. christian.baumgartner@umit.at|Research Group for Biomedical Data Mining, University for Health Sciences, Medical Informatics and Technology, Innrain 98, A-6020 Innsbruck, Austria. christian.baumgartner@umit.at|Research Group for Biomedical Data Mining, University for Health Sciences, Medical Informatics and Technology, Innrain 98, A-6020 Innsbruck, Austria. christian.baumgartner@umit.at|Research Group for Biomedical Data Mining, University for Health Sciences, Medical Informatics and Technology, Innrain 98, A-6020 Innsbruck, Austria. christian.baumgartner@umit.at|Research Group for Biomedical Data Mining, University for Health Sciences, Medical Informatics and Technology, Innrain 98, A-6020 Innsbruck, Austria. christian.baumgartner@umit.at|Research Group for Biomedical Data Mining, University for Health Sciences, Medical Informatics and Technology, Innrain 98, A-6020 Innsbruck, Austria. christian.baumgartner@umit.at', 'Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria', 28, 'Algorithms|Artificial Intelligence|Biomarkers|Diagnosis, Computer-Assisted|Germany|Humans|Infant, Newborn|Metabolism, Inborn Errors|Neonatal Screening|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Clinical Trial', '10.1093/bioinformatics/bth343', '15180934', 'During the Bavarian newborn screening programme all newborns have been tested for about 20 inherited metabolic disorders. Owing to the amount and complexity of the generated experimental data, machine learning techniques provide a promising approach to investigate novel patterns in high-dimensional metabolic data which form the source for constructing classification rules with high discriminatory power.'),
(71421, 2004, 'bio', 'Transmembrane proteins in the Protein Data Bank: identification and classification', 'Tusnády, Gábor E|Dosztányi, Zsuzsanna|Simon, István', 'Institute of Enzymology, BRC, Hungarian Academy of Sciences, Budapest, Hungary. tusi@enzim.hu|Institute of Enzymology, BRC, Hungarian Academy of Sciences, Budapest, Hungary. tusi@enzim.hu|Institute of Enzymology, BRC, Hungarian Academy of Sciences, Budapest, Hungary. tusi@enzim.hu', 'Hungary|Hungary|Hungary', 176, 'Algorithms|Amino Acid Sequence|Computer Simulation|Databases, Protein|Membrane Proteins|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Structure, Tertiary|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth340', '15180935', 'Integral membrane proteins play important roles in living cells. Although these proteins are estimated to constitute 25% of proteins at a genomic scale, the Protein Data Bank (PDB) contains only a few hundred membrane proteins due to the difficulties with experimental techniques. The presence of transmembrane proteins in the structure data bank, however, is quite invisible, as the annotation of these entries is rather poor. Even if a protein is identified as a transmembrane one, the possible location of the lipid bilayer is not indicated in the PDB because these proteins are crystallized without their natural lipid bilayer, and currently no method is publicly available to detect the possible membrane plane using the atomic coordinates of membrane proteins.'),
(71422, 2004, 'bio', 'A spline function approach for detecting differentially expressed genes in microarray data analysis', 'He, Wenqing', 'Prossermen Center for Health Research, Samuel Lunenfeld Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada M5G 1X5. he@mshri.on.ca', 'Canada', 6, 'Algorithms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Leukemia|Models, Genetic|Models, Statistical|Neoplasm Proteins|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis', 'Comparative Study', '10.1093/bioinformatics/bth339', '15180936', 'A primary objective of microarray studies is to determine genes which are differentially expressed under various conditions. Parametric tests, such as two-sample t-tests, may be used to identify differentially expressed genes, but they require some assumptions that are not realistic for many practical problems. Non-parametric tests, such as empirical Bayes methods and mixture normal approaches, have been proposed, but the inferences are complicated and the tests may not have as much power as parametric models.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71423, 2004, 'bio', 'Bayesian integrated functional analysis of microarray data', 'Bhattacharjee, Madhuchhanda|Pritchard, Colin C|Nelson, Peter S|Arjas, Elja', 'Rolf Nevanlinna Institute, Department of Mathematics and Statistics, University of Helsinki, P.O. Box 68, FIN 00014, Helsinki, Finland. mab@rni.helsinki.fi|Rolf Nevanlinna Institute, Department of Mathematics and Statistics, University of Helsinki, P.O. Box 68, FIN 00014, Helsinki, Finland. mab@rni.helsinki.fi|Rolf Nevanlinna Institute, Department of Mathematics and Statistics, University of Helsinki, P.O. Box 68, FIN 00014, Helsinki, Finland. mab@rni.helsinki.fi|Rolf Nevanlinna Institute, Department of Mathematics and Statistics, University of Helsinki, P.O. Box 68, FIN 00014, Helsinki, Finland. mab@rni.helsinki.fi', 'Finland|Finland|Finland|Finland', 19, 'Algorithms|Animals|Bayes Theorem|Gene Expression Profiling|Gene Expression Regulation|Kidney|Liver|Male|Mice|Oligonucleotide Array Sequence Analysis|Organ Specificity|Proteome|Structure-Activity Relationship|Systems Integration|Testis|Tissue Distribution', 'Comparative Study', '10.1093/bioinformatics/bth338', '15180937', 'The statistical analysis of microarray data usually proceeds in a sequential manner, with the output of the previous step always serving as the input of the next one. However, the methods currently used in such analyses do not properly account for the fact that the intermediate results may not always be correct, then leading to cumulating error in the inferences drawn based on such steps.'),
(71424, 2004, 'bio', 'Reconstruction of gene networks using Bayesian learning and manipulation experiments', 'Pournara, Iosifina|Wernisch, Lorenz', 'Department of Crystallography, Birkbeck College, University of London, Malet Street, London, WC1E 7HX, UK.|Department of Crystallography, Birkbeck College, University of London, Malet Street, London, WC1E 7HX, UK.', 'United Kingdom|United Kingdom', 55, 'Algorithms|Animals|Artificial Intelligence|Bayes Theorem|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Biological|Models, Statistical|Neoplasm Proteins|Neoplasms|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bth337', '15180938', 'The analysis of high-throughput experimental data, for example from microarray experiments, is currently seen as a promising way of finding regulatory relationships between genes. Bayesian networks have been suggested for learning gene regulatory networks from observational data. Not all causal relationships can be inferred from correlation data alone. Often several equivalent but different directed graphs explain the data equally well. Intervention experiments where genes are manipulated can help to narrow down the range of possible networks.'),
(71425, 2004, 'bio', 'A statistical framework for the design of microarray experiments and effective detection of differential gene expression', 'Zhang, Shu-Dong|Gant, Timothy W', 'MRC Toxicology Unit, Hodgkin Building, Lancaster Road, University of Leicester, Leicester, UK. sdz1@le.ac.uk|MRC Toxicology Unit, Hodgkin Building, Lancaster Road, University of Leicester, Leicester, UK. sdz1@le.ac.uk', 'United Kingdom|United Kingdom', 28, 'Algorithms|Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Programming Languages|Reproducibility of Results|Research Design|Sample Size|Sensitivity and Specificity|Software', 'Comparative Study', '10.1093/bioinformatics/bth336', '15180939', 'Microarray experiments generate a high data volume. However, often due to financial or experimental considerations, e.g. lack of sample, there is little or no replication of the experiments or hybridizations. These factors combined with the intrinsic variability associated with the measurement of gene expression can result in an unsatisfactory detection rate of differential gene expression (DGE). Our motivation was to provide an easy to use measure of the success rate of DGE detection that could find routine use in the design of microarray experiments or in post-experiment assessment.'),
(71426, 2004, 'bio', 'STAR: an algorithm to Search for Tandem Approximate Repeats', 'Delgrange, Olivier|Rivals, Eric', 'Université de Mons Hainaut, Service dInformatique Générale, Avenue du champ de Mars, 6, Mons, 7000, Belgique and LIRMM, CNRS UMR 5506, 161, rue Ada, Montpellier Cedex 5, 34392, France.|Université de Mons Hainaut, Service dInformatique Générale, Avenue du champ de Mars, 6, Mons, 7000, Belgique and LIRMM, CNRS UMR 5506, 161, rue Ada, Montpellier Cedex 5, 34392, France.', 'France|France', 78, 'Algorithms|Genetic Variation|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Tandem Repeat Sequences', 'Comparative Study', '10.1093/bioinformatics/bth335', '15180940', 'Tandem repeats consist in approximate and adjacent repetitions of a DNA motif. Such repeats account for large portions of eukaryotic genomes and have also been found in other life kingdoms. Owing to their polymorphism, tandem repeats have proven useful in genome cartography, forensic and population studies, etc. Nevertheless, they are not systematically detected nor annotated in genome projects. Partially because of this lack of data, their evolution is still poorly understood.'),
(71427, 2004, 'bio', 'EST clustering error evaluation and correction', 'Wang, Ji-Ping Z|Lindsay, Bruce G|Leebens-Mack, James|Cui, Liying|Wall, Kerr|Miller, Webb C|dePamphilis, Claude W', 'Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu', 'United States|United States|United States|United States|United States|United States|United States', 59, 'Algorithms|Arabidopsis|Chromosome Mapping|Cluster Analysis|Data Interpretation, Statistical|Expressed Sequence Tags|Gene Expression Profiling|Genetic Variation|Genome, Plant|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth342', '15189818', 'The gene expression intensity information conveyed by (EST) Expressed Sequence Tag data can be used to infer important cDNA library properties, such as gene number and expression patterns. However, EST clustering errors, which often lead to greatly inflated estimates of obtained unique genes, have become a major obstacle in the analyses. The EST clustering error structure, the relationship between clustering error and clustering criteria, and possible error correction methods need to be systematically investigated.'),
(71428, 2004, 'bio', 'A practical and robust sequence search strategy for structural genomics target selection', 'Bray, James E|Marsden, Russell L|Rison, Stuart C G|Savchenko, Alexei|Edwards, Aled M|Thornton, Janet M|Orengo, Christine A', 'Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London, WC1E 6BT, UK. james.bray@sgc.ox.ac.uk|Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London, WC1E 6BT, UK. james.bray@sgc.ox.ac.uk|Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London, WC1E 6BT, UK. james.bray@sgc.ox.ac.uk|Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London, WC1E 6BT, UK. james.bray@sgc.ox.ac.uk|Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London, WC1E 6BT, UK. james.bray@sgc.ox.ac.uk|Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London, WC1E 6BT, UK. james.bray@sgc.ox.ac.uk|Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London, WC1E 6BT, UK. james.bray@sgc.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 11, 'Algorithms|Chromosome Mapping|Gene Targeting|Genes|Genomics|Protein Structure, Tertiary|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bth240', '15201178', 'Target selection strategies for structural genomic projects must be able to prioritize gene regions on the basis of significant sequence similarity with proteins that have already been structurally determined. With the rapid development of protein comparison software a robust prioritization scheme should be independent of the choice of algorithm and be able to incorporate different sequence similarity thresholds.'),
(71429, 2004, 'bio', 'Mean and variance of the Gibbs free energy of oligonucleotides in the nearest neighbor model under varying conditions', 'Rahmann, Sven|Gräfe, Christine', 'Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, D-14195 Berlin, Germany. Sven.Rahmann@cebitec.uni-bielefeld.de|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, D-14195 Berlin, Germany. Sven.Rahmann@cebitec.uni-bielefeld.de', 'Germany|Germany', 0, 'Base Composition|Computer Simulation|DNA Probes|Energy Transfer|Models, Chemical|Models, Statistical|Nucleic Acid Conformation|Nucleic Acid Hybridization|Oligonucleotides|Sequence Analysis, DNA|Stochastic Processes|Temperature|Thermodynamics', 'Comparative Study', '10.1093/bioinformatics/bth334', '15201179', 'In order to assess the stability of DNA-DNA hybridizations-for example during PCR primer design or oligonucleotide selection for microarrays-one needs to predict the change in Gibbs free energy DeltaG during hybridization. The nearest neighbor model provides a good compromise between accuracy and computational simplicity for this task. To determine optimal combinations of reaction parameters (temperature, salt concentration, oligonucleotide length and GC-content), one would like to understand how DeltaG depends on all of these parameters simultaneously.'),
(71430, 2004, 'bio', 'GOLDsurfer: three dimensional display of linkage disequilibrium', 'Pettersson, Fredrik|Jonsson, Oskar|Cardon, Lon R', 'Department of Organic Chemistry, Umeä University, Sweden.|Department of Organic Chemistry, Umeä University, Sweden.|Department of Organic Chemistry, Umeä University, Sweden.', 'Sweden|Sweden|Sweden', 0, 'Chromosome Mapping|Color|Computer Graphics|Imaging, Three-Dimensional|Information Storage and Retrieval|Linkage Disequilibrium|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth341', '15201180', 'GOLDsurfer is a java-based analysis and graphics program for three-dimensional plotting of linkage disequilibrium (LD). Simultaneous presentation of LD measures, including recombination rate estimates and disease association statistics, helps to clarify LD patterns and facilitates interpretations based on multiple indices of local genetic data.'),
(71431, 2004, 'bio', 'Biologically valid linear factor models of gene expression', 'Girolami, Mark|Breitling, Rainer', 'Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, UK. girolami@dcs.gla.ac.uk|Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, UK. girolami@dcs.gla.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Cell Cycle Proteins|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Linear Models|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Oxidative Stress|Principal Component Analysis|Saccharomyces cerevisiae Proteins', 'Comparative Study', '10.1093/bioinformatics/bth354', '15201181', 'The identification of physiological processes underlying and generating the expression pattern observed in microarray experiments is a major challenge. Principal component analysis (PCA) is a linear multivariate statistical method that is regularly employed for that purpose as it provides a reduced-dimensional representation for subsequent study of possible biological processes responding to the particular experimental conditions. Making explicit the data assumptions underlying PCA highlights their lack of biological validity thus making biological interpretation of the principal components problematic. A microarray data representation which enables clear biological interpretation is a desirable analysis tool.'),
(71432, 2004, 'bio', 'Breakpoint identification and smoothing of array comparative genomic hybridization data', 'Jong, Kees|Marchiori, Elena|Meijer, Gerrit|Vaart, A V D|Ylstra, Bauke', 'Faculty of Sciences, Vrije Universiteit, De Boelelaan 1117, Amsterdam 1081HV, The Netherlands. cjong@few.vu.nl <cjong@few.vu.nl>|Faculty of Sciences, Vrije Universiteit, De Boelelaan 1117, Amsterdam 1081HV, The Netherlands. cjong@few.vu.nl <cjong@few.vu.nl>|Faculty of Sciences, Vrije Universiteit, De Boelelaan 1117, Amsterdam 1081HV, The Netherlands. cjong@few.vu.nl <cjong@few.vu.nl>|Faculty of Sciences, Vrije Universiteit, De Boelelaan 1117, Amsterdam 1081HV, The Netherlands. cjong@few.vu.nl <cjong@few.vu.nl>|Faculty of Sciences, Vrije Universiteit, De Boelelaan 1117, Amsterdam 1081HV, The Netherlands. cjong@few.vu.nl <cjong@few.vu.nl>', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 148, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|Gene Dosage|Gene Expression Profiling|In Situ Hybridization|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth355', '15201182', 'We describe a tool, called aCGH-Smooth, for the automated identification of breakpoints and smoothing of microarray comparative genomic hybridization (array CGH) data. aCGH-Smooth is written in visual C++, has a user-friendly interface including a visualization of the results and user-defined parameters adapting the performance of data smoothing and breakpoint recognition. aCGH-Smooth can handle array-CGH data generated by all array-CGH platforms: BAC, PAC, cosmid, cDNA and oligo CGH arrays. The tool has been successfully applied to real-life data.'),
(71433, 2004, 'bio', 'CTRD: a fast applet for computing signed translocation distance between genomes', 'Feng, WangSen|Wang, Lusheng|Zhu, Daming', 'Department of Computer Science, Peking University, Beijing, 100871, P.R. China. cswangl@cityu.edu.hk|Department of Computer Science, Peking University, Beijing, 100871, P.R. China. cswangl@cityu.edu.hk|Department of Computer Science, Peking University, Beijing, 100871, P.R. China. cswangl@cityu.edu.hk', 'China|China|China', 0, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|Evolution, Molecular|Internet|Programming Languages|Sequence Alignment|Software|Translocation, Genetic', 'Journal Article', '10.1093/bioinformatics/bth356', '15201183', 'CTRD is a software for computing translocation distance between genomes. It takes two genomes as its input and tests whether one genome can be transformed into the other. If possible, it computes the translocation distance between two genomes, and gives the translocation operation serial. We adopt the fastest known O(n(2)log n) algorithm. Our contributions include (1) give a necessary and sufficient condition to ensure that one genome can be transformed into the other for translocation operations, and (2) develop a software using the fastest known O(n(2)log n) algorithm.'),
(71434, 2004, 'bio', 'TMRPres2D: high quality visual representation of transmembrane protein models', 'Spyropoulos, Ioannis C|Liakopoulos, Theodore D|Bagos, Pantelis G|Hamodrakas, Stavros J', 'Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens 157 01, Greece.|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens 157 01, Greece.|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens 157 01, Greece.|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens 157 01, Greece.', 'Greece|Greece|Greece|Greece', 101, 'Amino Acid Sequence|Computer Graphics|Membrane Proteins|Models, Molecular|Molecular Sequence Data|Protein Conformation|Sequence Analysis, Protein|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth358', '15201184', 'The TransMembrane protein Re-Presentation in 2-Dimensions (TMRPres2D) tool, automates the creation of uniform, two-dimensional, high analysis graphical images/models of alpha-helical or beta-barrel transmembrane proteins. Protein sequence data and structural information may be acquired from public protein knowledge bases, emanate from prediction algorithms, or even be defined by the user. Several important biological and physical sequence attributes can be embedded in the graphical representation.'),
(71435, 2004, 'bio', 'QuickJoin--fast neighbour-joining tree reconstruction', 'Mailund, Thomas|Pedersen, Christian N S', 'Bioinformatics Research Center (BiRC), University of Aarhus, Høegh-Guldbergs Grade 10, Bldg. 090, DK-8000 Arhus C, Denmark. mailund@birc.dk|Bioinformatics Research Center (BiRC), University of Aarhus, Høegh-Guldbergs Grade 10, Bldg. 090, DK-8000 Arhus C, Denmark. mailund@birc.dk', 'Denmark|Denmark', 22, 'Algorithms|Animals|Chromosome Mapping|Evolution, Molecular|Humans|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology|Software', 'Comparative Study', '10.1093/bioinformatics/bth359', '15201185', 'We have built a tool for fast construction of very large phylogenetic trees. The tool uses heuristics for speeding up the neighbour-joining algorithm-while still constructing the same tree as the original neighbour-joining algorithm-making it possible to construct trees for 8000 species in <10 min on a single desktop PC. In comparison, the same task takes more than 30 min using the QuickTree neighbour-joining implementation.'),
(71436, 2004, 'bio', 'SNPicker: a graphical tool for primer picking in designing mutagenic endonuclease restriction assays', 'Niu, Tianhua|Hu, Zhenjun', 'Division of Preventive Medicine, Brigham and Womens Hospital, Harvard Medical School, 900 Commonwealth Avenue, MA 02215, USA. tniu@hsph.harvard.edu|Division of Preventive Medicine, Brigham and Womens Hospital, Harvard Medical School, 900 Commonwealth Avenue, MA 02215, USA. tniu@hsph.harvard.edu', 'United States|United States', 11, 'Computer Graphics|DNA Probes|Mutagenesis, Site-Directed|Polymorphism, Single Nucleotide|Restriction Mapping|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth360', '15201186', 'Simple, low-cost and accurate genotyping methods for single nucleotide polymorphisms (SNPs) are in high demand in the post-genome-sequencing era. We present a graphical tool called SNPicker, implemented in Java, which significantly facilitates the design of mutagenic endonuclease restriction assays. SNPicker uses the online NEB REBASE to automatically scan for all possible designs of mutagenic primers that can facilitate the picking of mismatched PCR primers to artificially introduce or abolish a restriction site at the target SNP site. We successfully applied SNPicker in designing endonuclease restriction assays for 14 SNPs for the MTHFR gene, the Coagulation Factor II gene and the Coagulation Factor V gene. The SNP assays designed using SNPicker were cross-validated using the MassARRAY technology.'),
(71437, 2004, 'bio', 'Taverna: a tool for the composition and enactment of bioinformatics workflows', 'Oinn, Tom|Addis, Matthew|Ferris, Justin|Marvin, Darren|Senger, Martin|Greenwood, Mark|Carver, Tim|Glover, Kevin|Pocock, Matthew R|Wipat, Anil|Li, Peter', 'EMBL European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK.|EMBL European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK.|EMBL European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK.|EMBL European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK.|EMBL European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK.|EMBL European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK.|EMBL European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK.|EMBL European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK.|EMBL European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK.|EMBL European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK.|EMBL European Bioinformatics Institute, Hinxton, 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', 1079, 'Computational Biology|Computer Communication Networks|Computer Graphics|Database Management Systems|Information Storage and Retrieval|Internet|Online Systems|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth361', '15201187', 'In silico experiments in bioinformatics involve the co-ordinated use of computational tools and information repositories. A growing number of these resources are being made available with programmatic access in the form of Web services. Bioinformatics scientists will need to orchestrate these Web services in workflows as part of their analyses.'),
(71438, 2004, 'bio', 'The CRASSS plug-in for integrating annotation data with hierarchical clustering results', 'Buehler, Eugen C|Sachs, Jeffrey R|Shao, Kui|Bagchi, Ansuman|Ungar, Lyle H', 'Applied Computer Science and Mathematics, Merck Research Laboratories, P.O. Box 2000 RY84-202, Rahway, NJ 07065 0900, USA. eugen_buehler@merck.com|Applied Computer Science and Mathematics, Merck Research Laboratories, P.O. Box 2000 RY84-202, Rahway, NJ 07065 0900, USA. eugen_buehler@merck.com|Applied Computer Science and Mathematics, Merck Research Laboratories, P.O. Box 2000 RY84-202, Rahway, NJ 07065 0900, USA. eugen_buehler@merck.com|Applied Computer Science and Mathematics, Merck Research Laboratories, P.O. Box 2000 RY84-202, Rahway, NJ 07065 0900, USA. eugen_buehler@merck.com|Applied Computer Science and Mathematics, Merck Research Laboratories, P.O. Box 2000 RY84-202, Rahway, NJ 07065 0900, USA. eugen_buehler@merck.com', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Cluster Analysis|Databases, Genetic|Documentation|Gene Expression Profiling|Information Storage and Retrieval|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth362', '15201188', 'We describe an algorithm for finding the most statistically significant non-overlapping subtrees of a hierarchical clustering of gene expression data with respect to a set of secondary data labels on genes. The method is implemented as a Java plug-in for a commercial gene expression analysis program (GeneSpring).'),
(71439, 2004, 'bio', 'BioSilico: an integrated metabolic database system', 'Hou, Bo Kyeng|Kim, Jin Sik|Jun, Ji Hoon|Lee, Dong-Yup|Kim, Yong Wook|Chae, Sujin|Roh, Mira|In, Yong-Ho|Lee, Sang Yup', 'Department of BioSystems and Bioinformatics Research Center, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of BioSystems and Bioinformatics Research Center, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of BioSystems and Bioinformatics Research Center, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of BioSystems and Bioinformatics Research Center, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of BioSystems and Bioinformatics Research Center, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of BioSystems and Bioinformatics Research Center, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of BioSystems and Bioinformatics Research Center, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of BioSystems and Bioinformatics Research Center, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of BioSystems and Bioinformatics Research Center, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.', '-|-|-|-|-|-|-|-|-', 0, 'Database Management Systems|Databases, Factual|Gene Expression Regulation|Information Storage and Retrieval|Internet|Metabolism|Models, Biological|Signal Transduction|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth363', '15201189', 'BioSilico is a web-based database system that facilitates the search and analysis of metabolic pathways. Heterogeneous metabolic databases including LIGAND, ENZYME, EcoCyc and MetaCyc are integrated in a systematic way, thereby allowing users to efficiently retrieve the relevant information on enzymes, biochemical compounds and reactions. In addition, it provides well-designed view pages for more detailed summary information. BioSilico is developed as an extensible system with a robust systematic architecture.'),
(71440, 2004, 'bio', 'Predicting the efficacy of short oligonucleotides in antisense and RNAi experiments with boosted genetic programming', 'Saetrom, Pål', 'Interagon AS, Medisinsk teknisk senter, N-7489 Trondheim, Norway.', 'Norway', 52, 'Algorithms|Artificial Intelligence|Gene Silencing|Gene Targeting|Models, Genetic|Oligonucleotides, Antisense|RNA Interference|RNA, Small Interfering|Thionucleotides', 'Comparative Study', '10.1093/bioinformatics/bth364', '15201190', 'Both small interfering RNAs (siRNAs) and antisense oligonucleotides can selectively block gene expression. Although the two methods rely on different cellular mechanisms, these methods share the common property that not all oligonucleotides (oligos) are equally effective. That is, if mRNA target sites are picked at random, many of the antisense or siRNA oligos will not be effective. Algorithms that can reliably predict the efficacy of candidate oligos can greatly reduce the cost of knockdown experiments, but previous attempts to predict the efficacy of antisense oligos have had limited success. Machine learning has not previously been used to predict siRNA efficacy.'),
(71441, 2004, 'bio', 'The UniMarker (UM) method for synteny mapping of large genomes', 'Liao, Ben-Yang|Chang, Yu-Jung|Ho, Jan-Ming|Hwang, Ming-Jing', 'Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.', '-|-|-|-', 0, 'Algorithms|Animals|Chromosome Mapping|Chromosomes, Human, Pair 16|Conserved Sequence|Evolution, Molecular|Genome, Human|Genomic Islands|Humans|Mice|Sequence Alignment|Sequence Analysis, DNA|Software|Species Specificity|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth380', '15217808', 'Synteny mapping, or detecting regions that are orthologous between two genomes, is a key step in studies of comparative genomics. For completely sequenced genomes, this is increasingly accomplished by whole-genome sequence alignment. However, such methods are computationally expensive, especially for large genomes, and require rather complicated post-processing procedures to filter out non-orthologous sequence matches.'),
(71442, 2004, 'bio', 'BioNetGen: software for rule-based modeling of signal transduction based on the interactions of molecular domains', 'Blinov, Michael L|Faeder, James R|Goldstein, Byron|Hlavacek, William S', 'Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.|Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.|Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.|Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Cell Physiological Phenomena|Computer Simulation|Models, Biological|Models, Chemical|Programming Languages|Protein Interaction Mapping|Proteins|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth378', '15217809', 'BioNetGen allows a user to create a computational model that characterizes the dynamics of a signal transduction system, and that accounts comprehensively and precisely for specified enzymatic activities, potential post-translational modifications and interactions of the domains of signaling molecules. The output defines and parameterizes the network of molecular species that can arise during signaling and provides functions that relate model variables to experimental readouts of interest. Models that can be generated are relevant for rational drug discovery, analysis of proteomic data and mechanistic studies of signal transduction.'),
(71443, 2004, 'bio', 'Phan3D: design of biological phantoms in 3D electron microscopy', 'Bilbao-Castro, J R|Sorzano, C O S|García, I|Fernández, J J', 'Centro Nacional Biotecnologia, Universidad Autonoma, 28049 Madrid, Spain.|Centro Nacional Biotecnologia, Universidad Autonoma, 28049 Madrid, Spain.|Centro Nacional Biotecnologia, Universidad Autonoma, 28049 Madrid, Spain.|Centro Nacional Biotecnologia, Universidad Autonoma, 28049 Madrid, Spain.', 'Spain|Spain|Spain|Spain', 0, 'Computer Graphics|Computer Simulation|Computer-Aided Design|Image Interpretation, Computer-Assisted|Imaging, Three-Dimensional|Microscopy, Electron|Models, Biological|Models, Molecular|Phantoms, Imaging|Proteins|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth377', '15217810', 'Three-Dimensional Electron Microscopy (3DEM) has turned out to be a major player in structural proteomics. In 3DEM, tens of thousands of EM images from a macromolecule at different views are combined to derive its structure by means of a 3D reconstruction algorithm. However, for an optimal reconstruction, the most suitable algorithm has to be used and its parameters have to be tuned for the macromolecule under study and the experimental conditions found. The use of phantoms is central to objective comparison of reconstruction algorithms and optimization of their parameters. Phan3D is a tool intended to provide a fully visual and interactive environment that facilitates the design of phantoms resembling biological specimens in 3DEM. Phan3D has been developed as an alternative to the tedious, error-prone and old-fashioned phantom design that is based on hand-written text description files.'),
(71444, 2004, 'bio', 'A web portal for classification of expression data using maximal margin linear programming', 'Antonov, Alexey V|Tetko, Igor V|Prokopenko, Volodymyr V|Kosykh, Denis|Mewes, Hans W', 'GSF National Research Center for Environment and Health, Institute for Bioinformatics, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.|GSF National Research Center for Environment and Health, Institute for Bioinformatics, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.|GSF National Research Center for Environment and Health, Institute for Bioinformatics, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.|GSF National Research Center for Environment and Health, Institute for Bioinformatics, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.|GSF National Research Center for Environment and Health, Institute for Bioinformatics, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 1, 'Algorithms|Artificial Intelligence|Gene Expression Profiling|Internet|Oligonucleotide Array Sequence Analysis|Programming, Linear|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth376', '15217811', 'The Maximal Margin (MAMA) linear programming classification algorithm has recently been proposed and tested for cancer classification based on expression data. It demonstrated sound performance on publicly available expression datasets. We developed a web interface to allow potential users easy access to the MAMA classification tool. Basic and advanced options provide flexibility in exploitation. The input data format is the same as that used in most publicly available datasets. This makes the web resource particularly convenient for non-expert machine learning users working in the field of expression data analysis.'),
(71445, 2004, 'bio', 'HumanMSD and MouseMSD: generating genetic maps for human and murine microsatellite markers', 'Bahlo, M|Xing, L|Wilkinson, C R', 'Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research, Parkville 3050 VIC, Australia.|Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research, Parkville 3050 VIC, Australia.|Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research, Parkville 3050 VIC, Australia.', 'Australia|Australia|Australia', 4, 'Algorithms|Animals|Chromosome Mapping|Computer Graphics|Database Management Systems|Information Storage and Retrieval|Internet|Linkage Disequilibrium|Mice|Microsatellite Repeats|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth375', '15217812', 'We present two Web interfaces that generate genetic maps for given sets of human or mouse microsatellite markers. The genetic maps are generated from available databases using linear interpolation of physical map distances to infer genetic map positions for missing markers in these databases.'),
(71446, 2004, 'bio', 'Evidence that microRNA precursors, unlike other non-coding RNAs, have lower folding free energies than random sequences', 'Bonnet, Eric|Wuyts, Jan|Rouzé, Pierre|Van de Peer, Yves', 'Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent University, Technologiepark 927, B-9052 Ghent, Belgium.|Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent University, Technologiepark 927, B-9052 Ghent, Belgium.|Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent University, Technologiepark 927, B-9052 Ghent, Belgium.|Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent University, Technologiepark 927, B-9052 Ghent, Belgium.', 'Belgium|Belgium|Belgium|Belgium', 0, 'Animals|Caenorhabditis elegans|Computer Simulation|Drosophila melanogaster|Energy Transfer|Humans|MicroRNAs|Models, Chemical|Models, Statistical|Nucleic Acid Conformation|Nucleic Acid Denaturation|Sequence Alignment|Sequence Analysis, RNA|Structure-Activity Relationship|Thermodynamics', 'Evaluation Studies', '10.1093/bioinformatics/bth374', '15217813', 'Most non-coding RNAs are characterized by a specific secondary and tertiary structure that determines their function. Here, we investigate the folding energy of the secondary structure of non-coding RNA sequences, such as microRNA precursors, transfer RNAs and ribosomal RNAs in several eukaryotic taxa. Statistical biases are assessed by a randomization test, in which the predicted minimum free energy of folding is compared with values obtained for structures inferred from randomly shuffling the original sequences.'),
(71447, 2004, 'bio', 'Constrained clusters of gene expression profiles with pathological features', 'Sese, Jun|Kurokawa, Yukinori|Monden, Morito|Kato, Kikuya|Morishita, Shinichi', 'Undergraduate Program for Bioinformatics and Systems Biology, Graduate School of Frontier Sciences, University of Tokyo, Bunkyo, Tokyo, Japan. sesejun@gi.k.u-tokyo.ac.jp|Undergraduate Program for Bioinformatics and Systems Biology, Graduate School of Frontier Sciences, University of Tokyo, Bunkyo, Tokyo, Japan. sesejun@gi.k.u-tokyo.ac.jp|Undergraduate Program for Bioinformatics and Systems Biology, Graduate School of Frontier Sciences, University of Tokyo, Bunkyo, Tokyo, Japan. sesejun@gi.k.u-tokyo.ac.jp|Undergraduate Program for Bioinformatics and Systems Biology, Graduate School of Frontier Sciences, University of Tokyo, Bunkyo, Tokyo, Japan. sesejun@gi.k.u-tokyo.ac.jp|Undergraduate Program for Bioinformatics and Systems Biology, Graduate School of Frontier Sciences, University of Tokyo, Bunkyo, Tokyo, Japan. sesejun@gi.k.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan|Japan', 32, 'Algorithms|Biomarkers, Tumor|Cluster Analysis|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Liver Neoplasms|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Clinical Trial', '10.1093/bioinformatics/bth373', '15217814', 'Gene expression profiles should be useful in distinguishing variations in disease, since they reflect accurately the status of cells. The primary clustering of gene expression reveals the genotypes that are responsible for the proximity of members within each cluster, while further clustering elucidates the pathological features of the individual members of each cluster. However, since the first clustering process and the second classification step, in which the features are associated with clusters, are performed independently, the initial set of clusters may omit genes that are associated with pathologically meaningful features. Therefore, it is important to devise a way of identifying gene expression clusters that are associated with pathological features.'),
(71448, 2004, 'bio', 'Standardization and denoising algorithms for mass spectra to classify whole-organism bacterial specimens', 'Satten, Glen A|Datta, Somnath|Moura, Hercules|Woolfitt, Adrian R|Carvalho, Maria da G|Carlone, George M|De, Barun K|Pavlopoulos, Antonis|Barr, John R', 'Division of Laboratory Science, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. gsatten@cdc.gov|Division of Laboratory Science, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. gsatten@cdc.gov|Division of Laboratory Science, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. gsatten@cdc.gov|Division of Laboratory Science, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. gsatten@cdc.gov|Division of Laboratory Science, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. gsatten@cdc.gov|Division of Laboratory Science, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. gsatten@cdc.gov|Division of Laboratory Science, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. gsatten@cdc.gov|Division of Laboratory Science, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. gsatten@cdc.gov|Division of Laboratory Science, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. gsatten@cdc.gov', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 11, 'Algorithms|Artificial Intelligence|Bacteria|Bacterial Proteins|Biomarkers|Escherichia coli|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Comparative Study', '10.1093/bioinformatics/bth372', '15217815', 'Application of mass spectrometry in proteomics is a breakthrough in high-throughput analyses. Early applications have focused on protein expression profiles to differentiate among various types of tissue samples (e.g. normal versus tumor). Here our goal is to use mass spectra to differentiate bacterial species using whole-organism samples. The raw spectra are similar to spectra of tissue samples, raising some of the same statistical issues (e.g. non-uniform baselines and higher noise associated with higher baseline), but are substantially noisier. As a result, new preprocessing procedures are required before these spectra can be used for statistical classification.'),
(71449, 2004, 'bio', 'Variance-modeled posterior inference of microarray data: detecting gene-expression changes in 3T3-L1 adipocytes', 'Hsiao, A|Worrall, D S|Olefsky, J M|Subramaniam, S', 'Department of Bioengineering, UC San Diego, La Jolla, CA 92093, USA.|Department of Bioengineering, UC San Diego, La Jolla, CA 92093, USA.|Department of Bioengineering, UC San Diego, La Jolla, CA 92093, USA.|Department of Bioengineering, UC San Diego, La Jolla, CA 92093, USA.', 'United States|United States|United States|United States', 33, '3T3-L1 Cells|Adipocytes|Algorithms|Animals|Dimethyl Sulfoxide|Gene Expression Profiling|Gene Expression Regulation|Genetic Variation|Mice|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Thiazolidinediones|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bth371', '15217816', 'Microarrays are becoming an increasingly common tool for observing changes in gene expression over a large cross section of the genome. This experimental tool is particularly valuable for understanding the genome-wide changes in gene transcription in response to thiazolidinedione (TZD) treatment. The TZD class of drugs is known to improve insulin-sensitivity in diabetic patients, and is clinically used in treatment regimens. In cells, TZDs bind to and activate the transcriptional activity of peroxisome proliferator-activated receptor gamma (PPAR-gamma). Large-scale array analyses will provide some insight into the mechanisms of TZD-mediated insulin sensitization. Unfortunately, a theoretical basis for analyzing array data has not kept pace with the rapid adoption of this tool. The methods that are commonly used, particularly the fold-change approach and the standard t-test, either lack statistical rigor or resort to generalized statistical models that do not accurately estimate variability at low replicate numbers.'),
(71450, 2004, 'bio', 'Comparison of probabilistic combination methods for protein secondary structure prediction', 'Liu, Yan|Carbonell, Jaime|Klein-Seetharaman, Judith|Gopalakrishnan, Vanathi', 'Language Technologies Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA15213, USA. yanliu@cs.cmu.edu|Language Technologies Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA15213, USA. yanliu@cs.cmu.edu|Language Technologies Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA15213, USA. yanliu@cs.cmu.edu|Language Technologies Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA15213, USA. yanliu@cs.cmu.edu', 'United States|United States|United States|United States', 27, 'Algorithms|Computer Simulation|Models, Chemical|Models, Molecular|Models, Statistical|Protein Conformation|Protein Folding|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth370', '15217817', 'Protein secondary structure prediction is an important step towards understanding how proteins fold in three dimensions. Recent analysis by information theory indicates that the correlation between neighboring secondary structures are much stronger than that of neighboring amino acids. In this article, we focus on the combination problem for sequences, i.e. combining the scores or assignments from single or multiple prediction systems under the constraint of a whole sequence, as a target for improvement in protein secondary structure prediction.'),
(71451, 2004, 'bio', 'Developing optimal non-linear scoring function for protein design', 'Hu, Changyu|Li, Xiang|Liang, Jie', 'Department of Bioengineering, SEO, MC-063, University of Illinois at Chicago, 851 S. Morgan Street, Room 218, Chicago, IL 60607-7052, USA.|Department of Bioengineering, SEO, MC-063, University of Illinois at Chicago, 851 S. Morgan Street, Room 218, Chicago, IL 60607-7052, USA.|Department of Bioengineering, SEO, MC-063, University of Illinois at Chicago, 851 S. Morgan Street, Room 218, Chicago, IL 60607-7052, USA.', 'United States|United States|United States', 23, 'Algorithms|Artificial Intelligence|Computer Simulation|Drug Design|Models, Chemical|Models, Molecular|Nonlinear Dynamics|Protein Conformation|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth369', '15217818', 'Motivation. Protein design aims to identify sequences compatible with a given protein fold but incompatible to any alternative folds. To select the correct sequences and to guide the search process, a design scoring function is critically important. Such a scoring function should be able to characterize the global fitness landscape of many proteins simultaneously.'),
(71452, 2004, 'bio', 'A comparative method for identification of gene structures and alternatively spliced variants', 'Chuang, Trees-Juen|Chen, Feng-Chi|Chou, Meng-Yuan', 'Genomics Research Center, Academia, Sinica, Taipei, Taiwan.|Genomics Research Center, Academia, Sinica, Taipei, Taiwan.|Genomics Research Center, Academia, Sinica, Taipei, Taiwan.', '-|-|-', 0, 'Algorithms|Alternative Splicing|Animals|Chromosome Mapping|Conserved Sequence|DNA, Recombinant|Evolution, Molecular|Expressed Sequence Tags|Genetic Variation|Mice|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth368', '15217819', 'Alternative splicing (AS) serves as a mechanism to create diversity among functional proteins. Increasing evidence indicates that a large portion of genes have AS forms. Hence AS variants should be considered while analyzing gene structures.'),
(71453, 2004, 'bio', 'PTGL--a web-based database application for protein topologies', 'May, Patrick|Barthel, Stefan|Koch, Ina', 'BCB Junior Research Group, ZIB Berlin, Takustr.7, Berlin 14195, Germany.|BCB Junior Research Group, ZIB Berlin, Takustr.7, Berlin 14195, Germany.|BCB Junior Research Group, ZIB Berlin, Takustr.7, Berlin 14195, Germany.', 'Germany|Germany|Germany', 11, 'Computer Graphics|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Models, Molecular|Natural Language Processing|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth367', '15217820', 'Protein Topology Graph Library (PTGL) is a database application for the representation and retrieval of protein topologies. Protein topologies are based on a graph-theoretical protein model at secondary structure level. Different views on protein topology are given by four linear notations for their characterization. Protein topologies can be derived at different description levels considering alpha- and beta-structures. The on-line search tool is based on an object-relational database and provides a query browser for data interrogation by string patterns, keyword queries and sequence similarity. Protein topologies are represented both as schematic diagrams and as three-dimensional images.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71454, 2004, 'bio', 'POINT: a database for the prediction of protein-protein interactions based on the orthologous interactome', 'Huang, Tao-Wei|Tien, An-Chi|Huang, Wen-Shien|Lee, Yuan-Chii G|Peng, Chin-Lin|Tseng, Huei-Hun|Kao, Cheng-Yan|Huang, Chi-Ying F', 'Division of Molecular and Genomic Medicine, National Health Research Institutes, Taipei 115, Taiwan, Republic of China.|Division of Molecular and Genomic Medicine, National Health Research Institutes, Taipei 115, Taiwan, Republic of China.|Division of Molecular and Genomic Medicine, National Health Research Institutes, Taipei 115, Taiwan, Republic of China.|Division of Molecular and Genomic Medicine, National Health Research Institutes, Taipei 115, Taiwan, Republic of China.|Division of Molecular and Genomic Medicine, National Health Research Institutes, Taipei 115, Taiwan, Republic of China.|Division of Molecular and Genomic Medicine, National Health Research Institutes, Taipei 115, Taiwan, Republic of China.|Division of Molecular and Genomic Medicine, National Health Research Institutes, Taipei 115, Taiwan, Republic of China.|Division of Molecular and Genomic Medicine, National Health Research Institutes, Taipei 115, Taiwan, Republic of China.', 'China|China|China|China|China|China|China|China', 87, 'Animals|Database Management Systems|Databases, Protein|Drosophila Proteins|Evolution, Molecular|Humans|Information Storage and Retrieval|Internet|Mice|Protein Interaction Mapping|Proteome|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Signal Transduction|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth366', '15217821', 'One possible path towards understanding the biological function of a target protein is through the discovery of how it interfaces within protein-protein interaction networks. The goal of this study was to create a virtual protein-protein interaction model using the concepts of orthologous conservation (or interologs) to elucidate the interacting networks of a particular target protein. POINT (the prediction of interactome database) is a functional database for the prediction of the human protein-protein interactome based on available orthologous interactome datasets. POINT integrates several publicly accessible databases, with emphasis placed on the extraction of a large quantity of mouse, fruit fly, worm and yeast protein-protein interactions datasets from the Database of Interacting Proteins (DIP), followed by conversion of them into a predicted human interactome. In addition, protein-protein interactions require both temporal synchronicity and precise spatial proximity. POINT therefore also incorporates correlated mRNA expression clusters obtained from cell cycle microarray databases and subcellular localization from Gene Ontology to further pinpoint the likelihood of biological relevance of each predicted interacting sets of protein partners.'),
(71455, 2005, 'bio', 'Voro3D: 3D Voronoi tessellations applied to protein structures', 'Dupuis, Franck|Sadoc, Jean-François|Jullien, Rémi|Angelov, Borislav|Mornon, Jean-Paul', 'Laboratoire de Minéralogie Cristallographie Paris, CNRS UMR 7590 Universités Paris 6 et 7, case 115, 4 Place Jussieu, 75252 Paris, France. franck.dupuis@sanofi-aventis.com|Laboratoire de Minéralogie Cristallographie Paris, CNRS UMR 7590 Universités Paris 6 et 7, case 115, 4 Place Jussieu, 75252 Paris, France. franck.dupuis@sanofi-aventis.com|Laboratoire de Minéralogie Cristallographie Paris, CNRS UMR 7590 Universités Paris 6 et 7, case 115, 4 Place Jussieu, 75252 Paris, France. franck.dupuis@sanofi-aventis.com|Laboratoire de Minéralogie Cristallographie Paris, CNRS UMR 7590 Universités Paris 6 et 7, case 115, 4 Place Jussieu, 75252 Paris, France. franck.dupuis@sanofi-aventis.com|Laboratoire de Minéralogie Cristallographie Paris, CNRS UMR 7590 Universités Paris 6 et 7, case 115, 4 Place Jussieu, 75252 Paris, France. franck.dupuis@sanofi-aventis.com', 'France|France|France|France|France', 31, 'Algorithms|Amino Acid Sequence|Computer Graphics|Computer Simulation|Imaging, Three-Dimensional|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Software|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth365', '15217822', 'Voro3D is an original easy-to-use tool, which provides a brand new point of view on protein structures through the three-dimensional (3D) Voronoi tessellations. To construct the Voronoi cells associated with each amino acid by a number of different tessellation methods, Voro3D uses a protein structure file in the PDB format as an input. After calculation, different structural properties of interest like secondary structures assignment, environment accessibility and exact contact matrices can be derived without any geometrical cut-off. Voro3D provides also a visualization of these tessellations superimposed on the associated protein structure, from which it is possible to model a polygonal protein surface using a model solvent or to quantify, for instance, the contact areas between a protein and a ligand.'),
(71456, 2004, 'bio', 'SCA db: spinocerebellar ataxia candidate gene database', 'Liu, Y-F|Yang, U-C', 'Institute of Biochemistry, National Yang-Ming University, No. 155, Section 2, Li-Noun Street, Taipei, Taiwan 11221, Republic of China.|Institute of Biochemistry, National Yang-Ming University, No. 155, Section 2, Li-Noun Street, Taipei, Taiwan 11221, Republic of China.', 'China|China', 3, 'Database Management Systems|Databases, Genetic|Documentation|Gene Expression Profiling|Genetic Testing|Humans|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Software|Spinocerebellar Ataxias|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth305', '15217823', 'The positional candidate gene approach accelerates the discovery of genes involved in disease. However, the properties of such disease genes are very diverse and the sample size of known disease genes is too small and does not warrant success by the use of a machine-learning approach. A user-defined scoring system may thus help to determine the priority of candidate genes. Spinocerebellar ataxia (SCA) is a good model to test this approach because most SCA subtypes are caused by an expansion of short tandem repeats (STRs). The SCA db is a candidate gene database for SCA, which collected 3185 genes for 17 types of SCA. Those SCA subtypes that have known disease genes can be used as positive controls to optimize the parameters. The users may browse the candidate genes of a given SCA subtype by using the default parameters. The known disease genes were found to be the top three candidates using the default parameters. Alternatively, the users may score the candidate genes by changing the weight or the scores on the basis of their own working hypothesis.'),
(71457, 2004, 'bio', 'Sample classification from protein mass spectrometry, by peak probability contrasts', 'Tibshirani, Robert|Hastie, Trevor|Narasimhan, Balasubramanian|Soltys, Scott|Shi, Gongyi|Koong, Albert|Le, Quynh-Thu', 'Department of Health, Research and Policy, Stanford University, CA 94305, USA. tibs@stanford.edu|Department of Health, Research and Policy, Stanford University, CA 94305, USA. tibs@stanford.edu|Department of Health, Research and Policy, Stanford University, CA 94305, USA. tibs@stanford.edu|Department of Health, Research and Policy, Stanford University, CA 94305, USA. tibs@stanford.edu|Department of Health, Research and Policy, Stanford University, CA 94305, USA. tibs@stanford.edu|Department of Health, Research and Policy, Stanford University, CA 94305, USA. tibs@stanford.edu|Department of Health, Research and Policy, Stanford University, CA 94305, USA. tibs@stanford.edu', 'United States|United States|United States|United States|United States|United States|United States', 163, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Cluster Analysis|Diagnosis, Computer-Assisted|Female|Humans|Models, Biological|Models, Statistical|Neoplasm Proteins|Ovarian Neoplasms|Reproducibility of Results|Sensitivity and Specificity|Spectrometry, Mass, Electrospray Ionization|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Clinical Trial', '10.1093/bioinformatics/bth357', '15226172', 'Early cancer detection has always been a major research focus in solid tumor oncology. Early tumor detection can theoretically result in lower stage tumors, more treatable diseases and ultimately higher cure rates with less treatment-related morbidities. Protein mass spectrometry is a potentially powerful tool for early cancer detection. We propose a novel method for sample classification from protein mass spectrometry data. When applied to spectra from both diseased and healthy patients, the peak probability contrast technique provides a list of all common peaks among the spectra, their statistical significance and their relative importance in discriminating between the two groups. We illustrate the method on matrix-assisted laser desorption and ionization mass spectrometry data from a study of ovarian cancers.'),
(71458, 2004, 'bio', 'A statistical method for identifying differential gene-gene co-expression patterns', 'Lai, Yinglei|Wu, Baolin|Chen, Liang|Zhao, Hongyu', 'Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USA.|Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USA.|Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USA.|Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USA.', 'United States|United States|United States|United States', 103, 'Algorithms|Biomarkers, Tumor|Diagnosis, Computer-Assisted|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Male|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Prostatic Neoplasms|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bth379', '15231528', 'To understand cancer etiology, it is important to explore molecular changes in cellular processes from normal state to cancerous state. Because genes interact with each other during cellular processes, carcinogenesis related genes may form differential co-expression patterns with other genes in different cell states. In this study, we develop a statistical method for identifying differential gene-gene co-expression patterns in different cell states.'),
(71459, 2004, 'bio', 'Differences in gene expression between B-cell chronic lymphocytic leukemia and normal B cells: a meta-analysis of three microarray studies', 'Wang, J|Coombes, K R|Highsmith, W E|Keating, M J|Abruzzo, L V', 'Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA.|Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA.|Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA.|Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA.|Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA.', 'United States|United States|United States|United States|United States', 94, 'Algorithms|Biomarkers, Tumor|Gene Expression Profiling|Genetic Variation|Humans|Leukemia, Lymphocytic, Chronic, B-Cell|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Reference Values|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth381', '15231529', 'A major focus of current cancer research is to identify genes that can be used as markers for prognosis and diagnosis, and as targets for therapy. Microarray technology has been applied extensively for this purpose, even though it has been reported that the agreement between microarray platforms is poor. A critical question is: how can we best combine the measurements of matched genes across microarray platforms to develop diagnostic and prognostic tools related to the underlying biology?'),
(71460, 2004, 'bio', 'Prediction of phosphorylation sites using SVMs', 'Kim, Jong Hun|Lee, Juyoung|Oh, Bermseok|Kimm, Kuchan|Koh, Insong', 'National Genome Research Institute, 5 Nokbun-Dong, Eunpyung-Gu, Seoul, 122-701 Korea. jh7521@ngri.re.kr|National Genome Research Institute, 5 Nokbun-Dong, Eunpyung-Gu, Seoul, 122-701 Korea. jh7521@ngri.re.kr|National Genome Research Institute, 5 Nokbun-Dong, Eunpyung-Gu, Seoul, 122-701 Korea. jh7521@ngri.re.kr|National Genome Research Institute, 5 Nokbun-Dong, Eunpyung-Gu, Seoul, 122-701 Korea. jh7521@ngri.re.kr|National Genome Research Institute, 5 Nokbun-Dong, Eunpyung-Gu, Seoul, 122-701 Korea. jh7521@ngri.re.kr', '-|-|-|-|-', 202, 'Algorithms|Artificial Intelligence|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Phosphorylation|Phosphotransferases|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth382', '15231530', 'Phosphorylation is involved in diverse signal transduction pathways. By predicting phosphorylation sites and their kinases from primary protein sequences, we can obtain much valuable information that can form the basis for further research. Using support vector machines, we attempted to predict phosphorylation sites and the type of kinase that acts at each site.'),
(71461, 2004, 'bio', 'Systematic benchmarking of microarray data classification: assessing the role of non-linearity and dimensionality reduction', 'Pochet, Nathalie|De Smet, Frank|Suykens, Johan A K|De Moor, Bart L R', 'ESAT-SCD (SISTA), K.U. Leuven, Kasteelpark Arenberg 10, 3001 Leuven-Heverlee, Belgium. Nathalie.Pochet@esat.kuleuven.ac.be|ESAT-SCD (SISTA), K.U. Leuven, Kasteelpark Arenberg 10, 3001 Leuven-Heverlee, Belgium. Nathalie.Pochet@esat.kuleuven.ac.be|ESAT-SCD (SISTA), K.U. Leuven, Kasteelpark Arenberg 10, 3001 Leuven-Heverlee, Belgium. Nathalie.Pochet@esat.kuleuven.ac.be|ESAT-SCD (SISTA), K.U. Leuven, Kasteelpark Arenberg 10, 3001 Leuven-Heverlee, Belgium. Nathalie.Pochet@esat.kuleuven.ac.be', 'Belgium|Belgium|Belgium|Belgium', 171, 'Algorithms|Benchmarking|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Linear Models|Models, Genetic|Nonlinear Dynamics|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Software|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/bth383', '15231531', 'Microarrays are capable of determining the expression levels of thousands of genes simultaneously. In combination with classification methods, this technology can be useful to support clinical management decisions for individual patients, e.g. in oncology. The aim of this paper is to systematically benchmark the role of non-linear versus linear techniques and dimensionality reduction methods.'),
(71462, 2004, 'bio', 'Normalization of microarray data using a spatial mixed model analysis which includes splines', 'Baird, David|Johnstone, Peter|Wilson, Theresa', 'AgResearch, Lincoln, New Zealand. david.baird@agresearch.co.nz|AgResearch, Lincoln, New Zealand. david.baird@agresearch.co.nz|AgResearch, Lincoln, New Zealand. david.baird@agresearch.co.nz', 'New Zealand|New Zealand|New Zealand', 37, 'Algorithms|Artifacts|Benchmarking|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Genetic Variation|Models, Genetic|Models, Statistical|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Software|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/bth384', '15231532', 'Microarray experiments with thousands of genes on a slide and multiple slides used in any experimental set represent a large body of data with many sources of variation. The identification of such sources of variation within microarray experimental sets is critical for correct deciphering of desired gene expression differences.'),
(71463, 2004, 'bio', 'Bioinformatics leads charge by publishing more Internet addresses in abstracts than any other journal', 'Schilling, Lisa M|Wren, Jonathan D|Dellavalle, Robert P', 'AgResearch, Lincoln, New Zealand. david.baird@agresearch.co.nz|AgResearch, Lincoln, New Zealand. david.baird@agresearch.co.nz|AgResearch, Lincoln, New Zealand. david.baird@agresearch.co.nz', 'New Zealand|New Zealand|New Zealand', 10, 'Abstracting and Indexing as Topic|Computational Biology|Databases, Bibliographic|Documentation|Information Storage and Retrieval|Internet|Periodicals as Topic|Publishing', 'Letter', '10.1093/bioinformatics/bth385', '15231533', '-'),
(71464, 2004, 'bio', 'BioRAT: extracting biological information from full-length papers', 'Corney, David P A|Buxton, Bernard F|Langdon, William B|Jones, David T', 'Bioinformatics Unit, Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK. d.corney@cs.ucl.ac.uk|Bioinformatics Unit, Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK. d.corney@cs.ucl.ac.uk|Bioinformatics Unit, Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK. d.corney@cs.ucl.ac.uk|Bioinformatics Unit, Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK. d.corney@cs.ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Bibliometrics|Biology|Database Management Systems|Databases, Bibliographic|Documentation|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Software|User-Computer Interface|Vocabulary, Controlled', 'Comparative Study', '10.1093/bioinformatics/bth386', '15231534', 'Converting the vast quantity of free-format text found in journals into a concise, structured format makes the researchers quest for information easier. Recently, several information extraction systems have been developed that attempt to simplify the retrieval and analysis of biological and medical data. Most of this work has used the abstract alone, owing to the convenience of access and the quality of data. Abstracts are generally available through central collections with easy direct access (e.g. PubMed). The full-text papers contain more information, but are distributed across many locations (e.g. publishers web sites, journal web sites and local repositories), making access more difficult. In this paper, we present BioRAT, a new information extraction (IE) tool, specifically designed to perform biomedical IE, and which is able to locate and analyse both abstracts and full-length papers. BioRAT is a Biological Research Assistant for Text mining, and incorporates a document search ability with domain-specific IE.'),
(71465, 2004, 'bio', 'Computational prediction of RNA editing sites', 'Bundschuh, R', 'Department of Physics, The Ohio State University, 174 West 18th Avenue, Columbus, OH 43210-1106, USA. bundschuh@mps.ohio-state.edu', 'United States', 17, 'Algorithms|Animals|Base Sequence|Conserved Sequence|Mitochondria|Molecular Sequence Data|Numerical Analysis, Computer-Assisted|Physarum polycephalum|RNA Editing|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth387', '15231535', 'Some organisms edit their messenger RNA resulting in differences between the genomic sequence for a gene and the corresponding messenger RNA sequence. This difference complicates experimental and computational attempts to find and study genes in organisms with RNA editing even if the full genomic sequence is known. Nevertheless, knowledge of these editing sites is crucial for understanding the editing machinery of these organisms.'),
(71466, 2005, 'bio', 'HAPLORE: a program for haplotype reconstruction in general pedigrees without recombination', 'Zhang, Kui|Sun, Fengzhu|Zhao, Hongyu', 'Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, AL 35294, USA.|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, AL 35294, USA.|Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, AL 35294, USA.', 'United States|United States|United States', 69, 'Algorithms|Chromosome Mapping|Computer Simulation|Haplotypes|Linkage Disequilibrium|Models, Genetic|Pedigree|Recombination, Genetic|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth388', '15231536', 'Haplotype reconstruction is an essential step in genetic linkage and association studies. Although many methods have been developed to estimate haplotype frequencies and reconstruct haplotypes for a sample of unrelated individuals, haplotype reconstruction in large pedigrees with a large number of genetic markers remains a challenging problem.'),
(71467, 2004, 'bio', 'Proceedings from the German Conference on Bioinformatics 2003 (GCB03) Munich, Germany, October 12-14, 2003', '-', '-', '-', 0, 'Computational Biology', 'Congress', '10.1093/bioinformatics/bth353', '15231537', '-'),
(71468, 2004, 'bio', 'Regional and time-resolved mutation patterns of the human genome', 'Arndt, Peter F|Hwa, Terence', 'Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. peter.arndt@molgen.mpg.de|Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. peter.arndt@molgen.mpg.de', 'Germany|Germany', 0, 'Algorithms|Chromosome Mapping|CpG Islands|DNA Mutational Analysis|Evolution, Molecular|Gene Deletion|Gene Frequency|Genome, Human|Humans|Mutagenesis, Insertional|Phylogeny|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bth105', '15231538', 'Substantial regional variations of substitutional processes have recently been reported from human/mouse comparisons. However, several features including the C + G dependence and the CpG-based transition effect remain obscure.'),
(71469, 2004, 'bio', 'Using convex hulls to extract interaction interfaces from known structures', 'Dafas, Panos|Bolser, Dan|Gomoluch, Jacek|Park, Jong|Schroeder, Michael', 'Department of Computing, City University, London, EC1V 0HB, UK. panos@alumni.doc.ic.ac.uk|Department of Computing, City University, London, EC1V 0HB, UK. panos@alumni.doc.ic.ac.uk|Department of Computing, City University, London, EC1V 0HB, UK. panos@alumni.doc.ic.ac.uk|Department of Computing, City University, London, EC1V 0HB, UK. panos@alumni.doc.ic.ac.uk|Department of Computing, City University, London, EC1V 0HB, UK. panos@alumni.doc.ic.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 18, 'Algorithms|Binding Sites|Databases, Protein|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bth106', '15231539', 'Protein interactions provide an important context for the understanding of function. Experimental approaches have been complemented with computational ones, such as PSIMAP, which computes domain-domain interactions for all multi-domain and multi-chain proteins in the Protein Data Bank (PDB). PSIMAP has been used to determine that superfamilies occurring in many species have many interaction partners, to show examples of convergent evolution through shared interaction partners and to uncover complexes in the interaction map. To determine an interaction, the original PSIMAP algorithm checks all residue pairs of any domain pair defined by classification systems such as SCOP. The computation takes several days for the PDB. The computation of PSIMAP has two shortcomings: first, the original PSIMAP algorithm considers only interactions of residue pairs rather than atom pairs losing information for detailed analysis of contact patterns. At the atomic level the original algorithm would take months. Second, with the superlinear growth of PDB, PSIMAP is not sustainable.'),
(71470, 2004, 'bio', 'Threshold extraction in metabolite concentration data', 'Flöter, A|Nicolas, J|Schaub, T|Selbig, J', 'University of Potsdam, Institute for Computer Science, August-Bebel-Str. 89/Hs. 4, 14482 Potsdam, Germany. floeter@cs.uni-postdam.de|University of Potsdam, Institute for Computer Science, August-Bebel-Str. 89/Hs. 4, 14482 Potsdam, Germany. floeter@cs.uni-postdam.de|University of Potsdam, Institute for Computer Science, August-Bebel-Str. 89/Hs. 4, 14482 Potsdam, Germany. floeter@cs.uni-postdam.de|University of Potsdam, Institute for Computer Science, August-Bebel-Str. 89/Hs. 4, 14482 Potsdam, Germany. floeter@cs.uni-postdam.de', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Computer Simulation|Differential Threshold|Energy Metabolism|Gene Expression Profiling|Gene Expression Regulation, Plant|Homeostasis|Models, Biological|Plant Proteins|Signal Transduction|Solanum tuberosum', 'Evaluation Studies', '10.1093/bioinformatics/bth107', '15231540', 'Continued development of analytical techniques based on gas chromatography and mass spectrometry now facilitates the generation of larger sets of metabolite concentration data. An important step towards the understanding of metabolite dynamics is the recognition of stable states where metabolite concentrations exhibit a simple behaviour. Such states can be characterized through the identification of significant thresholds in the concentrations. But general techniques for finding discretization thresholds in continuous data prove to be practically insufficient for detecting states due to the weak conditional dependences in concentration data.'),
(71471, 2004, 'bio', 'Conserved RNA secondary structures in viral genomes: a survey', 'Hofacker, I L|Stadler, P F|Stocsits, R R', 'Institut für Theoretische Chemie und Molekulare Strukturbiologie, Universität Wien, Währingerstrasse 17, Vienna, A-1090, Austria. ivo@tbi.univie.ac.at|Institut für Theoretische Chemie und Molekulare Strukturbiologie, Universität Wien, Währingerstrasse 17, Vienna, A-1090, Austria. ivo@tbi.univie.ac.at|Institut für Theoretische Chemie und Molekulare Strukturbiologie, Universität Wien, Währingerstrasse 17, Vienna, A-1090, Austria. ivo@tbi.univie.ac.at', 'Austria|Austria|Austria', 35, 'Algorithms|Computer Simulation|Conserved Sequence|Databases, Genetic|Genome, Viral|Models, Molecular|Nucleic Acid Conformation|RNA, Viral|Retroviridae|Sequence Alignment|Sequence Analysis, RNA', 'Comparative Study', '10.1093/bioinformatics/bth108', '15231541', 'The genomes of RNA viruses often carry conserved RNA structures that perform vital functions during the life cycle of the virus. Such structures can be detected using a combination of structure prediction and co-variation analysis. Here we present results from pilot studies on a variety of viral families performed during bioinformatics computer lab courses in past years.'),
(71472, 2004, 'bio', 'Gene expression analysis on biochemical networks using the Potts spin model', 'König, Rainer|Eils, Roland', 'Division Intelligent Bioinformatics Systems, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. r.koenig@dkfz.de|Division Intelligent Bioinformatics Systems, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. r.koenig@dkfz.de', 'Germany|Germany', 0, 'Algorithms|Cluster Analysis|Computer Simulation|Energy Metabolism|Escherichia coli|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Models, Biological|Oligonucleotide Array Sequence Analysis|Signal Transduction|Software|Tryptophan', 'Evaluation Studies', '10.1093/bioinformatics/bth109', '15231542', 'Microarray technology allows us to profile the expression of a large subset or all genes of a cell. Biochemical research over the last three decades has elucidated an increasingly complete image of the metabolic architecture. For less complex organisms, such as Escherichia coli, the biochemical network has been described in much detail. Here, we investigate the clustering of such networks by applying gene expression data that define edge lengths in the network.'),
(71473, 2004, 'bio', 'Bifurcation analysis of the regulatory modules of the mammalian G1/S transition', 'Swat, Maciej|Kel, Alexander|Herzel, Hanspeter', 'Institute for Theoretical Biology, Humboldt University Berlin, Invalidenstrasse 43, Berlin, D-10115, Germany. swat@itb.biologie.hu-berlin.de|Institute for Theoretical Biology, Humboldt University Berlin, Invalidenstrasse 43, Berlin, D-10115, Germany. swat@itb.biologie.hu-berlin.de|Institute for Theoretical Biology, Humboldt University Berlin, Invalidenstrasse 43, Berlin, D-10115, Germany. swat@itb.biologie.hu-berlin.de', 'Germany|Germany|Germany', 113, 'Animals|Cell Cycle|Cell Cycle Proteins|Computer Simulation|DNA-Binding Proteins|E2F Transcription Factors|E2F1 Transcription Factor|Feedback|G1 Phase|Gene Expression Regulation|Genes, Regulator|Humans|Models, Biological|S Phase|Saccharomyces|Signal Transduction|Species Specificity|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth110', '15231543', 'Mathematical models of the cell cycle can contribute to an understanding of its basic mechanisms. Modern simulation tools make the analysis of key components and their interactions very effective. This paper focuses on the role of small modules and feedbacks in the gene-protein network governing the G1/S transition in mammalian cells. Mutations in this network may lead to uncontrolled cell proliferation. Bifurcation analysis helps to identify the key components of this extremely complex interaction network.'),
(71474, 2004, 'bio', 'Recognition of multiple patterns in unaligned sets of sequences: comparison of kernel clustering method with other methods', 'Kel, A|Tikunov, Y|Voss, N|Wingender, E', 'Institute of Cytology and Genetics SB RAN, Lavrentyev pr., 10, 630090, Novosibirsk, Russia. ake@biobase.de|Institute of Cytology and Genetics SB RAN, Lavrentyev pr., 10, 630090, Novosibirsk, Russia. ake@biobase.de|Institute of Cytology and Genetics SB RAN, Lavrentyev pr., 10, 630090, Novosibirsk, Russia. ake@biobase.de|Institute of Cytology and Genetics SB RAN, Lavrentyev pr., 10, 630090, Novosibirsk, Russia. ake@biobase.de', '-|-|-|-', 4, 'Algorithms|Base Sequence|Molecular Sequence Data|Pattern Recognition, Automated|Promoter Regions, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth111', '15231544', 'Transcription factor binding sites often differ significantly in their primary sequence and can hardly be aligned. Often one set of sites can contain several subsets of sequences that follow not just one but several different patterns. There is a need for sensitive methods to reveal multiple patterns in unaligned sets of sequences.'),
(71475, 2004, 'bio', 'New methods for joint analysis of biological networks and expression data', 'Sohler, Florian|Hanisch, Daniel|Zimmer, Ralf', 'Institut für Informatik, Ludwig-Maximilians-Universität München, Amalienstrasse 17, 80333 München, Germany. florian.sohler@ifi.lmu.edu|Institut für Informatik, Ludwig-Maximilians-Universität München, Amalienstrasse 17, 80333 München, Germany. florian.sohler@ifi.lmu.edu|Institut für Informatik, Ludwig-Maximilians-Universität München, Amalienstrasse 17, 80333 München, Germany. florian.sohler@ifi.lmu.edu', 'Germany|Germany|Germany', 0, 'Algorithms|Computer Graphics|Computer Simulation|Database Management Systems|Databases, Factual|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Models, Biological|Signal Transduction|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth112', '15231545', 'Biological networks, such as protein interaction, regulatory or metabolic networks, derived from public databases, biological experiments or text mining can be useful for the analysis of high-throughput experimental data. We present two algorithms embedded in the ToPNet application that show promising performance in analyzing expression data in the context of such networks. First, the Significant Area Search algorithm detects subnetworks consisting of significantly regulated genes. These subnetworks often provide hints on which biological processes are affected in the measured conditions. Second, Pathway Queries allow detection of networks including molecules that are not necessarily significantly regulated, such as transcription factors or signaling proteins. Moreover, using these queries, the user can formulate biological hypotheses and check their validity with respect to experimental data. All resulting networks and pathways can be explored further using the interactive analysis tools provided by ToPNet program.'),
(71476, 2004, 'bio', 'Efficient similarity search in protein structure databases by k-clique hashing', 'Weskamp, Nils|Kuhn, Daniel|Hüllermeier, Eyke|Klebe, Gerhard', 'Department of Mathematics and Computer Science, University of Marburg, Hans-Meerwein-Strasse, 35032 Marburg, Germany.|Department of Mathematics and Computer Science, University of Marburg, Hans-Meerwein-Strasse, 35032 Marburg, Germany.|Department of Mathematics and Computer Science, University of Marburg, Hans-Meerwein-Strasse, 35032 Marburg, Germany.|Department of Mathematics and Computer Science, University of Marburg, Hans-Meerwein-Strasse, 35032 Marburg, Germany.', 'Germany|Germany|Germany|Germany', 43, 'Algorithms|Binding Sites|Data Compression|Databases, Protein|Pattern Recognition, Automated|Protein Binding|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bth113', '15231546', 'Graph-based clique-detection techniques are widely used for the recognition of common substructures in proteins. They permit the detection of resemblances that are independent of sequence or fold homologies and are also able to handle conformational flexibility. Their high computational complexity is often a limiting factor and prevents a detailed and fine-grained modeling of the protein structure.'),
(71477, 2004, 'bio', 'Comparative analysis of protein unfoldedness in human housekeeping and non-housekeeping proteins', 'Pandey, Neeraj|Ganapathi, Mythily|Kumar, Kaushal|Dasgupta, Dipayan|Das Sutar, Sushanta Kumar|Dash, Debasis', 'Institute of Genomics and Integrative Biology (CSIR), Delhi University Campus, Mall Road, Delhi 110 007, India.|Institute of Genomics and Integrative Biology (CSIR), Delhi University Campus, Mall Road, Delhi 110 007, India.|Institute of Genomics and Integrative Biology (CSIR), Delhi University Campus, Mall Road, Delhi 110 007, India.|Institute of Genomics and Integrative Biology (CSIR), Delhi University Campus, Mall Road, Delhi 110 007, India.|Institute of Genomics and Integrative Biology (CSIR), Delhi University Campus, Mall Road, Delhi 110 007, India.|Institute of Genomics and Integrative Biology (CSIR), Delhi University Campus, Mall Road, Delhi 110 007, India.', 'India|India|India|India|India|India', 16, 'Algorithms|Animals|Caenorhabditis elegans|Conserved Sequence|Drosophila melanogaster|Evolution, Molecular|Humans|Mice|Protein Conformation|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology|Species Specificity|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth344', '15238363', 'Absence of any regular structure is increasingly being observed in structural studies of proteins. These disordered regions or random coils, which have been observed under physiological conditions, are indicators of protein plasticity. The wide variety of interactions possible due to the flexibility of these natively disordered regions confers functional advantage to the protein and the organism in general. This concept is underscored by the increasing proportion of intrinsically unstructured proteins seen with the ascension in the complexity of the organisms. The natively unfolded/disordered state of the protein can be predicted utilizing Uverskys or Dunkers algorithm. We utilized Uverskys prediction scheme and based on the unique position of a protein in the charge-hydrophobicity plot, a derived net score was used to predict the overall disorder of the human housekeeping and non-housekeeping proteins. Substantial numbers of proteins in both the classes were predicted to be unfolded. However, comparative genomic analysis of predicted unfolded Homo sapiens proteins with homologues in Caenorhabditis elegans, Drosophila melanogaster and Mus musculus revealed significant increase in unfoldedness in non-housekeeping proteins in comparison with housekeeping proteins. Our analysis in the evolutionary context suggests addition or substitution of amino acid residues which favour unfoldedness in non-housekeeping proteins compared to housekeeping proteins.'),
(71478, 2004, 'bio', 'Conserved network motifs allow protein-protein interaction prediction', 'Albert, István|Albert, Réka', 'The Huck Institutes for the Life Sciences, Pennsylvania State University, PA 16802, USA. iua1@psu.edu <iua1@psu.edu>|The Huck Institutes for the Life Sciences, Pennsylvania State University, PA 16802, USA. iua1@psu.edu <iua1@psu.edu>', 'United States|United States', 125, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Binding Sites|Conserved Sequence|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bth402', '15247093', 'High-throughput protein interaction detection methods are strongly affected by false positive and false negative results. Focused experiments are needed to complement the large-scale methods by validating previously detected interactions but it is often difficult to decide which proteins to probe as interaction partners. Developing reliable computational methods assisting this decision process is a pressing need in bioinformatics.'),
(71479, 2004, 'bio', 'DNMAD: web-based diagnosis and normalization for microarray data', 'Vaquerizas, Juan M|Dopazo, Joaquín|Díaz-Uriarte, Ramón', 'Bioinformatics Unit, CNIO, Spanish National Cancer Centre, Melchor Fernández Almagro 3, 28029 Madrid, Spain.|Bioinformatics Unit, CNIO, Spanish National Cancer Centre, Melchor Fernández Almagro 3, 28029 Madrid, Spain.|Bioinformatics Unit, CNIO, Spanish National Cancer Centre, Melchor Fernández Almagro 3, 28029 Madrid, Spain.', 'Spain|Spain|Spain', 51, 'Algorithms|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/bth401', '15247094', 'We present a web server for Diagnosis and Normalization of MicroArray Data (DNMAD). DNMAD includes several common data transformations such as spatial and global robust local regression or multiple slide normalization, and allows for detecting several kinds of errors that result from the manipulation and the image analysis of the arrays. This tool offers a user-friendly interface, and is completely integrated within the Gene Expression Pattern Analysis Suite (GEPAS).'),
(71480, 2004, 'bio', 'VisRD--visual recombination detection', 'Forslund, Kristoffer|Huson, Daniel H|Moulton, Vincent', 'The Linnaeus Centre for Bioinformatics, BMC, Box 598, Uppsala 751 24, Sweden. krfo6395@student.uu.se <krfo6395@student.uu.se>|The Linnaeus Centre for Bioinformatics, BMC, Box 598, Uppsala 751 24, Sweden. krfo6395@student.uu.se <krfo6395@student.uu.se>|The Linnaeus Centre for Bioinformatics, BMC, Box 598, Uppsala 751 24, Sweden. krfo6395@student.uu.se <krfo6395@student.uu.se>', 'Sweden|Sweden|Sweden', 5, 'Algorithms|Computer Graphics|Recombination, Genetic|Sequence Alignment|Sequence Analysis|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth400', '15247095', 'VisRD, a program for visual recombination detection in a sequence alignment is presented. VisRD is written in Java and is designed to complement the multi-purpose phylogenetic software package SplitsTree4.'),
(71481, 2004, 'bio', 'PLPMDB: pyridoxal-5-phosphate dependent enzymes mutants database', 'Di Giovine, Paolo', 'Dipartimento di Scienze Biochimiche A. Rossi Fanelli, Universita degli Studi di Roma La Sapienza, Piazzale Aldo Moro, 5, 00185 Rome, Italy. paolo.digiovine@studiofmp.com <paolo.digiovine@studiofmp.com>', 'Italy', 4, 'Database Management Systems|Databases, Protein|Enzymes|Information Dissemination|Information Storage and Retrieval|Internet|Mutation|Pyridoxal Phosphate|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth399', '15247096', 'The searchable mutant database PLPMDB has been developed to provide rapid and simple access to relevant mutant information on pyridoxal-5-phosphate dependent enzymes. All data have been extracted from publications and publicly available databases, then organized in a relational database to enable searching via a web-based search form. The current version of PLPMDB contains 688 mutants described in 220 research papers. The database is a useful tool for planning mutant experiments and for interpretation of information from such experiments.'),
(71482, 2004, 'bio', 'CSBDB: a comprehensive systems-biology database', 'Steinhauser, Dirk|Usadel, Björn|Luedemann, Alexander|Thimm, Oliver|Kopka, Joachim', 'Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany. Steinhauser@mpimp-golm.mpg.de <Steinhauser@mpimp-golm.mpg.de>|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany. Steinhauser@mpimp-golm.mpg.de <Steinhauser@mpimp-golm.mpg.de>|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany. Steinhauser@mpimp-golm.mpg.de <Steinhauser@mpimp-golm.mpg.de>|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany. Steinhauser@mpimp-golm.mpg.de <Steinhauser@mpimp-golm.mpg.de>|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany. Steinhauser@mpimp-golm.mpg.de <Steinhauser@mpimp-golm.mpg.de>', 'Germany|Germany|Germany|Germany|Germany', 137, 'Database Management Systems|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Sequence Analysis, Protein|Systems Biology|Systems Integration|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth398', '15247097', 'The open access comprehensive systems-biology database (CSB.DB) presents the results of bio-statistical analyses on gene expression data in association with additional biochemical and physiological knowledge. The main aim of this database platform is to provide tools that support insight into lifes complexity pyramid with a special focus on the integration of data from transcript and metabolite profiling experiments. The central part of CSB.DB, which we describe in this applications note, is a set of co-response databases that currently focus on the three key model organisms, Escherichia coli, Saccharomyces cerevisiae and Arabidopsis thaliana. CSB.DB gives easy access to the results of large-scale co-response analyses, which are currently based exclusively on the publicly available compendia of transcript profiles. By scanning for the best co-responses among changing transcript levels, CSB.DB allows to infer hypotheses on the functional interaction of genes. These hypotheses are novel and not accessible through analysis of sequence homology. The database enables the search for pairs of genes and larger units of genes, which are under common transcriptional control. In addition, statistical tools are offered to the user, which allow validation and comparison of those co-responses that were discovered by gene queries performed on the currently available set of pre-selectable datasets.'),
(71483, 2004, 'bio', 'DAGchainer: a tool for mining segmental genome duplications and synteny', 'Haas, Brian J|Delcher, Arthur L|Wortman, Jennifer R|Salzberg, Steven L', 'The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA. bhaas@tigr.org <bhaas@tigr.org>|The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA. bhaas@tigr.org <bhaas@tigr.org>|The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA. bhaas@tigr.org <bhaas@tigr.org>|The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA. bhaas@tigr.org <bhaas@tigr.org>', 'United States|United States|United States|United States', 219, 'Algorithms|Arabidopsis|Chromosome Mapping|Conserved Sequence|Gene Duplication|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth397', '15247098', 'Given the positions of protein-coding genes along genomic sequence and probability values for protein alignments between genes, DAGchainer identifies chains of gene pairs sharing conserved order between genomic regions, by identifying paths through a directed acyclic graph (DAG). These chains of collinear gene pairs can represent segmentally duplicated regions and genes within a single genome or syntenic regions between related genomes. Automated mining of the Arabidopsis genome for segmental duplications illustrates the use of DAGchainer.'),
(71484, 2004, 'bio', 'SARGE: a tool for creation of putative genetic networks', 'Shaw, O J|Harwood, C|Steggles, L J|Wipat, A', 'School of Computing Science, University of Newcastle upon Tyne, Newcastle upon Tyne NE1 7RU, UK.|School of Computing Science, University of Newcastle upon Tyne, Newcastle upon Tyne NE1 7RU, UK.|School of Computing Science, University of Newcastle upon Tyne, Newcastle upon Tyne NE1 7RU, UK.|School of Computing Science, University of Newcastle upon Tyne, Newcastle upon Tyne NE1 7RU, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 9, 'Algorithms|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth395', '15247099', 'SARGE is a tool for creating, visualizing and manipulating a putative genetic network from time series microarray data. The tool assigns potential edges through time-lagged correlation, incorporates a clustering mechanism, an interactive visual graph representation and employs simulated annealing for network optimization.'),
(71485, 2004, 'bio', 'A computational search for box C/D snoRNA genes in the Drosophila melanogaster genome', 'Accardo, M C|Giordano, E|Riccardo, S|Digilio, F A|Iazzetti, G|Calogero, R A|Furia, M', 'Department of Genetics, General and Molecular Biology, University of Naples Federico II, via Mezzocannone 8, 80134 Napoli, Italy.|Department of Genetics, General and Molecular Biology, University of Naples Federico II, via Mezzocannone 8, 80134 Napoli, Italy.|Department of Genetics, General and Molecular Biology, University of Naples Federico II, via Mezzocannone 8, 80134 Napoli, Italy.|Department of Genetics, General and Molecular Biology, University of Naples Federico II, via Mezzocannone 8, 80134 Napoli, Italy.|Department of Genetics, General and Molecular Biology, University of Naples Federico II, via Mezzocannone 8, 80134 Napoli, Italy.|Department of Genetics, General and Molecular Biology, University of Naples Federico II, via Mezzocannone 8, 80134 Napoli, Italy.|Department of Genetics, General and Molecular Biology, University of Naples Federico II, via Mezzocannone 8, 80134 Napoli, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 25, 'Animals|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Drosophila melanogaster|Gene Expression Profiling|Methylation|Molecular Sequence Data|RNA, Small Nucleolar', 'Comparative Study', '10.1093/bioinformatics/bth394', '15247100', 'In eukaryotes, the family of non-coding RNA genes includes a number of genes encoding small nucleolar RNAs (mainly C/D and H/ACA snoRNAs), which act as guides in the maturation or post-transcriptional modifications of target RNA molecules. Since in Drosophila melanogaster (Dm) only few examples of snoRNAs have been identified so far by cDNA libraries screening, integration of the molecular data with in silico identification of these types of genes could throw light on their organization in the Dm genome.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71486, 2004, 'bio', 'DNA structure constraint is probably a fundamental factor inducing CpG deficiency in bacteria', 'Wang, Yong|Leung, Frederick C C', 'Department of Zoology, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.|Department of Zoology, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.', 'China|China', 5, 'Base Sequence|Chromosome Mapping|Computer Simulation|CpG Islands|DNA Mutational Analysis|Genetic Variation|Genome, Bacterial|Markov Chains|Models, Genetic|Models, Statistical|Molecular Sequence Data|Sequence Analysis, DNA|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth393', '15247101', 'It has been speculated that CpG dinucleotide deficiency in genomes is a consequence of DNA methylation. However, this hypothesis does not adequately explain CpG deficiency in bacteria. The hypothesis based on DNA structure constraint as an alternative explanation was therefore examined.'),
(71487, 2004, 'bio', 'MyWEST: my Web Extraction Software Tool for effective mining of annotations from web-based databanks', 'Masseroli, Marco|Stella, Andrea|Meani, Natalia|Alcalay, Myriam|Pinciroli, Francesco', 'Bioengineering Department, Politecnico di Milano, I-20133 Milano, Italy. masseroli@biomed.polimi.it <masseroli@biomed.polimi.it>|Bioengineering Department, Politecnico di Milano, I-20133 Milano, Italy. masseroli@biomed.polimi.it <masseroli@biomed.polimi.it>|Bioengineering Department, Politecnico di Milano, I-20133 Milano, Italy. masseroli@biomed.polimi.it <masseroli@biomed.polimi.it>|Bioengineering Department, Politecnico di Milano, I-20133 Milano, Italy. masseroli@biomed.polimi.it <masseroli@biomed.polimi.it>|Bioengineering Department, Politecnico di Milano, I-20133 Milano, Italy. masseroli@biomed.polimi.it <masseroli@biomed.polimi.it>', 'Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Artificial Intelligence|Database Management Systems|Databases, Genetic|Documentation|Gene Expression Profiling|Information Dissemination|Information Storage and Retrieval|Internet|Natural Language Processing|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth392', '15247102', 'High-throughput technologies create the necessity to mine large amounts of gene annotations from diverse databanks, and to integrate the resulting data. Most databanks can be interrogated only via Web, for a single gene at a time, and query results are generally available only in the HTML format. Although some databanks provide batch retrieval of data via FTP, this requires expertise and resources for locally reimplementing the databank.'),
(71488, 2004, 'bio', 'Effects of pooling mRNA in microarray class comparisons', 'Shih, Joanna H|Michalowska, Aleksandra M|Dobbin, Kevin|Ye, Yumei|Qiu, Ting Hu|Green, Jeffrey E', 'Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA. jshih@mail.nih.gov <jshih@mail.nih.gov>|Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA. jshih@mail.nih.gov <jshih@mail.nih.gov>|Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA. jshih@mail.nih.gov <jshih@mail.nih.gov>|Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA. jshih@mail.nih.gov <jshih@mail.nih.gov>|Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA. jshih@mail.nih.gov <jshih@mail.nih.gov>|Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA. jshih@mail.nih.gov <jshih@mail.nih.gov>', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Gene Expression Profiling|Genetic Variation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|RNA, Messenger|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bth391', '15247103', 'In microarray experiments investigators sometimes wish to pool RNA samples before labeling and hybridization due to insufficient RNA from each individual sample or to reduce the number of arrays for the purpose of saving cost. The basic assumption of pooling is that the expression of an mRNA molecule in the pool is close to the average expression from individual samples. Recently, a method for studying the effect of pooling mRNA on statistical power in detecting differentially expressed genes between classes has been proposed, but the different sources of variation arising in microarray experiments were not distinguished. Another paper recently did take different sources of variation into account, but did not address power and sample size for class comparison. In this paper, we study the implication of pooling in detecting differential gene expression taking into account different sources of variation and check the basic assumption of pooling using data from both the cDNA and Affymetrix GeneChip microarray experiments.'),
(71489, 2004, 'bio', 'Accuracy improvement for identifying translation initiation sites in microbial genomes', 'Zhu, Huai-Qiu|Hu, Gang-Qing|Ouyang, Zheng-Qing|Wang, Jin|She, Zhen-Su', 'State Key Lab for Turbulence and Complex Systems and Center for Theoretical Biology, Peking University, Beijing 100871, China.|State Key Lab for Turbulence and Complex Systems and Center for Theoretical Biology, Peking University, Beijing 100871, China.|State Key Lab for Turbulence and Complex Systems and Center for Theoretical Biology, Peking University, Beijing 100871, China.|State Key Lab for Turbulence and Complex Systems and Center for Theoretical Biology, Peking University, Beijing 100871, China.|State Key Lab for Turbulence and Complex Systems and Center for Theoretical Biology, Peking University, Beijing 100871, China.', 'China|China|China|China|China', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Codon, Initiator|Genome, Bacterial|Models, Genetic|Models, Statistical|Molecular Sequence Data|Protein Biosynthesis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Software|Transcription Initiation Site', 'Comparative Study', '10.1093/bioinformatics/bth390', '15247104', 'At present the computational gene identification methods in microbial genomes have a high prediction accuracy of verified translation termination site (3 end), but a much lower accuracy of the translation initiation site (TIS, 5 end). The latter is important to the analysis and the understanding of the putative protein of a gene and the regulatory machinery of the translation. Improving the accuracy of prediction of TIS is one of the remaining open problems.'),
(71490, 2004, 'bio', 'A model-based optimization framework for the inference on gene regulatory networks from DNA array data', 'Thomas, Reuben|Mehrotra, Sanjay|Papoutsakis, Eleftherios T|Hatzimanikatis, Vassily', 'Department of Industrial Engineering and Management Science, Northwestern University, Evanston, IL 60208-3120, USA.|Department of Industrial Engineering and Management Science, Northwestern University, Evanston, IL 60208-3120, USA.|Department of Industrial Engineering and Management Science, Northwestern University, Evanston, IL 60208-3120, USA.|Department of Industrial Engineering and Management Science, Northwestern University, Evanston, IL 60208-3120, USA.', 'United States|United States|United States|United States', 6, 'Algorithms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Oligonucleotide Array Sequence Analysis|Proteins|RNA, Messenger|Signal Transduction|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth389', '15247105', 'Identification of the regulatory structures in genetic networks and the formulation of mechanistic models in the form of wiring diagrams is one of the significant objectives of expression profiling using DNA microarray technologies and it requires the development and application of identification frameworks.'),
(71491, 2004, 'bio', 'Quantitative DNA methylation analysis based on four-dye trace data from direct sequencing of PCR amplificates', 'Lewin, Jörn|Schmitt, Armin O|Adorján, Péter|Hildmann, Thomas|Piepenbrock, Christian', 'Epigenomics AG, Kleine Präsidentenstrasse 1, 10178 Berlin, Germany. joern.lewin@epigenomics.com|Epigenomics AG, Kleine Präsidentenstrasse 1, 10178 Berlin, Germany. joern.lewin@epigenomics.com|Epigenomics AG, Kleine Präsidentenstrasse 1, 10178 Berlin, Germany. joern.lewin@epigenomics.com|Epigenomics AG, Kleine Präsidentenstrasse 1, 10178 Berlin, Germany. joern.lewin@epigenomics.com|Epigenomics AG, Kleine Präsidentenstrasse 1, 10178 Berlin, Germany. joern.lewin@epigenomics.com', 'Germany|Germany|Germany|Germany|Germany', 197, 'Algorithms|DNA Methylation|Electrophoresis|Fluorescent Dyes|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth346', '15247106', 'Methylation of cytosines in DNA plays an important role in the regulation of gene expression, and the analysis of methylation patterns is fundamental for the understanding of cell differentiation, aging processes, diseases and cancer development. Such analysis has been limited, because technologies for detailed and efficient high-throughput studies have not been available. We have developed a novel quantitative methylation analysis algorithm and workflow based on direct DNA sequencing of PCR products from bisulfite-treated DNA with high-throughput sequencing machines. This technology is a prerequisite for success of the Human Epigenome Project, the first large genome-wide sequencing study for DNA methylation in many different tissues. Methylation in tissue samples which are compositions of different cells is a quantitative information represented by cytosine/thymine proportions after bisulfite conversion of unmethylated cytosines to uracil and PCR. Calculation of quantitative methylation information from base proportions represented by different dye signals in four-dye sequencing trace files needs a specific algorithm handling imbalanced and overscaled signals, incomplete conversion, quality problems and basecaller artifacts.'),
(71492, 2004, 'bio', 'CBS Genome Atlas Database: a dynamic storage for bioinformatic results and sequence data', 'Hallin, Peter F|Ussery, David W', 'Center for Biological Sequence Analysis (CBS), BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Lyngby, Denmark. pfh@cbs.dtu.dk <pfh@cbs.dtu.dk>|Center for Biological Sequence Analysis (CBS), BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Lyngby, Denmark. pfh@cbs.dtu.dk <pfh@cbs.dtu.dk>', 'Denmark|Denmark', 66, 'Algorithms|Computational Biology|Database Management Systems|Databases, Nucleic Acid|Information Dissemination|Information Storage and Retrieval|Internet|Sequence Alignment|Sequence Analysis, DNA|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth423', '15256401', 'Currently, new bacterial genomes are being published on a monthly basis. With the growing amount of genome sequence data, there is a demand for a flexible and easy-to-maintain structure for storing sequence data and results from bioinformatic analysis. More than 150 sequenced bacterial genomes are now available, and comparisons of properties for taxonomically similar organisms are not readily available to many biologists. In addition to the most basic information, such as AT content, chromosome length, tRNA count and rRNA count, a large number of more complex calculations are needed to perform detailed comparative genomics. DNA structural calculations like curvature and stacking energy, DNA compositions like base skews, oligo skews and repeats at the local and global level are just a few of the analysis that are presented on the CBS Genome Atlas Web page. Complex analysis, changing methods and frequent addition of new models are factors that require a dynamic database layout. Using basic tools like the GNU Make system, csh, Perl and MySQL, we have created a flexible database environment for storing and maintaining such results for a collection of complete microbial genomes. Currently, these results counts to more than 220 pieces of information. The backbone of this solution consists of a program package written in Perl, which enables administrators to synchronize and update the database content. The MySQL database has been connected to the CBS web-server via PHP4, to present a dynamic web content for users outside the center. This solution is tightly fitted to existing server infrastructure and the solutions proposed here can perhaps serve as a template for other research groups to solve database issues.'),
(71493, 2004, 'bio', 'Limited agreement among three global gene expression methods highlights the requirement for non-global validation', 'Haverty, Peter M|Hsiao, Li-Li|Gullans, Steven R|Hansen, Ulla|Weng, Zhiping', 'Bioinformatics Program, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA.|Bioinformatics Program, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA.|Bioinformatics Program, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA.|Bioinformatics Program, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA.|Bioinformatics Program, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Benchmarking|Expressed Sequence Tags|Genetic Variation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Technology Assessment, Biomedical', 'Comparative Study', '10.1093/bioinformatics/bth421', '15256402', 'DNA microarrays have revolutionized biological research, but their reliability and accuracy have not been extensively evaluated. Thorough testing of microarrays through comparison to dissimilar gene expression methods is necessary in order to determine their accuracy.'),
(71494, 2004, 'bio', 'DNAfan: a software tool for automated extraction and analysis of user-defined sequence regions', 'Gisel, Andreas|Panetta, Maria|Grillo, Giorgio|Licciulli, Vito Flavio|Liuni, Sabino|Saccone, Cecilia|Pesole, Graziano', 'Sezione di Bioinformatica e Genomica di Bari, Istituto di Tecnologie Biomediche, CNR, via Amendola 122/D, 70126 Bari, Italy.|Sezione di Bioinformatica e Genomica di Bari, Istituto di Tecnologie Biomediche, CNR, via Amendola 122/D, 70126 Bari, Italy.|Sezione di Bioinformatica e Genomica di Bari, Istituto di Tecnologie Biomediche, CNR, via Amendola 122/D, 70126 Bari, Italy.|Sezione di Bioinformatica e Genomica di Bari, Istituto di Tecnologie Biomediche, CNR, via Amendola 122/D, 70126 Bari, Italy.|Sezione di Bioinformatica e Genomica di Bari, Istituto di Tecnologie Biomediche, CNR, via Amendola 122/D, 70126 Bari, Italy.|Sezione di Bioinformatica e Genomica di Bari, Istituto di Tecnologie Biomediche, CNR, via Amendola 122/D, 70126 Bari, Italy.|Sezione di Bioinformatica e Genomica di Bari, Istituto di Tecnologie Biomediche, CNR, via Amendola 122/D, 70126 Bari, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Artificial Intelligence|Conserved Sequence|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth420', '15256403', 'DNAfan (DNA Feature ANalyzer) is a tool combining sequence-filtering and pattern searching. DNAfan automatically extracts user-defined sets of sequence fragments from large sequence sets. Fragments are defined by annotated gene feature keys and co- or non-occurring patterns within the feature or close to it. A gene feature parser and a pattern-based filter tool localizes and extracts the specific subset of sequences. The selected sequence data can subsequently be retrieved for analyses or further processed with DNAfan to find the occurrence of specific patterns or structural motifs. DNAfan is a powerful tool for pattern analysis. Its filter features restricts the pattern search to a well-defined set of sequences, allowing drastic reduction in false positive hits.'),
(71495, 2004, 'bio', 'Gene selection using a two-level hierarchical Bayesian model', 'Bae, Kyounghwa|Mallick, Bani K', 'Department of Statistics, Texas A&M University, College Station, TX 77843-3143, USA.|Department of Statistics, Texas A&M University, College Station, TX 77843-3143, USA.', 'United States|United States', 113, 'Algorithms|Bayes Theorem|Biomarkers, Tumor|Gene Expression Profiling|Genetic Testing|Humans|Leukemia|Models, Genetic|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1093/bioinformatics/bth419', '15256404', 'The fundamental problem of gene selection via cDNA data is to identify which genes are differentially expressed across different kinds of tissue samples (e.g. normal and cancer). cDNA data contain large number of variables (genes) and usually the sample size is relatively small so the selection process can be unstable. Therefore, models which incorporate sparsity in terms of variables (genes) are desirable for this kind of problem. This paper proposes a two-level hierarchical Bayesian model for variable selection which assumes a prior that favors sparseness. We adopt a Markov chain Monte Carlo (MCMC) based computation technique to simulate the parameters from the posteriors. The method is applied to leukemia data from a previous study and a published dataset on breast cancer.'),
(71496, 2004, 'bio', 'GenePicker: replicate analysis of Affymetrix gene expression microarrays', 'Finocchiaro, Giacomo|Parise, Paola|Minardi, Simone P|Alcalay, Myriam|Müller, Heiko', 'Department of Experimental Oncology, European Institute of Oncology, Milan, Italy.|Department of Experimental Oncology, European Institute of Oncology, Milan, Italy.|Department of Experimental Oncology, European Institute of Oncology, Milan, Italy.|Department of Experimental Oncology, European Institute of Oncology, Milan, Italy.|Department of Experimental Oncology, European Institute of Oncology, Milan, Italy.', 'Italy|Italy|Italy|Italy|Italy', 13, 'Algorithms|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth416', '15256405', 'GenePicker allows efficient analysis of Affymetrix gene expression data performed in replicate, through definition of analysis schemes, data normalization, t-test/ANOVA, Change-Fold Change-analysis and yields lists of differentially expressed genes with high confidence. Comparison of noise and signal analysis schemes allows determining a signal-to-noise ratio in a given experiment. Change Call, Fold Change and Signal mean ratios are used in the analysis. While each parameter alone yields gene lists that contain up to 30% false positives, the combination of these parameters nearly eliminates the false positives as verified by northern blotting, quantitative PCR in numerous independent experiments as well as by the analysis of spike-in data.'),
(71497, 2004, 'bio', 'Dimension reduction methods for microarrays with application to censored survival data', 'Li, Lexin|Li, Hongzhe', 'Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, CA 95616, USA. lexli@ucdavis.edu <lexli@ucdavis.edu>|Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, CA 95616, USA. lexli@ucdavis.edu <lexli@ucdavis.edu>', 'United States|United States', 73, 'Biomarkers, Tumor|Genetic Predisposition to Disease|Genetic Testing|Humans|Lymphoma, B-Cell|Models, Statistical|Oligonucleotide Array Sequence Analysis|Proportional Hazards Models|Reproducibility of Results|Risk Assessment|Risk Factors|Sensitivity and Specificity|Survival Analysis|Survival Rate', 'Evaluation Studies', '10.1093/bioinformatics/bth415', '15256406', 'Recent research has shown that gene expression profiles can potentially be used for predicting various clinical phenotypes, such as tumor class, drug response and survival time. While there has been extensive studies on tumor classification, there has been less emphasis on other phenotypic features, in particular, patient survival time or time to cancer recurrence, which are subject to right censoring. We consider in this paper an analysis of censored survival time based on microarray gene expression profiles.'),
(71498, 2004, 'bio', 'Mining HIV protease cleavage data using genetic programming with a sum-product function', 'Yang, Zheng Rong|Dalby, Andrew R|Qiu, Jing', 'Department of Computer Science, Exeter University, UK. z.r.yang@ex.ac.uk <z.r.yang@ex.ac.uk>|Department of Computer Science, Exeter University, UK. z.r.yang@ex.ac.uk <z.r.yang@ex.ac.uk>|Department of Computer Science, Exeter University, UK. z.r.yang@ex.ac.uk <z.r.yang@ex.ac.uk>', 'United Kingdom|United Kingdom|United Kingdom', 12, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Drug Design|Enzyme Activation|Enzyme Inhibitors|HIV Protease|HIV Protease Inhibitors|Models, Chemical|Molecular Sequence Data|Numerical Analysis, Computer-Assisted|Protein Binding|Protein Interaction Mapping|Sequence Analysis, Protein|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bth414', '15256407', 'In order to design effective HIV inhibitors, studying and understanding the mechanism of HIV protease cleavage specification is critical. Various methods have been developed to explore the specificity of HIV protease cleavage activity. However, success in both extracting discriminant rules and maintaining high prediction accuracy is still challenging. The earlier study had employed genetic programming with a min-max scoring function to extract discriminant rules with success. However, the decision will finally be degenerated to one residue making further improvement of the prediction accuracy difficult. The challenge of revising the min-max scoring function so as to improve the prediction accuracy motivated this study.'),
(71499, 2004, 'bio', 'An optimized algorithm for flux estimation from isotopomer distribution in glucose metabolites', 'Selivanov, Vitaly A|Puigjaner, Joaquim|Sillero, Antonio|Centelles, Josep J|Ramos-Montoya, Antonio|Lee, Paul W-N|Cascante, Marta', 'Departamento de Bioquímica i Biologia Molecular, Facultat de Química and CERQT at Parc Científic de Barcelona, Barcelona, Catalunya, Spain.|Departamento de Bioquímica i Biologia Molecular, Facultat de Química and CERQT at Parc Científic de Barcelona, Barcelona, Catalunya, Spain.|Departamento de Bioquímica i Biologia Molecular, Facultat de Química and CERQT at Parc Científic de Barcelona, Barcelona, Catalunya, Spain.|Departamento de Bioquímica i Biologia Molecular, Facultat de Química and CERQT at Parc Científic de Barcelona, Barcelona, Catalunya, Spain.|Departamento de Bioquímica i Biologia Molecular, Facultat de Química and CERQT at Parc Científic de Barcelona, Barcelona, Catalunya, Spain.|Departamento de Bioquímica i Biologia Molecular, Facultat de Química and CERQT at Parc Científic de Barcelona, Barcelona, Catalunya, Spain.|Departamento de Bioquímica i Biologia Molecular, Facultat de Química and CERQT at Parc Científic de Barcelona, Barcelona, Catalunya, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Computer Simulation|Energy Metabolism|Glucose|Kinetics|Metabolic Clearance Rate|Models, Biological|Multienzyme Complexes|Radioisotope Dilution Technique|Signal Transduction|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth412', '15256408', 'Analysis of the conversion of (13)C glucose within the metabolic network allows the evaluation of the biochemical fluxes in interconnecting metabolic pathways. Such analyses require solving hundreds of equations with respect to individual isotopomer concentrations, and this assumes applying special software even for constructing the equations. The algorithm, proposed by others could be improved.'),
(71500, 2004, 'bio', 'CRH_Server: an online comparative and radiation hybrid mapping server for the canine genome', 'Hitte, Christophe|Derrien, Thomas|André, Catherine|Ostrander, Elaine A|Galibert, Francis', 'UMR 6061 CNRS, Génétique et Développement, faculté de Médecine, Université de Rennes1, 2 avenue Pr. Léon Bernard, 35043 Rennes Cédex, France. hitte@univ-rennes1.fr <hitte@univ-rennes1.fr>|UMR 6061 CNRS, Génétique et Développement, faculté de Médecine, Université de Rennes1, 2 avenue Pr. Léon Bernard, 35043 Rennes Cédex, France. hitte@univ-rennes1.fr <hitte@univ-rennes1.fr>|UMR 6061 CNRS, Génétique et Développement, faculté de Médecine, Université de Rennes1, 2 avenue Pr. Léon Bernard, 35043 Rennes Cédex, France. hitte@univ-rennes1.fr <hitte@univ-rennes1.fr>|UMR 6061 CNRS, Génétique et Développement, faculté de Médecine, Université de Rennes1, 2 avenue Pr. Léon Bernard, 35043 Rennes Cédex, France. hitte@univ-rennes1.fr <hitte@univ-rennes1.fr>|UMR 6061 CNRS, Génétique et Développement, faculté de Médecine, Université de Rennes1, 2 avenue Pr. Léon Bernard, 35043 Rennes Cédex, France. hitte@univ-rennes1.fr <hitte@univ-rennes1.fr>', 'France|France|France|France|France', 6, 'Algorithms|Animals|Chromosome Mapping|DNA Mutational Analysis|Dogs|Internet|Online Systems|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth411', '15256409', 'CRH_Server is an on line Comparative and Radiation Hybrid mapping Server dedicated to canine genomics. CRH_Server allows users to compute their own RH data using the current canine RH map, and allows comparative dog/human mapping analyses. Finally, it suggests multiple options for storage and queries of the dog RH database.'),
(71501, 2004, 'bio', 'A software program combining sequence motif searches with keywords for finding repeats containing DNA sequences', 'Bilgen, Mehmet|Karaca, Mehmet|Onus, A Naci|Ince, Ayxc5x9fe Gxc3xbcl', 'Faculty of Agriculture, Akdeniz University, 07059 Antalya, Turkey.|Faculty of Agriculture, Akdeniz University, 07059 Antalya, Turkey.|Faculty of Agriculture, Akdeniz University, 07059 Antalya, Turkey.|Faculty of Agriculture, Akdeniz University, 07059 Antalya, Turkey.', 'Turkey|Turkey|Turkey|Turkey', 39, 'Arabidopsis|Arabidopsis Proteins|Expressed Sequence Tags|Plant Structures|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software|Tandem Repeat Sequences', 'Evaluation Studies', '10.1093/bioinformatics/bth410', '15256410', 'One of the most interesting features of genomes (both coding and non-coding regions) is the presence of relatively short tandemly repeated DNA sequences known as tandem repeats (TRs). We developed a new PC-based stand-alone software analysis program, combining sequence motif searches with keywords such as organs, tissues, cell lines or development stages for finding exact, inexact and compound, TRs. Tandem Repeats Analyzer 1.5 (TRA) has several advanced repeat search parameters/options over other repeat finder programs as it does not only accept GenBank, FASTA and expressed sequence tag (EST) sequence files but also does analysis of multifiles with multisequences. Advanced user-defined parameters/options let the researchers use different motif lengths search criteria for varying motif lengths simultaneously. The outputs show statistical results to be evaluated by the user. The discovery of TRs in ESTs could be useful for both gene mapping and association studies and discovering TRs located in coding regions of important genes that are expressed under various conditions of environment, stress, organ, tissue and development stage.'),
(71502, 2004, 'bio', 'Extracting gene pathway relations using a hybrid grammar: the Arizona Relation Parser', 'McDonald, Daniel M|Chen, Hsinchun|Su, Hua|Marshall, Byron B', 'Artificial Intelligence Laboratory MIS Department, University of Arizona, 1130 E. Helen St, Tucson, AZ 85721, USA. dmm@eller.arizona.edu <dmm@eller.arizona.edu>|Artificial Intelligence Laboratory MIS Department, University of Arizona, 1130 E. Helen St, Tucson, AZ 85721, USA. dmm@eller.arizona.edu <dmm@eller.arizona.edu>|Artificial Intelligence Laboratory MIS Department, University of Arizona, 1130 E. Helen St, Tucson, AZ 85721, USA. dmm@eller.arizona.edu <dmm@eller.arizona.edu>|Artificial Intelligence Laboratory MIS Department, University of Arizona, 1130 E. Helen St, Tucson, AZ 85721, USA. dmm@eller.arizona.edu <dmm@eller.arizona.edu>', 'United States|United States|United States|United States', 47, 'Artificial Intelligence|Database Management Systems|Documentation|Gene Expression Regulation|Information Storage and Retrieval|Natural Language Processing|Pattern Recognition, Automated|PubMed|Semantics|Signal Transduction|Transcription Factors|User-Computer Interface|Vocabulary, Controlled', 'Comparative Study', '10.1093/bioinformatics/bth409', '15256411', 'Text-mining research in the biomedical domain has been motivated by the rapid growth of new research findings. Improving the accessibility of findings has potential to speed hypothesis generation.'),
(71503, 2004, 'bio', 'Reducing storage requirements for biological sequence comparison', 'Roberts, Michael|Hayes, Wayne|Hunt, Brian R|Mount, Stephen M|Yorke, James A', 'Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742-2431, USA.|Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742-2431, USA.|Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742-2431, USA.|Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742-2431, USA.|Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742-2431, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Databases, Genetic|Information Storage and Retrieval|Numerical Analysis, Computer-Assisted|Sequence Alignment|Sequence Analysis', 'Evaluation Studies', '10.1093/bioinformatics/bth408', '15256412', 'Comparison of nucleic acid and protein sequences is a fundamental tool of modern bioinformatics. A dominant method of such string matching is the seed-and-extend approach, in which occurrences of short subsequences called seeds are used to search for potentially longer matches in a large database of sequences. Each such potential match is then checked to see if it extends beyond the seed. To be effective, the seed-and-extend approach needs to catalogue seeds from virtually every substring in the database of search strings. Projects such as mammalian genome assemblies and large-scale protein matching, however, have such large sequence databases that the resulting list of seeds cannot be stored in RAM on a single computer. This significantly slows the matching process.'),
(71504, 2004, 'bio', 'Preferred in vivo ubiquitination sites', 'Catic, André|Collins, Cal|Church, George M|Ploegh, Hidde L', 'Department of Pathology, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA. Catic@fas.harvard.edu <Catic@fas.harvard.edu>|Department of Pathology, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA. Catic@fas.harvard.edu <Catic@fas.harvard.edu>|Department of Pathology, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA. Catic@fas.harvard.edu <Catic@fas.harvard.edu>|Department of Pathology, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA. Catic@fas.harvard.edu <Catic@fas.harvard.edu>', 'United States|United States|United States|United States', 38, 'Amino Acid Motifs|Amino Acid Sequence|Binding Sites|Enzyme Activation|Molecular Conformation|Protein Binding|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship|Substrate Specificity|Ubiquitin|Ubiquitin-Activating Enzymes', 'Journal Article', '10.1093/bioinformatics/bth407', '15256413', 'The conjugation of ubiquitin to target molecules involves several enzymatic steps. Little is known about the specificity of ubiquitination. How E3 ligases select their substrate and which lysines are targeted for ubiquitin conjugation is largely an enigma. The object of this study is to identify preferred ubiquitination sites. Genetic approaches to study this question have proven difficult, because of the redundancy of ligases and the lack of strictly required motifs. However, a better understanding of acceptor site selection could help to predict ubiquitination sites and clarify yet unsolved structure-function relationships of the transfer reaction.'),
(71505, 2004, 'bio', 'Interactive gene-order comparison for multiple small genomes', 'Kaluszka, Aaron|Gibas, Cynthia', 'Department of Biology, College of Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.|Department of Biology, College of Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.', 'United States|United States', 2, 'Algorithms|Chromosome Mapping|Computer Graphics|Online Systems|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth406', '15256414', 'The Genome Organization Analysis Tool (GOAT) is a program that performs comparative sequence analysis on ordered gene lists from annotated genomes, provides visual and tabular output, and provides means of accessing and analyzing related gene sequence data, for the purpose of comparing genome organization at the gene-order level. GOAT can be used to compare any two or more genomes or chromosomes on demand, or configured to provide access to precomputed comparisons of a specific group of genome sequences.'),
(71506, 2004, 'bio', 'A graph-theoretic approach to testing associations between disparate sources of functional genomics data', 'Balasubramanian, Raji|LaFramboise, Thomas|Scholtens, Denise|Gentleman, Robert', 'Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.|Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.', 'United States|United States|United States|United States', 31, 'Algorithms|Chromosome Mapping|Gene Expression Profiling|Numerical Analysis, Computer-Assisted|Reproducibility of Results|Saccharomyces cerevisiae|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth405', '15256415', 'The last few years have seen the advent of high-throughput technologies to analyze various properties of the transcriptome and proteome of several organisms. The congruency of these different data sources, or lack thereof, can shed light on the mechanisms that govern cellular function. A central challenge for bioinformatics research is to develop a unified framework for combining the multiple sources of functional genomics information and testing associations between them, thus obtaining a robust and integrated view of the underlying biology.'),
(71507, 2004, 'bio', 'Importing MAGE-ML format microarray data into BioConductor', 'Durinck, Steffen|Allemeersch, Joke|Carey, Vincent J|Moreau, Yves|De Moor, Bart', 'Department of Electronical Engineering, ESAT-SCD, K.U. Leuven, Kasteelpark Arenberg 10, 3001, Leuven-Heverlee, Belgium.|Department of Electronical Engineering, ESAT-SCD, K.U. Leuven, Kasteelpark Arenberg 10, 3001, Leuven-Heverlee, Belgium.|Department of Electronical Engineering, ESAT-SCD, K.U. Leuven, Kasteelpark Arenberg 10, 3001, Leuven-Heverlee, Belgium.|Department of Electronical Engineering, ESAT-SCD, K.U. Leuven, Kasteelpark Arenberg 10, 3001, Leuven-Heverlee, Belgium.|Department of Electronical Engineering, ESAT-SCD, K.U. Leuven, Kasteelpark Arenberg 10, 3001, Leuven-Heverlee, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth396', '15256416', 'The microarray gene expression markup language (MAGE-ML) is a widely used XML (eXtensible Markup Language) standard for describing and exchanging information about microarray experiments. It can describe microarray designs, microarray experiment designs, gene expression data and data analysis results. We describe RMAGEML, a new Bioconductor package that provides a link between cDNA microarray data stored in MAGE-ML format and the Bioconductor framework for preprocessing, visualization and analysis of microarray experiments.'),
(71508, 2004, 'bio', 'Application of a new probabilistic model for recognizing complex patterns in glycans', 'Aoki, Kiyoko F|Ueda, Nobuhisa|Yamaguchi, Atsuko|Kanehisa, Minoru|Akutsu, Tatsuya|Mamitsuka, Hiroshi', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 18, 'Algorithms|Carbohydrate Sequence|Computer Simulation|Data Interpretation, Statistical|Models, Chemical|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Polysaccharides|Sequence Analysis', 'Evaluation Studies', '10.1093/bioinformatics/bth916', '15262775', 'The study of carbohydrate sugar chains, or glycans, has been one of slow progress mainly due to the difficulty in establishing standard methods for analyzing their structures and biosynthesis. Glycans are generally tree structures that are more complex than linear DNA or protein sequences, and evidence shows that patterns in glycans may be present that spread across siblings and into further regions that are not limited by the edges in the actual tree structure itself. Current models were not able to capture such patterns.'),
(71509, 2004, 'bio', 'A knowledge based approach for representing and reasoning about signaling networks', 'Baral, C|Chancellor, K|Tran, N|Tran, N L|Joy, A|Berens, M', 'Department of Computer Science and Engineering, Ira A. Fulton School of Engineering, Arizona State University, Tempe, AZ 85281, USA. baral@asu.edu|Department of Computer Science and Engineering, Ira A. Fulton School of Engineering, Arizona State University, Tempe, AZ 85281, USA. baral@asu.edu|Department of Computer Science and Engineering, Ira A. Fulton School of Engineering, Arizona State University, Tempe, AZ 85281, USA. baral@asu.edu|Department of Computer Science and Engineering, Ira A. Fulton School of Engineering, Arizona State University, Tempe, AZ 85281, USA. baral@asu.edu|Department of Computer Science and Engineering, Ira A. Fulton School of Engineering, Arizona State University, Tempe, AZ 85281, USA. baral@asu.edu|Department of Computer Science and Engineering, Ira A. Fulton School of Engineering, Arizona State University, Tempe, AZ 85281, USA. baral@asu.edu', 'United States|United States|United States|United States|United States|United States', 54, 'Algorithms|Artificial Intelligence|Computer Simulation|Gene Expression|Gene Expression Profiling|Models, Biological|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/bth918', '15262776', 'In this paper we propose to use recent developments in knowledge representation languages and reasoning methodologies for representing and reasoning about signaling networks. Our approach is different from most other qualitative systems biology approaches in that it is based on reasoning (or inferencing) rather than simulation. Some of the advantages of our approach are, we can use recent advances in reasoning with incomplete and partial information to deal with gaps in signal network knowledge, and can perform various kinds of reasoning such as planning, hypothetical reasoning and explaining observations.'),
(71510, 2004, 'bio', 'Deconvolving cell cycle expression data with complementary information', 'Bar-Joseph, Ziv|Farkash, Shlomit|Gifford, David K|Simon, Itamar|Rosenfeld, Roni', 'School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. zivbj@cs.cmu.edu|School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. zivbj@cs.cmu.edu|School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. zivbj@cs.cmu.edu|School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. zivbj@cs.cmu.edu|School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. zivbj@cs.cmu.edu', 'United States|United States|United States|United States|United States', 41, 'Biological Clocks|Cell Communication|Cell Cycle|Cell Cycle Proteins|Computer Simulation|Databases, Protein|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Saccharomycetales', 'Journal Article', '10.1093/bioinformatics/bth915', '15262777', 'In the study of many systems, cells are first synchronized so that a large population of cells exhibit similar behavior. While synchronization can usually be achieved for a short duration, after a while cells begin to lose their synchronization. Synchronization loss is a continuous process and so the observed value in a population of cells for a gene at time t is actually a convolution of its values in an interval around t. Deconvolving the observed values from a mixed population will allow us to obtain better models for these systems and to accurately detect the genes that participate in these systems.'),
(71511, 2004, 'bio', 'Statistical modeling of sequencing errors in SAGE libraries', 'Beissbarth, Tim|Hyde, Lavinia|Smyth, Gordon K|Job, Chris|Boon, Wee-Ming|Tan, Seong-Seng|Scott, Hamish S|Speed, Terence P', 'Walter and Eliza Hall Institute of Medical Research, Genetics and Bioinformatics, Parkville, Vic, Australia. beissbarth@wehi.edu.au|Walter and Eliza Hall Institute of Medical Research, Genetics and Bioinformatics, Parkville, Vic, Australia. beissbarth@wehi.edu.au|Walter and Eliza Hall Institute of Medical Research, Genetics and Bioinformatics, Parkville, Vic, Australia. beissbarth@wehi.edu.au|Walter and Eliza Hall Institute of Medical Research, Genetics and Bioinformatics, Parkville, Vic, Australia. beissbarth@wehi.edu.au|Walter and Eliza Hall Institute of Medical Research, Genetics and Bioinformatics, Parkville, Vic, Australia. beissbarth@wehi.edu.au|Walter and Eliza Hall Institute of Medical Research, Genetics and Bioinformatics, Parkville, Vic, Australia. beissbarth@wehi.edu.au|Walter and Eliza Hall Institute of Medical Research, Genetics and Bioinformatics, Parkville, Vic, Australia. beissbarth@wehi.edu.au|Walter and Eliza Hall Institute of Medical Research, Genetics and Bioinformatics, Parkville, Vic, Australia. beissbarth@wehi.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 74, 'Algorithms|Base Sequence|Computer Simulation|Data Interpretation, Statistical|Expressed Sequence Tags|Gene Expression Profiling|Gene Library|Models, Genetic|Models, Statistical|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bth924', '15262778', 'Sequencing errors may bias the gene expression measurements made by Serial Analysis of Gene Expression (SAGE). They may introduce non-existent tags at low abundance and decrease the real abundance of other tags. These effects are increased in the longer tags generated in LongSAGE libraries. Current sequencing technology generates quite accurate estimates of sequencing error rates. Here we make use of the sequence neighborhood of SAGE tags and error estimates from the base-calling software to correct for such errors.'),
(71512, 2004, 'bio', 'Into the heart of darkness: large-scale clustering of human non-coding DNA', 'Bejerano, Gill|Haussler, David|Blanchette, Mathieu', 'Center for Biomolecular Science and Engineering, Baskin School of Engineering University of California in Santa Cruz, Santa Cruz, CA 95064, USA. jill@soe.ucsc.edu|Center for Biomolecular Science and Engineering, Baskin School of Engineering University of California in Santa Cruz, Santa Cruz, CA 95064, USA. jill@soe.ucsc.edu|Center for Biomolecular Science and Engineering, Baskin School of Engineering University of California in Santa Cruz, Santa Cruz, CA 95064, USA. jill@soe.ucsc.edu', 'United States|United States|United States', 53, 'Animals|Chromosome Mapping|Cluster Analysis|Conserved Sequence|Evolution, Molecular|Humans|Mice|Multigene Family|Rats|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Species Specificity|Untranslated Regions', 'Journal Article', '10.1093/bioinformatics/bth946', '15262779', 'It is currently believed that the human genome contains about twice as much non-coding functional regions as it does protein-coding genes, yet our understanding of these regions is very limited.'),
(71513, 2004, 'bio', 'Automatic quality assessment of peptide tandem mass spectra', 'Bern, Marshall|Goldberg, David|McDonald, W Hayes|Yates, John R', 'Palo Alto Research Center, Palo Alto, CA 94304, USA.|Palo Alto Research Center, Palo Alto, CA 94304, USA.|Palo Alto Research Center, Palo Alto, CA 94304, USA.|Palo Alto Research Center, Palo Alto, CA 94304, USA.', 'United States|United States|United States|United States', 158, 'Algorithms|Amino Acid Sequence|Mass Spectrometry|Molecular Sequence Data|Peptide Mapping|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/bth947', '15262780', 'A powerful proteomics methodology couples high-performance liquid chromatography (HPLC) with tandem mass spectrometry and database-search software, such as SEQUEST. Such a set-up, however, produces a large number of spectra, many of which are of too poor quality to be useful. Hence a filter that eliminates poor spectra before the database search can significantly improve throughput and robustness. Moreover, spectra judged to be of high quality, but that cannot be identified by database search, are prime candidates for still more computationally intensive methods, such as de novo sequencing or wider database searches including post-translational modifications.'),
(71514, 2004, 'bio', 'Analysis of domain correlations in yeast protein complexes', 'Betel, Doron|Isserlin, Ruth|Hogue, Christopher W V', 'Samuel Lunenfeld Research Institute, Mt Sinai Hospital, Toronto, Canada.|Samuel Lunenfeld Research Institute, Mt Sinai Hospital, Toronto, Canada.|Samuel Lunenfeld Research Institute, Mt Sinai Hospital, Toronto, Canada.', 'Canada|Canada|Canada', 10, 'Amino Acid Motifs|Amino Acid Sequence|Conserved Sequence|Databases, Protein|Molecular Sequence Data|Protein Structure, Tertiary|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/bth903', '15262781', 'A growing body of research has concentrated on the identification and definition of conserved sequence motifs. It is widely recognized that these conserved sequence and structural units often mediate protein functions and interactions. The continuing advancements in high-throughput experiments necessitate the development of computational methods to critically assess the results. In this work, we analyzed high-throughput protein complexes using the domain composition of their protein constituents. Domains that mediate similar or related functions may consistently co-occur in protein complexes.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71515, 2004, 'bio', 'A neural-network-based method for predicting protein stability changes upon single point mutations', 'Capriotti, Emidio|Fariselli, Piero|Casadio, Rita', 'Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, Bologna, Italy.|Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, Bologna, Italy.|Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, Bologna, Italy.', 'Italy|Italy|Italy', 132, 'Algorithms|Computer Simulation|Drug Stability|Models, Chemical|Models, Molecular|Mutagenesis, Site-Directed|Neural Networks (Computer)|Pattern Recognition, Automated|Protein Denaturation|Protein Folding|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth928', '15262782', 'One important requirement for protein design is to be able to predict changes of protein stability upon mutation. Different methods addressing this task have been described and their performance tested considering global linear correlation between predicted and experimental data. Neither is direct statistical evaluation of their prediction performance available, nor is a direct comparison among different approaches possible. Recently, a significant database of thermodynamic data on protein stability changes upon single point mutation has been generated (ProTherm). This allows the application of machine learning techniques to predicting free energy stability changes upon mutation starting from the protein sequence.'),
(71516, 2004, 'bio', 'Splice site identification by idlBNs', 'Castelo, Robert|Guigó, Roderic', 'Grup de Recerca en Informàtica Biomèdica, Institut Municipal dInvestigació Mèdica, Universitat Pompeu Fabra, Centre de Regulació Genòmica, Psg. Marítim 37-49, Barcelona, Spain. rcastelo@imim.es|Grup de Recerca en Informàtica Biomèdica, Institut Municipal dInvestigació Mèdica, Universitat Pompeu Fabra, Centre de Regulació Genòmica, Psg. Marítim 37-49, Barcelona, Spain. rcastelo@imim.es', 'Spain|Spain', 33, 'Algorithms|Artificial Intelligence|Base Sequence|Bayes Theorem|Chromosome Mapping|Molecular Sequence Data|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bth932', '15262783', 'Computational identification of functional sites in nucleotide sequences is at the core of many algorithms for the analysis of genomic data. This identification is based on the statistical parameters estimated from a training set. Often, because of the huge number of parameters, it is difficult to obtain consistent estimators. To simplify the estimation problem, one imposes independent assumptions between the nucleotides along the site. However, this can potentially limit the minimum value of the estimation error.'),
(71517, 2004, 'bio', 'Mining frequent patterns in protein structures: a study of protease families', 'Chen, Shann-Ching|Bahar, Ivet', 'Center for Computational Biology and Bioinformatics, Department of Molecular Genetics and Biochemistry, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15261, USA.|Center for Computational Biology and Bioinformatics, Department of Molecular Genetics and Biochemistry, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15261, USA.', 'United States|United States', 28, 'Algorithms|Amino Acid Sequence|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Pattern Recognition, Automated|Peptide Hydrolases|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth912', '15262784', 'Analysis of protein sequence and structure databases usually reveal frequent patterns (FP) associated with biological function. Data mining techniques generally consider the physicochemical and structural properties of amino acids and their microenvironment in the folded structures. Dynamics is not usually considered, although proteins are not static, and their function relates to conformational mobility in many cases.'),
(71518, 2004, 'bio', 'Selecting biomedical data sources according to user preferences', 'Boulakia, Sarah Cohen|Lair, Séverine|Stransky, Nicolas|Graziani, Stéphane|Radvanyi, François|Barillot, Emmanuel|Froidevaux, Christine', 'Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, Orsay Cedex, France. cohen@lri.fr|Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, Orsay Cedex, France. cohen@lri.fr|Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, Orsay Cedex, France. cohen@lri.fr|Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, Orsay Cedex, France. cohen@lri.fr|Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, Orsay Cedex, France. cohen@lri.fr|Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, Orsay Cedex, France. cohen@lri.fr|Laboratoire de Recherche en Informatique, CNRS UMR 8623, Université Paris-Sud, Orsay Cedex, France. cohen@lri.fr', 'France|France|France|France|France|France|France', 15, 'Algorithms|Biomedical Engineering|Database Management Systems|Databases, Factual|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Systems Integration|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth949', '15262785', 'Biologists are now faced with the problem of integrating information from multiple heterogeneous public sources with their own experimental data contained in individual sources. The selection of the sources to be considered is thus critically important.'),
(71519, 2004, 'bio', 'Improved techniques for the identification of pseudogenes', 'Coin, L|Durbin, R', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. lc1@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. lc1@sanger.ac.uk', 'United Kingdom|United Kingdom', 21, 'Algorithms|Chromosome Mapping|Evolution, Molecular|Genetic Variation|Pseudogenes|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth942', '15262786', 'Pseudogenes are the remnants of genomic sequences of genes which are no longer functional. They are frequent in most eukaryotic genomes, and an important resource for comparative genomics. However, pseudogenes are often mis-annotated as functional genes in sequence databases. Current methods for identifying pseudogenes include methods which rely on the presence of stop codons and frameshifts, as well as methods based on the ratio of non-silent to silent nucleotide substitution rates (dN/dS). A recent survey concluded that 50% of human pseudogenes have no detectable truncation in their pseudo-coding regions, indicating that the former methods lack sensitivity. The latter methods have been used to find sets of genes enriched for pseudogenes, but are not specific enough to accurately separate pseudogenes from expressed genes.'),
(71520, 2004, 'bio', 'Predicting gene regulation by sigma factors in Bacillus subtilis from genome-wide data', 'de Hoon, M J L|Makita, Y|Imoto, S|Kobayashi, K|Ogasawara, N|Nakai, K|Miyano, S', 'Human Genome Center, Institute of Medical Science, University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan. mdehoon@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan. mdehoon@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan. mdehoon@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan. mdehoon@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan. mdehoon@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan. mdehoon@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan. mdehoon@ims.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 22, 'Algorithms|Bacillus subtilis|Bacterial Proteins|Chromosome Mapping|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Models, Statistical|Sigma Factor', 'Journal Article', '10.1093/bioinformatics/bth927', '15262787', 'Sigma factors regulate the expression of genes in Bacillus subtilis at the transcriptional level. We assess the accuracy of a fold-change analysis, Bayesian networks, dynamic models and supervised learning based on coregulation in predicting gene regulation by sigma factors from gene expression data. To improve the prediction accuracy, we combine sequence information with expression data by adding their log-likelihood scores and by using a logistic regression model. We use the resulting score function to discover currently unknown gene regulations by sigma factors.'),
(71521, 2004, 'bio', 'Functional inference from non-random distributions of conserved predicted transcription factor binding sites', 'Dieterich, Christoph|Rahmann, Sven|Vingron, Martin', 'Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. christoph.dieterich@molgen.mpg.de|Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. christoph.dieterich@molgen.mpg.de|Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. christoph.dieterich@molgen.mpg.de', 'Germany|Germany|Germany', 10, 'Animals|Binding Sites|Computer Simulation|Conserved Sequence|Evolution, Molecular|HeLa Cells|Humans|Mice|Models, Genetic|Models, Statistical|Protein Binding|Regulatory Sequences, Nucleic Acid|Sequence Analysis, DNA|Statistical Distributions|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bth908', '15262788', 'Our understanding of how genes are regulated in a concerted fashion is still limited. Especially, complex phenomena like cell cycle regulation in multicellular organisms are poorly understood. Therefore, we investigated conserved predicted transcription factor binding sites (TFBSs) in man-mouse upstream regions of genes that can be associated to a particular cell cycle phase in HeLa cells. TFBSs were predicted from selected binding site motifs (represented by position weight matrices, PWMs) based on a statistical approach. A regulatory role for a transcription factor is more probable if its predicted TFBSs are enriched in upstream regions of genes, that are associated with a subset of cell cycle phases. We tested for this association by computing exact P-values for the observed phase distributions under the null distribution defined by the relative amount of conserved upstream sequence of genes per cell cycle phase. We considered non-exonic and 5-untranslated region (5-UTR) binding sites separately and corrected for multiple testing by taking the false discovery rate into account.'),
(71522, 2004, 'bio', 'Phylogenomics and the number of characters required for obtaining an accurate phylogeny of eukaryote model species', 'Dopazo, Hernán|Santoyo, Javier|Dopazo, Joaquín', 'Bioinformatics Unit. Biotechnology Programme, Centro Nacional de Investigaciones Oncológicas, Melchor Fernández Almagro, Madrid, Spain.|Bioinformatics Unit. Biotechnology Programme, Centro Nacional de Investigaciones Oncológicas, Melchor Fernández Almagro, Madrid, Spain.|Bioinformatics Unit. Biotechnology Programme, Centro Nacional de Investigaciones Oncológicas, Melchor Fernández Almagro, Madrid, Spain.', 'Spain|Spain|Spain', 44, 'Animals|Base Sequence|Biological Evolution|Chromosome Mapping|Exons|Genetic Code|Humans|Models, Genetic|Molecular Sequence Data|Phylogeny|Reproducibility of Results|Sensitivity and Specificity|Species Specificity', 'Journal Article', '10.1093/bioinformatics/bth902', '15262789', 'Through the most extensive phylogenomic analysis carried out to date, complete genomes of 11 eukaryotic species have been examined in order to find the homologous of more than 25,000 amino acid sequences. These sequences correspond to the exons of more than 3000 genes and were used as presence/absence characters to test one of the most controversial hypotheses concerning animal evolution, namely the Ecdysozoa hypothesis. Distance, maximum parsimony and Bayesian methods of phylogenetic reconstruction were used to test the hypothesis.'),
(71523, 2004, 'bio', 'Assigning transmembrane segments to helices in intermediate-resolution structures', 'Enosh, Angela|Fleishman, Sarel J|Ben-Tal, Nir|Halperin, Dan', 'School of Computer Science, Tel Aviv University, Ramat Aviv, Israel. angela@post.tau.ac.il|School of Computer Science, Tel Aviv University, Ramat Aviv, Israel. angela@post.tau.ac.il|School of Computer Science, Tel Aviv University, Ramat Aviv, Israel. angela@post.tau.ac.il|School of Computer Science, Tel Aviv University, Ramat Aviv, Israel. angela@post.tau.ac.il', 'Israel|Israel|Israel|Israel', 12, 'Amino Acid Sequence|Cell Membrane|Computer Simulation|Membrane Proteins|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Structure, Tertiary|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth939', '15262790', 'Transmembrane (TM) proteins that form alpha-helix bundles constitute approximately 50% of contemporary drug targets. Yet, it is difficult to determine their high-resolution (< 4 A) structures. Some TM proteins yield more easily to structure determination using cryo electron microscopy (cryo-EM), though this technique most often results in lower resolution structures, precluding an unambiguous assignment of TM amino acid sequences to the helices seen in the structure. We present computational tools for assigning the TM segments in the proteins sequence to the helices seen in cryo-EM structures.'),
(71524, 2004, 'bio', 'SCOPEC: a database of protein catalytic domains', 'George, Richard A|Spriggs, Ruth V|Thornton, Janet M|Al-Lazikani, Bissan|Swindells, Mark B', 'Inpharmatica Ltd, London, UK. richardg@inpharmatica.co.uk|Inpharmatica Ltd, London, UK. richardg@inpharmatica.co.uk|Inpharmatica Ltd, London, UK. richardg@inpharmatica.co.uk|Inpharmatica Ltd, London, UK. richardg@inpharmatica.co.uk|Inpharmatica Ltd, London, UK. richardg@inpharmatica.co.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 27, 'Catalysis|Computer Simulation|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Models, Chemical|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth948', '15262791', 'Domains are the units of protein structure, function and evolution. It is therefore essential to utilize knowledge of domains when studying the evolution of function, or when assigning function to genome sequence data. For this purpose, we have developed a database of catalytic domains, SCOPEC, by combining structural domain information from SCOP, full-length sequence information from Swiss-Prot, and verified functional information from the Enzyme Classification (EC) database. Two major problems need to be overcome to create a database of domain-function relationships, (1) for sequences, EC numbers are typically assigned to whole sequences rather than the functional unit, and (2) The Protein Data Bank (PDB) structures elucidated from a larger multi-domain protein will often have EC annotation although the relevant catalytic domain may lie elsewhere.'),
(71525, 2004, 'bio', 'High density linkage disequilibrium mapping using models of haplotype block variation', 'Greenspan, G|Geiger, D', 'Computer Science Department, Technion, Haifa, Israel. gdg@cs.technion.ac.il|Computer Science Department, Technion, Haifa, Israel. gdg@cs.technion.ac.il', 'Israel|Israel', 31, 'Artificial Intelligence|Bayes Theorem|Chromosome Mapping|Computer Simulation|Genetic Variation|Haplotypes|Linkage Disequilibrium|Models, Genetic|Models, Statistical|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bth907', '15262792', 'The presence of millions of single nucleotide polymorphisms (SNPs) in the human genome has spurred interest in genetic mapping methods based on linkage disequilibrium. The recently discovered haplotype block structure of human variation promises to improve the effectiveness of these methods. A key difficulty for mapping techniques is the cost involved in separately identifying the haplotypes on each of an individuals chromosomes.'),
(71526, 2004, 'bio', 'The cell graphs of cancer', 'Gunduz, Cigdem|Yener, Bülent|Gultekin, S Humayun', 'Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. gunduz@cs.rpi.edu|Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. gunduz@cs.rpi.edu|Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY 12180, USA. gunduz@cs.rpi.edu', 'United States|United States|United States', 97, 'Algorithms|Artificial Intelligence|Brain Neoplasms|Glioma|Humans|Image Interpretation, Computer-Assisted|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1093/bioinformatics/bth933', '15262793', 'We report a novel, proof-of-concept, computational method that models a type of brain cancer (glioma) only by using the topological properties of its cells in the tissue image. From low-magnification (80x) tissue images of 384 x 384 pixels, we construct the graphs of the cells based on the locations of the cells within the images. We generate such cell graphs of 1000-3000 cells (nodes) with 2000-10,000 links, each of which is calculated as a decaying exponential function of the Euclidean distance between every pair of cells in accordance with the Waxman model. At the cellular level, we compute the graph metrics of the cell graphs, including the degree, clustering coefficient, eccentricity and closeness for each cell. Working with a total of 285 tissue samples surgically removed from 12 different patients, we demonstrate that the self-organizing clusters of cancerous cells exhibit distinctive graph metrics that distinguish them from the healthy cells and the unhealthy inflamed cells at the cellular level with an accuracy of at least 85%. At the tissue level, we accomplish correct tissue classifications of cancerous, healthy and non-neoplastic inflamed tissue samples with an accuracy of 100% by requiring correct classification for the majority of the cells within the tissue sample.'),
(71527, 2004, 'bio', 'TraitMap: an XML-based genetic-map database combining multigenic loci and biomolecular networks', 'Heida, Naohiko|Hasegawa, Yoshikazu|Mochizuki, Yoshiki|Hirosawa, Katsura|Konagaya, Akihiko|Toyoda, Tetsuro', 'Genomic Knowledge Base Research Team, Bioinformatics Group, Genomic Sciences Center, RIKEN, Suehiro, Tsurumi, Yokohama, Kanagawa, Japan.|Genomic Knowledge Base Research Team, Bioinformatics Group, Genomic Sciences Center, RIKEN, Suehiro, Tsurumi, Yokohama, Kanagawa, Japan.|Genomic Knowledge Base Research Team, Bioinformatics Group, Genomic Sciences Center, RIKEN, Suehiro, Tsurumi, Yokohama, Kanagawa, Japan.|Genomic Knowledge Base Research Team, Bioinformatics Group, Genomic Sciences Center, RIKEN, Suehiro, Tsurumi, Yokohama, Kanagawa, Japan.|Genomic Knowledge Base Research Team, Bioinformatics Group, Genomic Sciences Center, RIKEN, Suehiro, Tsurumi, Yokohama, Kanagawa, Japan.|Genomic Knowledge Base Research Team, Bioinformatics Group, Genomic Sciences Center, RIKEN, Suehiro, Tsurumi, Yokohama, Kanagawa, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 5, 'Chromosome Mapping|Computer Graphics|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Multigene Family|Programming Languages|Protein Interaction Mapping|Quantitative Trait Loci|Signal Transduction|Software|Systems Integration', 'Journal Article', '10.1093/bioinformatics/bth940', '15262794', 'Most ordinary traits are well described by multiple measurable parameters. Thus, in the course of elucidating the genes responsible for a given trait, it is necessary to conduct and integrate the genetic mapping of each parameter. However, the integration of multiple mapping results from different publications is prevented by the fact that they are conventionally published and accumulated in printed forms or graphics which are difficult for computers to reuse for further analyses.'),
(71528, 2004, 'bio', 'Efficient approximations for learning phylogenetic HMM models from data', 'Jojic, Vladimir|Jojic, Nebojsa|Meek, Chris|Geiger, Dan|Siepel, Adam|Haussler, David|Heckerman, D', 'Microsoft Research, Redmond, WA 98052, USA. vjojic@psi.toronto.edu|Microsoft Research, Redmond, WA 98052, USA. vjojic@psi.toronto.edu|Microsoft Research, Redmond, WA 98052, USA. vjojic@psi.toronto.edu|Microsoft Research, Redmond, WA 98052, USA. vjojic@psi.toronto.edu|Microsoft Research, Redmond, WA 98052, USA. vjojic@psi.toronto.edu|Microsoft Research, Redmond, WA 98052, USA. vjojic@psi.toronto.edu|Microsoft Research, Redmond, WA 98052, USA. vjojic@psi.toronto.edu', 'United States|United States|United States|United States|United States|United States|United States', 23, 'Algorithms|Artificial Intelligence|Base Sequence|Computer Simulation|Databases, Genetic|Evolution, Molecular|Markov Chains|Models, Genetic|Molecular Sequence Data|Pattern Recognition, Automated|Phylogeny|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1093/bioinformatics/bth917', '15262795', 'We consider models useful for learning an evolutionary or phylogenetic tree from data consisting of DNA sequences corresponding to the leaves of the tree. In particular, we consider a general probabilistic model described in Siepel and Haussler that we call the phylogenetic-HMM model which generalizes the classical probabilistic models of Neyman and Felsenstein. Unfortunately, computing the likelihood of phylogenetic-HMM models is intractable. We consider several approximations for computing the likelihood of such models including an approximation introduced in Siepel and Haussler, loopy belief propagation and several variational methods.'),
(71529, 2004, 'bio', 'The gene ontology categorizer', 'Joslyn, Cliff A|Mniszewski, Susan M|Fulmer, Andy|Heaton, Gary', 'Computer and Computational Sciences, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. joslyn@lanl.gov|Computer and Computational Sciences, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. joslyn@lanl.gov|Computer and Computational Sciences, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. joslyn@lanl.gov|Computer and Computational Sciences, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. joslyn@lanl.gov', 'United States|United States|United States|United States', 58, 'Database Management Systems|Databases, Protein|Genes|Information Storage and Retrieval|Medical Subject Headings|Proteins|Terminology as Topic', 'Journal Article', '10.1093/bioinformatics/bth921', '15262796', 'The Gene Ontology Categorizer, developed jointly by the Los Alamos National Laboratory and Procter & Gamble Corp., provides a capability for the categorization task in the Gene Ontology (GO): given a list of genes of interest, what are the best nodes of the GO to summarize or categorize that list? The motivating question is from a drug discovery process, where after some gene expression analysis experiment, we wish to understand the overall effect of some cell treatment or condition by identifying where in the GO the differentially expressed genes fall: clustered together in one place? in two places? uniformly spread throughout the GO? high, or low? In order to address this need, we view bio-ontologies more as combinatorially structured databases than facilities for logical inference, and draw on the discrete mathematics of finite partially ordered sets (posets) to develop data representation and algorithms appropriate for the GO. In doing so, we have laid the foundations for a general set of methods to address not just the categorization task, but also other tasks (e.g. distances in ontologies and ontology merger and exchange) in both the GO and other bio-ontologies (such as the Enzyme Commission database or the MEdical Subject Headings) cast as hierarchically structured taxonomic knowledge systems.'),
(71530, 2004, 'bio', 'Filling gaps in a metabolic network using expression information', 'Kharchenko, Peter|Vitkup, Dennis|Church, George M', 'Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.|Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.|Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.', 'United States|United States|United States', 81, 'Algorithms|Computer Simulation|Gene Expression Profiling|Models, Biological|Multienzyme Complexes|Proteome|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/bth930', '15262797', 'The metabolic models of both newly sequenced and well-studied organisms contain reactions for which the enzymes have not been identified yet. We present a computational approach for identifying genes encoding such missing metabolic enzymes in a partially reconstructed metabolic network.'),
(71531, 2004, 'bio', 'Optimal robust non-unique probe selection using Integer Linear Programming', 'Klau, Gunnar W|Rahmann, Sven|Schliep, Alexander|Vingron, Martin|Reinert, Knut', 'Institute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Austria.|Institute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Austria.|Institute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Austria.|Institute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Austria.|Institute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Austria.', 'Austria|Austria|Austria|Austria|Austria', 42, 'Algorithms|Base Sequence|DNA|DNA Probes|Molecular Sequence Data|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Programming, Linear|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bth936', '15262798', 'Besides their prevalent use for analyzing gene expression, microarrays are an efficient tool for biological, medical and industrial applications due to their ability to assess the presence or absence of biological agents, the targets, in a sample. Given a collection of genetic sequences of targets one faces the challenge of finding short oligonucleotides, the probes, which allow detection of targets in a sample. Each hybridization experiment determines whether the probe binds to its corresponding sequence in the target. Depending on the problem, the experiments are conducted using either unique or non-unique probes and usually assume that only one target is present in the sample. The problem at hand is to compute a design, i.e. a minimal set of probes that allows to infer the targets in the sample from the result of the hybridization experiment. If we allow to test for more than one target in the sample, the design of the probe set becomes difficult in the case of non-unique probes.'),
(71532, 2004, 'bio', 'Finding disease specific alterations in the co-expression of genes', 'Kostka, Dennis|Spang, Rainer', 'Max Planck Institute for Molecular Genetics, Berlin, Germany. dennis.kostka@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Berlin, Germany. dennis.kostka@molgen.mpg.de', 'Germany|Germany', 0, 'Algorithms|Biomarkers, Tumor|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Leukemia|Multigene Family|Neoplasm Proteins|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/bth909', '15262799', 'Standard analysis routines for microarray data aim at differentially expressed genes. In this paper, we address the complementary problem of detecting sets of differentially co-expressed genes in two phenotypically distinct sets of expression profiles.'),
(71533, 2004, 'bio', 'An efficient algorithm for detecting frequent subgraphs in biological networks', 'Koyutürk, Mehmet|Grama, Ananth|Szpankowski, Wojciech', 'Department of Computer Sciences, Purdue University, West Lafayette, IN 47907, USA. koyuturk@cs.purdue.edu|Department of Computer Sciences, Purdue University, West Lafayette, IN 47907, USA. koyuturk@cs.purdue.edu|Department of Computer Sciences, Purdue University, West Lafayette, IN 47907, USA. koyuturk@cs.purdue.edu', 'United States|United States|United States', 0, 'Algorithms|Computer Simulation|Gene Expression|Gene Expression Profiling|Models, Biological|Protein Interaction Mapping|Proteome|Signal Transduction|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth919', '15262800', 'With rapidly increasing amount of network and interaction data in molecular biology, the problem of effectively analyzing this data is an important one. Graph theoretic formalisms, commonly used for these analysis tasks, often lead to computationally hard problems due to their relation with subgraph isomorphism.'),
(71534, 2004, 'bio', 'Partial Cox regression analysis for high-dimensional microarray gene expression data', 'Li, Hongzhe|Gui, Jiang', 'Rowe Program in Human Genetics and Department of Statistics, University of California, Davis, CA 95616, USA. hli@ucdavis.edu|Rowe Program in Human Genetics and Department of Statistics, University of California, Davis, CA 95616, USA. hli@ucdavis.edu', 'United States|United States', 99, 'Biomarkers, Tumor|Humans|Lymphoma, B-Cell|Neoplasm Proteins|Prevalence|Prognosis|Proportional Hazards Models|Reproducibility of Results|Risk Assessment|Risk Factors|Sensitivity and Specificity|Survival Analysis|Survival Rate', 'Journal Article', '10.1093/bioinformatics/bth900', '15262801', 'An important application of microarray technology is to predict various clinical phenotypes based on the gene expression profile. Success has been demonstrated in molecular classification of cancer in which different types of cancer serve as categorical outcome variable. However, there has been less research in linking gene expression profile to censored survival outcome such as patients overall survival time or time to cancer relapse. In this paper, we develop a partial Cox regression method for constructing mutually uncorrelated components based on microarray gene expression data for predicting the survival of future patients.'),
(71535, 2004, 'bio', 'A nucleotide substitution model with nearest-neighbour interactions', 'Lunter, Gerton|Hein, Jotun', 'Bioinformatics group, Department of Statistics, University of Oxford, Oxford, UK. lunter@stats.ox.ac.uk|Bioinformatics group, Department of Statistics, University of Oxford, Oxford, UK. lunter@stats.ox.ac.uk', 'United Kingdom|United Kingdom', 26, 'Algorithms|Animals|Base Pair Mismatch|Chromosome Mapping|Computer Simulation|DNA|DNA Mutational Analysis|Genetic Variation|Humans|Mice|Models, Genetic|Nucleotides|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bth901', '15262802', 'It is well known that neighbouring nucleotides in DNA sequences do not mutate independently of each other. In this paper, we introduce a context-dependent substitution model and derive an algorithm to calculate the likelihood of sequences evolving under this model. We use this algorithm to estimate neighbour-dependent substitution rates, as well as rates for dinucleotide substitutions, using a Bayesian sampling procedure. The model is irreversible, giving an arrow to time, and allowing the position of the root between a pair of sequences to be inferred without using out-groups.'),
(71536, 2004, 'bio', 'Striped sheets and protein contact prediction', 'MacCallum, Robert M', 'Stockholm Bioinformatics Center, Stockholm University, Stockholm, Sweden. maccallr@sbc.su.se', 'Sweden', 72, 'Amino Acid Sequence|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth913', '15262803', 'Current approaches to contact map prediction in proteins have focused on amino acid conservation and patterns of mutation at sequentially distant positions. This sequence information is poorly understood and very little progress has been made in this area during recent years.'),
(71537, 2004, 'bio', 'Predicting genetic regulatory response using classification', 'Middendorf, Manuel|Kundaje, Anshul|Wiggins, Chris|Freund, Yoav|Leslie, Christina', 'Department of Physics, Columbia University, NY, NY 10027, USA.|Department of Physics, Columbia University, NY, NY 10027, USA.|Department of Physics, Columbia University, NY, NY 10027, USA.|Department of Physics, Columbia University, NY, NY 10027, USA.|Department of Physics, Columbia University, NY, NY 10027, USA.', 'United States|United States|United States|United States|United States', 0, 'Binding Sites|Chromosome Mapping|Computer Simulation|Gene Expression Regulation|Models, Genetic|Protein Binding|Proteome|Regulatory Elements, Transcriptional|Saccharomyces cerevisiae Proteins|Sequence Analysis, DNA|Signal Transduction|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1093/bioinformatics/bth923', '15262804', 'Studying gene regulatory mechanisms in simple model organisms through analysis of high-throughput genomic data has emerged as a central problem in computational biology. Most approaches in the literature have focused either on finding a few strong regulatory patterns or on learning descriptive models from training data. However, these approaches are not yet adequate for making accurate predictions about which genes will be up- or down-regulated in new or held-out experiments. By introducing a predictive methodology for this problem, we can use powerful tools from machine learning and assess the statistical significance of our predictions.'),
(71538, 2004, 'bio', 'Protein names precisely peeled off free text', 'Mika, Sven|Rost, Burkhard', 'CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA. mika@cubic.bioc.columbia.edu|CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA. mika@cubic.bioc.columbia.edu', 'United States|United States', 0, 'Abstracting and Indexing as Topic|Artificial Intelligence|Dictionaries as Topic|Dictionaries, Chemical as Topic|Information Storage and Retrieval|MEDLINE|Pattern Recognition, Automated|Proteins|Terminology as Topic', 'Evaluation Studies', '10.1093/bioinformatics/bth904', '15262805', 'Automatically identifying protein names from the scientific literature is a pre-requisite for the increasing demand in data-mining this wealth of information. Existing approaches are based on dictionaries, rules and machine-learning. Here, we introduced a novel system that combines a pre-processing dictionary- and rule-based filtering step with several separately trained support vector machines (SVMs) to identify protein names in the MEDLINE abstracts.'),
(71539, 2004, 'bio', 'Inferring quantitative models of regulatory networks from expression data', 'Nachman, I|Regev, A|Friedman, N', 'School of Computer Science & Engineering, Hebrew University, Jerusalem, Israel.|School of Computer Science & Engineering, Hebrew University, Jerusalem, Israel.|School of Computer Science & Engineering, Hebrew University, Jerusalem, Israel.', 'Israel|Israel|Israel', 143, 'Binding Sites|Chromosome Mapping|Computer Simulation|Databases, Protein|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Protein Binding|Proteome|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Signal Transduction|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1093/bioinformatics/bth941', '15262806', 'Genetic networks regulate key processes in living cells. Various methods have been suggested to reconstruct network architecture from gene expression data. However, most approaches are based on qualitative models that provide only rough approximations of the underlying events, and lack the quantitative aspects that are critical for understanding the proper function of biomolecular systems.'),
(71540, 2004, 'bio', 'HyBrow: a prototype system for computer-aided hypothesis evaluation', 'Racunas, S A|Shah, N H|Albert, I|Fedoroff, N V', 'The Huck Institute for Life Sciences, Penn State University, University Park, PA 16801, USA.|The Huck Institute for Life Sciences, Penn State University, University Park, PA 16801, USA.|The Huck Institute for Life Sciences, Penn State University, University Park, PA 16801, USA.|The Huck Institute for Life Sciences, Penn State University, University Park, PA 16801, USA.', 'United States|United States|United States|United States', 0, 'Computational Biology|Databases, Protein|Galactose|Information Storage and Retrieval|Models, Biological|Pilot Projects|Research Design|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Systems Integration', 'Evaluation Studies', '10.1093/bioinformatics/bth905', '15262807', 'Experimental design, hypothesis-testing and model-building in the current data-rich environment require the biologists to collect, evaluate and integrate large amounts of information of many disparate kinds. Developing a unified framework for the representation and conceptual integration of biological data and processes is a major challenge in bioinformatics because of the variety of available data and the different levels of detail at which biological processes can be considered.'),
(71541, 2004, 'bio', 'Reconstructing tumor amplisomes', 'Raphael, Benjamin J|Pevzner, Pavel A', 'Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093-0114, USA. braphael@ucsd.edu|Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093-0114, USA. braphael@ucsd.edu', 'United States|United States', 0, 'Algorithms|Animals|Base Sequence|Chromosome Mapping|DNA, Circular|DNA, Neoplasm|Humans|Molecular Sequence Data|Neoplasms|Repetitive Sequences, Nucleic Acid|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bth931', '15262808', 'Duplication of genomic sequences is a common phenomenon in tumor cells. While many duplications associated with tumors have been identified (e.g. via techniques such as CGH), both the organization of the duplicated sequences and the process that leads to these duplications are less clear. One mechanism that has been observed to lead to duplication is the extraction of DNA from the chromosomes and aggregation of this DNA into small, independently replicating linear or circular DNA sequences (amplisomes). Parts of these amplisomes may later be reinserted back into the main chromosomes leading to duplication. Although amplisomes are known to play an important role in tumorigenesis, their architecture and even size remain largely unknown.'),
(71542, 2004, 'bio', 'Predicting protein-peptide interactions via a network-based motif sampler', 'Reiss, David J|Schwikowski, Benno', 'Institute for Systems Biology, Seattle, WA 98103-8904, USA. dreiss@systemsbiology.org|Institute for Systems Biology, Seattle, WA 98103-8904, USA. dreiss@systemsbiology.org', 'United States|United States', 0, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Peptides|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth922', '15262809', 'Many protein-protein interactions are mediated by peptide recognition modules (PRMs), compact domains that bind to short peptides, and play a critical role in a wide array of biological processes. Recent experimental protein interaction data provide us with an opportunity to examine whether we may explain, or even predict their interactions by computational sequence analysis. Such a question was recently posed by the use of random peptide screens to characterize the ligands of one such PRM, the SH3 domain.'),
(71543, 2004, 'bio', 'Robust inference of groups in gene expression time-courses using mixtures of HMMs', 'Schliep, Alexander|Steinhoff, Christine|Schönhuth, Alexander', 'Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. schliep@molgen.mpg.de|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. schliep@molgen.mpg.de|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. schliep@molgen.mpg.de', 'Germany|Germany|Germany', 0, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Computer Simulation|Gene Expression|Gene Expression Profiling|HeLa Cells|Humans|Markov Chains|Models, Genetic|Multigene Family|Neoplasm Proteins|Neoplasms', 'Journal Article', '10.1093/bioinformatics/bth937', '15262810', 'Genetic regulation of cellular processes is frequently investigated using large-scale gene expression experiments to observe changes in expression over time. This temporal data poses a challenge to classical distance-based clustering methods due to its horizontal dependencies along the time-axis. We propose to use hidden Markov models (HMMs) to explicitly model these time-dependencies. The HMMs are used in a mixture approach that we show to be superior over clustering. Furthermore, mixtures are a more realistic model of the biological reality, as an unambiguous partitioning of genes into clusters of unique functional assignment is impossible. Use of the mixture increases robustness with respect to noise and allows an inference of groups at varying level of assignment ambiguity. A simple approach, partially supervised learning, allows to benefit from prior biological knowledge during the training. Our method allows simultaneous analysis of cyclic and non-cyclic genes and copes well with noise and missing values.'),
(71544, 2004, 'bio', 'Mining MEDLINE for implicit links between dietary substances and diseases', 'Srinivasan, Padmini|Libbus, Bisharah', 'School of Library and Information Science, University of Iowa, Iowa City, IA 52242, USA. padmini-srinivasan@uiowa.edu|School of Library and Information Science, University of Iowa, Iowa City, IA 52242, USA. padmini-srinivasan@uiowa.edu', 'United States|United States', 0, 'Abstracting and Indexing as Topic|Artificial Intelligence|Crohn Disease|Curcumin|Diet Therapy|Humans|MEDLINE|Natural Language Processing|Retinal Diseases|Spinal Cord Diseases|Statistics as Topic', 'Evaluation Studies', '10.1093/bioinformatics/bth914', '15262811', 'Text mining systems aim at knowledge discovery from text collections. This work presents our text mining algorithm and demonstrates its use to uncover information that could form the basis of new hypotheses. In particular, we use it to discover novel uses for Curcuma longa, a dietary substance, which is highly regarded for its therapeutic properties in Asia.'),
(71545, 2004, 'bio', 'Prediction of class I T-cell epitopes: evidence of presence of immunological hot spots inside antigens', 'Srinivasan, K N|Zhang, G L|Khan, A M|August, J T|Brusic, V', 'Division of Biomedical Sciences, Johns Hopkins Medicine in Singapore, The Gemini, Singapore.|Division of Biomedical Sciences, Johns Hopkins Medicine in Singapore, The Gemini, Singapore.|Division of Biomedical Sciences, Johns Hopkins Medicine in Singapore, The Gemini, Singapore.|Division of Biomedical Sciences, Johns Hopkins Medicine in Singapore, The Gemini, Singapore.|Division of Biomedical Sciences, Johns Hopkins Medicine in Singapore, The Gemini, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore', 0, 'Algorithms|Computer Simulation|Epitope Mapping|Epitopes, T-Lymphocyte|Histocompatibility Antigens Class I|Models, Immunological|Oncogene Proteins, Viral|Papillomavirus E7 Proteins|Peptides|Protein Binding', 'Journal Article', '10.1093/bioinformatics/bth943', '15262812', 'Processing and presentation of major histocompatibility complex class I antigens to cytotoxic T-lymphocytes is crucial for immune surveillance against intracellular bacteria, parasites, viruses and tumors. Identification of antigenic regions on pathogen proteins will play a pivotal role in designer vaccine immunotherapy. We have developed a system that not only identifies high binding T-cell antigenic epitopes, but also class I T-cell antigenic clusters termed immunological hot spots.'),
(71546, 2004, 'bio', 'Exploring Williams-Beuren syndrome using myGrid', 'Stevens, R D|Tipney, H J|Wroe, C J|Oinn, T M|Senger, M|Lord, P W|Goble, C A|Brass, A|Tassabehji, M', 'Department of Computer Science, University of Manchester, Manchester, UK. robert.stevens@cs.man.ac.uk|Department of Computer Science, University of Manchester, Manchester, UK. robert.stevens@cs.man.ac.uk|Department of Computer Science, University of Manchester, Manchester, UK. robert.stevens@cs.man.ac.uk|Department of Computer Science, University of Manchester, Manchester, UK. robert.stevens@cs.man.ac.uk|Department of Computer Science, University of Manchester, Manchester, UK. robert.stevens@cs.man.ac.uk|Department of Computer Science, University of Manchester, Manchester, UK. robert.stevens@cs.man.ac.uk|Department of Computer Science, University of Manchester, Manchester, UK. robert.stevens@cs.man.ac.uk|Department of Computer Science, University of Manchester, Manchester, UK. robert.stevens@cs.man.ac.uk|Department of Computer Science, University of Manchester, Manchester, UK. robert.stevens@cs.man.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 76, 'Algorithms|Chromosome Mapping|Computer Graphics|Genetic Predisposition to Disease|Internet|Sequence Analysis, DNA|Software|User-Computer Interface|Williams Syndrome', 'Journal Article', '10.1093/bioinformatics/bth944', '15262813', 'In silico experiments necessitate the virtual organization of people, data, tools and machines. The scientific process also necessitates an awareness of the experience base, both of personal data as well as the wider context of work. The management of all these data and the co-ordination of resources to manage such virtual organizations and the data surrounding them needs significant computational infra-structure support.'),
(71547, 2004, 'bio', 'Tracking repeats using significance and transitivity', 'Szklarczyk, Radek|Heringa, Jaap', 'Centre for Integrative Bioinformatics (IBIVU), Faculty of Sciences and Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1081A, Amsterdam, The Netherlands. radek@cs.vu.nl|Centre for Integrative Bioinformatics (IBIVU), Faculty of Sciences and Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1081A, Amsterdam, The Netherlands. radek@cs.vu.nl', 'Netherlands|Netherlands', 0, 'Algorithms|Amino Acid Sequence|Evolution, Molecular|Molecular Sequence Data|Proteins|Repetitive Sequences, Amino Acid|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth911', '15262814', 'Internal repeats in coding sequences correspond to structural and functional units of proteins. Moreover, duplication of fragments of coding sequences is known to be a mechanism to facilitate evolution. Identification of repeats is crucial to shed light on the function and structure of proteins, and explain their evolutionary past. The task is difficult because during the course of evolution many repeats diverged beyond recognition.'),
(71548, 2004, 'bio', 'Genomic features in the breakpoint regions between syntenic blocks', 'Trinh, Phil|McLysaght, Aoife|Sankoff, David', 'Hillcrest High School, Ottawa, Canada.|Hillcrest High School, Ottawa, Canada.|Hillcrest High School, Ottawa, Canada.', 'Canada|Canada|Canada', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Conserved Sequence|Evolution, Molecular|Genetic Variation|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Synteny', 'Journal Article', '10.1093/bioinformatics/bth934', '15262815', 'We study the largely unaligned regions between the syntenic blocks conserved in humans and mice, based on data extracted from the UCSC genome browser. These regions contain evolutionary breakpoints caused by inversion, translocation and other processes.'),
(71549, 2004, 'bio', 'Learning kernels from biological networks by maximizing entropy', 'Tsuda, Koji|Noble, William Stafford', 'Max Planck Institute for Biological Cybernetics, Tübingen, Germany.|Max Planck Institute for Biological Cybernetics, Tübingen, Germany.', 'Germany|Germany', 0, 'Algorithms|Artificial Intelligence|Computer Simulation|Models, Biological|Pattern Recognition, Automated|Protein Interaction Mapping|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/bth906', '15262816', 'The diffusion kernel is a general method for computing pairwise distances among all nodes in a graph, based on the sum of weighted paths between each pair of nodes. This technique has been used successfully, in conjunction with kernel-based learning methods, to draw inferences from several types of biological networks.');
