INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70757, 2003, 'bio', 'Quantitative quality control in microarray experiments and the application in data filtering, normalization and false positive rate prediction', 'Wang, Xujing|Hessner, Martin J|Wu, Yan|Pati, Nirupma|Ghosh, Soumitra', 'Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, Medical College and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, Medical College and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, Medical College and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, Medical College and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, Medical College and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|False Positive Reactions|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Signal Processing, Computer-Assisted|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/btg154', '12874045', 'Data preprocessing including proper normalization and adequate quality control before complex data mining is crucial for studies using the cDNA microarray technology. We have developed a simple procedure that integrates data filtering and normalization with quantitative quality control of microarray experiments. Previously we have shown that data variability in a microarray experiment can be very well captured by a quality score q(com) that is defined for every spot, and the ratio distribution depends on q(com). Utilizing this knowledge, our data-filtering scheme allows the investigator to decide on the filtering stringency according to desired data variability, and our normalization procedure corrects the q(com)-dependent dye biases in terms of both the location and the spread of the ratio distribution. In addition, we propose a statistical model for false positive rate determination based on the design and the quality of a microarray experiment. The model predicts that a lower limit of 0.5 for the replicate concordance rate is needed in order to be certain of true positives. Our work demonstrates the importance and advantages of having a quantitative quality control scheme for microarrays.'),
(70758, 2003, 'bio', 'Noise sampling method: an ANOVA approach allowing robust selection of differentially regulated genes measured by DNA microarrays', 'Draghici, Sorin|Kulaeva, Olga|Hoff, Bruce|Petrov, Anton|Shams, Soheil|Tainsky, Michael A', 'Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI, 48202, USA. sod@cs.wayne.edu|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI, 48202, USA. sod@cs.wayne.edu|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI, 48202, USA. sod@cs.wayne.edu|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI, 48202, USA. sod@cs.wayne.edu|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI, 48202, USA. sod@cs.wayne.edu|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI, 48202, USA. sod@cs.wayne.edu', 'United States|United States|United States|United States|United States|United States', 50, 'Algorithms|Analysis of Variance|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Humans|Li-Fraumeni Syndrome|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/btg165', '12874046', 'A crucial step in microarray data analysis is the selection of subsets of interesting genes from the initial set of genes. In many cases, especially when comparing a specific condition to a reference, the genes of interest are those which are differentially expressed. Two common methods for gene selection are: (a) selection by fold difference (at least n fold variation) and (b) selection by altered ratio (at least n standard deviations away from the mean ratio).'),
(70759, 2003, 'bio', 'Estimation of transformation parameters for microarray data', 'Durbin, Blythe|Rocke, David M', 'Department of Statistics, UC Davis, Davis, CA 95616, USA. bpdurbin@ucdavis.edu|Department of Statistics, UC Davis, Davis, CA 95616, USA. bpdurbin@ucdavis.edu', 'United States|United States', 18, 'Algorithms|Animals|Computer Simulation|Gene Expression Profiling|Leukemia|Likelihood Functions|Linear Models|Male|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Rats|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg178', '12874047', 'Durbin et al. (2002), Huber et al. (2002) and Munson (2001) independently introduced a family of transformations (the generalized-log family) which stabilizes the variance of microarray data up to the first order. We introduce a method for estimating the transformation parameter in tandem with a linear model based on the procedure outlined in Box and Cox (1964). We also discuss means of finding transformations within the generalized-log family which are optimal under other criteria, such as minimum residual skewness and minimum mean-variance dependency.'),
(70760, 2003, 'bio', 'Exact significance levels for the maximum chi(2) method of detecting recombination', 'Spencer, M', 'Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge CB2 1QW, England. ms379@cam.ac.uk', '-', 3, 'Algorithms|Chi-Square Distribution|Computer Simulation|Gene Expression Profiling|Genetic Variation|Likelihood Functions|Models, Genetic|Models, Statistical|Recombination, Genetic|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg171', '12874048', 'Maynard Smiths maximum chi(2) method is a useful tool for detecting recombination. Significance testing is usually carried out by random permutation, which may require a large amount of computer time. I describe an exact algorithm.'),
(70761, 2003, 'bio', 'Computational analysis of stop codon readthrough in Dmelanogaster', 'Sato, Misaki|Umeki, Hitomi|Saito, Rintaro|Kanai, Akio|Tomita, Masaru', 'Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0017, Japan.|Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0017, Japan.|Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0017, Japan.|Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0017, Japan.|Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0017, Japan.', 'Japan|Japan|Japan|Japan|Japan', 10, 'Algorithms|Animals|Base Sequence|Codon, Terminator|Drosophila Proteins|Drosophila melanogaster|Gene Expression Profiling|Gene Expression Regulation|Molecular Sequence Data|Protein Biosynthesis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg183', '12874049', 'Readthrough is an unusual process in which a stop codon is misread or skipped. Recently it has been shown that some translation is regulated by the readthrough reactions although the complete mechanism is not clear. Therefore, the discovery of readthrough genes is important for further investigation of their cellular roles, which may provide additional insights into the mechanism of translational regulation.'),
(70762, 2003, 'bio', 'Identifying property based sequence motifs in protein families and superfamilies: application to DNase-1 related endonucleases', 'Mathura, Venkatarajan S|Schein, Catherine H|Braun, Werner', 'Sealy Center for Structural Biology, Department of Human Biological Chemistry and Genetics, University of Texas Medical Branch, Galveston, TX 77555-1157, USA.|Sealy Center for Structural Biology, Department of Human Biological Chemistry and Genetics, University of Texas Medical Branch, Galveston, TX 77555-1157, USA.|Sealy Center for Structural Biology, Department of Human Biological Chemistry and Genetics, University of Texas Medical Branch, Galveston, TX 77555-1157, USA.', 'United States|United States|United States', 33, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Conserved Sequence|Databases, Protein|Deoxyribonucleases, Type I Site-Specific|Endonucleases|Humans|Molecular Sequence Data|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/btg164', '12874050', 'Identification of short conserved sequence motifs common to a protein family or superfamily can be more useful than overall sequence similarity in suggesting the function of novel gene products. Locating motifs still requires expert knowledge, as automated methods using stringent criteria may not differentiate subtle similarities from statistical noise.'),
(70763, 2003, 'bio', 'Alignment of BLAST high-scoring segment pairs based on the longest increasing subsequence algorithm', 'Zhang, Hongyu', 'Celera Genomics, 45 West Gude Drive, Rockville, MD 20850, USA. me@hongyu.org', 'United States', 26, 'Algorithms|Base Pair Mismatch|Base Pairing|Base Sequence|Gene Expression Profiling|Humans|Molecular Sequence Data|National Library of Medicine (U.S.)|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|United States', 'Comparative Study', '10.1093/bioinformatics/btg168', '12874051', 'The popular BLAST algorithm is based on a local similarity search strategy, so its high-scoring segment pairs (HSPs) do not have global alignment information. When scientists use BLAST to search for a target protein or DNA sequence in a huge database like the human genome map, the existence of repeated fragments, homologues or pseudogenes in the genome often makes the BLAST result filled with redundant HSPs. Therefore, we need a computational strategy to alleviate this problem.'),
(70764, 2003, 'bio', 'Increased coverage obtained by combination of methods for protein sequence database searching', 'Webber, Caleb|Barton, Geoffrey J', 'EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, England, UK.|EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, England, UK.', 'United Kingdom|United Kingdom', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Systems Integration', 'Comparative Study', '10.1093/bioinformatics/btg156', '12874052', 'Sequence alignment methods that compare two sequences (pairwise methods) are important tools for the detection of biological sequence relationships. In genome annotation, multiple methods are often run and agreement between methods taken as confirmation. In this paper, we assess the advantages of combining search methods by comparing seven pairwise alignment methods, including three local dynamic programming algorithms (PRSS, SSEARCH and SCANPS), two global dynamic programming algorithms (GSRCH and AMPS) and two heuristic approximations (BLAST and FASTA), individually and by pairwise intersection and union of their result lists at equal p-value cut-offs.'),
(70765, 2003, 'bio', 'SATCHMO: sequence alignment and tree construction using hidden Markov models', 'Edgar, Robert C|Sjölander, Kimmen', '195 Roque Moraes Drive, Mill Valley, CA 94941, USA. bob@drive5.com|195 Roque Moraes Drive, Mill Valley, CA 94941, USA. bob@drive5.com', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Gene Expression Profiling|Markov Chains|Models, Genetic|Models, Statistical|Molecular Sequence Data|Protein Structure, Tertiary|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/btg158', '12874053', 'Aligning multiple proteins based on sequence information alone is challenging if sequence identity is low or there is a significant degree of structural divergence. We present a novel algorithm (SATCHMO) that is designed to address this challenge. SATCHMO simultaneously constructs a tree and a set of multiple sequence alignments, one for each internal node of the tree. The alignment at a given node contains all sequences within its sub-tree, and predicts which positions in those sequences are alignable and which are not. Aligned regions therefore typically get shorter on a path from a leaf to the root as sequences diverge in structure. Current methods either regard all positions as alignable (e.g. ClustalW), or align only those positions believed to be homologous across all sequences (e.g. profile HMM methods), by contrast SATCHMO makes different predictions of alignable regions in different subgroups. SATCHMO generates profile hidden Markov models at each node, these are used to determine branching order, to align sequences and to predict structurally alignable regions.'),
(70766, 2003, 'bio', 'GeneTRACE-reconstruction of gene content of ancestral species', 'Kunin, Victor|Ouzounis, Christos A', 'Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.', 'United Kingdom|United Kingdom', 0, 'Algorithms|Computer Simulation|Evolution, Molecular|Gene Expression Profiling|Genetic Variation|Genome|Linear Models|Models, Genetic|Models, Statistical|Phylogeny|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg174', '12874054', 'While current computational methods allow the reconstruction of individual ancestral protein sequences, reconstruction of complete gene content of ancestral species is not yet an established task. In this paper, we describe GENETRACE, an efficient linear-time algorithm that allows the reconstruction of evolutionary history of individual protein families as well as the complete gene content of ancestral species. The performance of the method was validated with a simulated evolution program called SimulEv. Our results indicate that given a set of correct phylogenetic profiles and a correct species tree, ancestral gene content can be reconstructed with sensitivity and selectivity of more than 90%. SimulEv simulations were also used to evaluate performance of the reconstruction of gene content-based phylogenetic trees, suggesting that these trees may be accurate at the terminal branches but suffer from long branch attraction near the root of the tree.'),
(70767, 2003, 'bio', 'MeKE: discovering the functions of gene products from biomedical literature via sentence alignment', 'Chiang, Jung-Hsien|Yu, Hsu-Chun', 'Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan, ROC. jchiang@mail.ncku.edu.tw|Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan, ROC. jchiang@mail.ncku.edu.tw', '-|-', 0, 'Biomedical Research|Cluster Analysis|Database Management Systems|Databases, Genetic|Databases, Protein|Documentation|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Proteins|Software|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/btg160', '12874055', 'Research on roles of gene products in cells is accumulating and changing rapidly, but most of the results are still reported in text form and are not directly accessible by computers. To expedite the progress of functional bioinformatics, it is, therefore, important to efficiently process large amounts of biomedical literature and transform the knowledge extracted into a structured format usable by biologists and medical researchers. Our aim was to develop an intelligent text-mining system that will extract from biomedical documents knowledge about the functions of gene products and thus facilitate computing with function.'),
(70768, 2003, 'bio', 'The connectivity structure, giant strong component and centrality of metabolic networks', 'Ma, Hong-Wu|Zeng, An-Ping', 'Department of Genome Analysis,GBF - German Research Center for Biotechnology, Mascheroder Weg 1, 38124 Braunschweig, Germany.|Department of Genome Analysis,GBF - German Research Center for Biotechnology, Mascheroder Weg 1, 38124 Braunschweig, Germany.', 'Germany|Germany', 0, 'Bacteria|Cell Physiological Phenomena|Computer Simulation|Energy Metabolism|Models, Biological|Proteome|Proteomics|Species Specificity', 'Evaluation Studies', '10.1093/bioinformatics/btg177', '12874056', 'Structural and functional analysis of genome-based large-scale metabolic networks is important for understanding the design principles and regulation of the metabolism at a system level. The metabolic network is conventionally considered to be highly integrated and very complex. A rational reduction of the metabolic network to its core structure and a deeper understanding of its functional modules are important.'),
(70769, 2003, 'bio', 'An adjustable-threshold algorithm for the identification of objects in three-dimensional images', 'Ponomarev, Artem L|Davis, Ronald L', 'Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA. artemp@bcm.tcm.edu|Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA. artemp@bcm.tcm.edu', 'United States|United States', 12, 'Algorithms|Anatomy, Cross-Sectional|Animals|Brain|Cell Nucleus|Differential Threshold|Drosophila melanogaster|Image Enhancement|Image Interpretation, Computer-Assisted|Imaging, Three-Dimensional|Microscopy, Fluorescence, Multiphoton|Neurons|Pattern Recognition, Automated', 'Evaluation Studies', '10.1093/bioinformatics/btg176', '12874057', 'To develop a highly accurate, practical and fast automated segmentation algorithm for three-dimensional images containing biological objects. To test the algorithm on images of the Drosophila brain, and identify, count and determine the locations of neurons in the images.'),
(70770, 2003, 'bio', 'Which genetic loci have greater population assignment power?', 'Banks, Michael A|Eichert, Will|Olsen, Jeffrey B', 'Coastal Oregon Marine Experiment Station, Hatfield Marine Science Center, Oregon State University, 2030 SE Marine Science Drive, Newport, OR 97365-5229, USA. Michael.Banks@oregonstate.edu|Coastal Oregon Marine Experiment Station, Hatfield Marine Science Center, Oregon State University, 2030 SE Marine Science Drive, Newport, OR 97365-5229, USA. Michael.Banks@oregonstate.edu|Coastal Oregon Marine Experiment Station, Hatfield Marine Science Center, Oregon State University, 2030 SE Marine Science Drive, Newport, OR 97365-5229, USA. Michael.Banks@oregonstate.edu', 'United States|United States|United States', 0, 'Algorithms|Animals|Evolution, Molecular|Gene Expression Profiling|Gene Frequency|Genetic Variation|Genetics, Population|Polymorphism, Genetic|Quantitative Trait Loci|Salmon|Software', 'Comparative Study', '10.1093/bioinformatics/btg172', '12874058', 'WHICHLOCI is a program that determines the relative discriminatory power of alternate genetic loci and loci combinations for population assignment of individuals.'),
(70771, 2003, 'bio', 'Q-Gene: processing quantitative real-time RT-PCR data', 'Simon, Perikles', 'Section for Neurobiology of the Eye, University Eye Hospital Tuebingen, Calwerstr. 7/1, 72076 Tuebingen, Germany. perikles@uni-tuebingen.de', 'Germany', 535, 'Algorithms|Gene Expression Profiling|Online Systems|Reproducibility of Results|Reverse Transcriptase Polymerase Chain Reaction|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, RNA|Software', 'Comparative Study', '10.1093/bioinformatics/btg157', '12874059', 'Q-Gene is an application for the processing of quantitative real-time RT-PCR data. It offers the user the possibility to freely choose between two principally different procedures to calculate normalized gene expressions as either means of Normalized Expressions or Mean Normalized Expressions. In this contribution it will be shown that the calculation of Mean Normalized Expressions has to be used for processing simplex PCR data, while multiplex PCR data should preferably be processed by calculating Normalized Expressions. The two procedures, which are currently in widespread use and regarded as more or less equivalent alternatives, should therefore specifically be applied according to the quantification procedure used.'),
(70772, 2003, 'bio', 'GABI-Kat SimpleSearch: a flanking sequence tag (FST) database for the identification of T-DNA insertion mutants in Arabidopsis thaliana', 'Li, Yong|Rosso, Mario G|Strizhov, Nicolai|Viehoever, Prisca|Weisshaar, Bernd', 'Max Planck Institute for Plant Breeding Research, Carl-von-Linne-Weg 10, D-50829 Koeln, Germany.|Max Planck Institute for Plant Breeding Research, Carl-von-Linne-Weg 10, D-50829 Koeln, Germany.|Max Planck Institute for Plant Breeding Research, Carl-von-Linne-Weg 10, D-50829 Koeln, Germany.|Max Planck Institute for Plant Breeding Research, Carl-von-Linne-Weg 10, D-50829 Koeln, Germany.|Max Planck Institute for Plant Breeding Research, Carl-von-Linne-Weg 10, D-50829 Koeln, Germany.', 'Germany|Germany|Germany|Germany|Germany', 54, 'Arabidopsis|DNA Transposable Elements|DNA, Bacterial|Database Management Systems|Databases, Nucleic Acid|Expressed Sequence Tags|Gene Expression Profiling|Information Storage and Retrieval|Internet|Mutagenesis, Insertional|Plants, Genetically Modified|Sequence Analysis, DNA|Terminal Repeat Sequences|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg170', '12874060', 'GABI-Kat SimpleSearch is a database of flanking sequence tags (FSTs) of T-DNA mutagenized Arabidopsis thaliana lines that were generated by the GABI-Kat project. Sequences flanking the T-DNA insertion sites were aligned to the A.thaliana genome sequence, annotated with information about the FST, the insertion site and the line from which the FST was derived. A web interface permits text-based as well as sequence-based searches for relevant insertions. GABI-Kat SimpleSearch aims to help biologists to quickly find T-DNA insertion mutants for their research.'),
(70773, 2003, 'bio', '2HAPI: a microarray data analysis system', 'Fink, J Lynn|Drewes, Scott|Patel, Hiren|Welsh, John B|Masys, Daniel R|Corbeil, Jacques|Gribskov, Michael', 'San Diego Supercomputer Center, Department of Biology, University of California, San Diego, 9500 Gilman Drive, San Diego, CA 92093-0537, USA.|San Diego Supercomputer Center, Department of Biology, University of California, San Diego, 9500 Gilman Drive, San Diego, CA 92093-0537, USA.|San Diego Supercomputer Center, Department of Biology, University of California, San Diego, 9500 Gilman Drive, San Diego, CA 92093-0537, USA.|San Diego Supercomputer Center, Department of Biology, University of California, San Diego, 9500 Gilman Drive, San Diego, CA 92093-0537, USA.|San Diego Supercomputer Center, Department of Biology, University of California, San Diego, 9500 Gilman Drive, San Diego, CA 92093-0537, USA.|San Diego Supercomputer Center, Department of Biology, University of California, San Diego, 9500 Gilman Drive, San Diego, CA 92093-0537, USA.|San Diego Supercomputer Center, Department of Biology, University of California, San Diego, 9500 Gilman Drive, San Diego, CA 92093-0537, USA.', 'United States|United States|United States|United States|United States|United States|United States', 6, 'Algorithms|Cluster Analysis|Database Management Systems|Databases, Nucleic Acid|Gene Expression Profiling|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Promoter Regions, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btg169', '12874061', '2HAPI (version 2 of High density Array Pattern Interpreter) is a web-based, publicly-available analytical tool designed to aid researchers in microarray data analysis. 2HAPI includes tools for searching, manipulating, visualizing, and clustering the large sets of data generated by microarray experiments. Other features include association of genes with NCBI information and linkage to external data resources. Unique to 2HAPI is the ability to retrieve upstream sequences of co-regulated genes for promoter analysis using MEME (Multiple Expectation-maximization for Motif Elicitation)'),
(70774, 2003, 'bio', 'POAVIZ: a Partial order multiple sequence alignment visualizer', 'Grasso, Catherine|Quist, Michael|Ke, Kevin|Lee, Christopher', 'Molecular Biology Institute, Center for Genomics and Proteomics, Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095-1570, USA.|Molecular Biology Institute, Center for Genomics and Proteomics, Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095-1570, USA.|Molecular Biology Institute, Center for Genomics and Proteomics, Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095-1570, USA.|Molecular Biology Institute, Center for Genomics and Proteomics, Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095-1570, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Gene Expression Profiling|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg175', '12874062', 'POAVIZ creates a visualization of a multiple sequence alignment that makes clear the overall structure of how sequences match and diverge in the alignment. POAVIZ can construct visualizations from any multiple sequence alignment source (e.g. PIR and CLUSTAL formats), and is valuable for revealing complex branching structure (such as domains, large-scale insertions / deletions or recombinations), especially in partnership with the Partial Order Alignment (POA) multiple sequence alignment program.'),
(70775, 2003, 'bio', 'Genome visualization made fast and simple', 'Gibson, René|Smith, Douglas R', 'Genome Therapeutics Corporation, Waltham, Massachusetts, 02453, USA.|Genome Therapeutics Corporation, Waltham, Massachusetts, 02453, USA.', 'United States|United States', 11, 'Algorithms|Computer Graphics|Database Management Systems|Genome|Genomics|Hypermedia|Information Storage and Retrieval|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg152', '12874063', 'The easiest way to gain a quick overall understanding of genomic data is with a visual display that allows the user to view information about an entire genome or chromosome at once. We have constructed GenomePlot, a Perl/Tk script with a series of modules that allow us to display many types of information simultaneously. Menu options allow the user to zoom to the desired view of the data and to print or save the image to a file to produce publication quality illustrations.'),
(70776, 2003, 'bio', 'COmplete GENome Tracking (COGENT): a flexible data environment for computational genomics', 'Janssen, Paul|Enright, Anton J|Audit, Benjamin|Cases, Ildefonso|Goldovsky, Leon|Harte, Nicola|Kunin, Victor|Ouzounis, Christos A', 'Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Welcome Trust Genome Campus, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Welcome Trust Genome Campus, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Welcome Trust Genome Campus, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Welcome Trust Genome Campus, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Welcome Trust Genome Campus, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Welcome Trust Genome Campus, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Welcome Trust Genome Campus, Cambridge CB10 1SD, UK.|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Welcome Trust Genome Campus, Cambridge CB10 1SD, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 33, 'Computational Biology|Database Management Systems|Databases, Genetic|Documentation|Genomics|Information Storage and Retrieval|Internet|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/btg161', '12874064', 'We present a database of fully sequenced and published genomes to facilitate the re-distribution of data and ensure reproducibility of results in the field of computational genomics. For its design we have implemented an extremely simple yet powerful schema to allow linking of genome sequence data to other resources.'),
(70777, 2003, 'bio', 'The binding interface database (BID): a compilation of amino acid hot spots in protein interfaces', 'Fischer, T B|Arunachalam, K V|Bailey, D|Mangual, V|Bakhru, S|Russo, R|Huang, D|Paczkowski, M|Lalchandani, V|Ramachandra, C|Ellison, B|Galer, S|Shapley, J|Fuentes, E|Tsai, J', 'Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, USA.|Department of Biochemistry & Biophysics, Texas A&M University, 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|United States|United States|United States', 0, 'Amino Acid Sequence|Amino Acids|Binding Sites|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Molecular Sequence Data|Mutation|Protein Binding|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btg163', '12874065', 'To make information about protein interactive function easily accessible, we are mining the primary scientific literature for detailed data about protein interfaces. The Binding Interface Database (BID) organizes the vast amount of protein interaction information into tables, graphical contact maps and descriptive functional profiles. Currently data on 170 interacting protein pairs are available with over 1300 mutations described.'),
(70778, 2003, 'bio', 'PseuRECA: genome annotation and gene context analysis for Pseudomonas aeruginosa PAO1', 'Weinel, Christian|Ermolaeva, Maria D|Ouzounis, Christos', 'Klinische Forschergruppe, OE6711, Medizinische Hochschule Hannover, Carl-Neuberg-Strasse 1, D-30625 Hannover, Germany. weinel.christian@mh-hannover.de|Klinische Forschergruppe, OE6711, Medizinische Hochschule Hannover, Carl-Neuberg-Strasse 1, D-30625 Hannover, Germany. weinel.christian@mh-hannover.de|Klinische Forschergruppe, OE6711, Medizinische Hochschule Hannover, Carl-Neuberg-Strasse 1, D-30625 Hannover, Germany. weinel.christian@mh-hannover.de', 'Germany|Germany|Germany', 5, 'Amino Acid Sequence|Databases, Protein|Documentation|Genome, Bacterial|Information Storage and Retrieval|Molecular Sequence Data|Pseudomonas aeruginosa|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btg184', '12912824', '-'),
(70779, 2003, 'bio', 'Comprehensive aligned sequence construction for automated design of effective probes (CASCADE-P) using 16S rDNA', 'DeSantis, T Z|Dubosarskiy, I|Murray, S R|Andersen, G L', 'Center for Environmental Biotechnology, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Mail Stop 70A-3317, Berkeley, CA 94720, USA.|Center for Environmental Biotechnology, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Mail Stop 70A-3317, Berkeley, CA 94720, USA.|Center for Environmental Biotechnology, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Mail Stop 70A-3317, Berkeley, CA 94720, USA.|Center for Environmental Biotechnology, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Mail Stop 70A-3317, Berkeley, CA 94720, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Bacillus anthracis|Cluster Analysis|Computer-Aided Design|DNA Probes|Equipment Design|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|RNA, Ribosomal, 16S|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Staphylococcus aureus', 'Comparative Study', '10.1093/bioinformatics/btg200', '12912825', 'Prokaryotic organisms have been identified utilizing the sequence variation of the 16S rRNA gene. Variations steer the design of DNA probes for the detection of taxonomic groups or specific organisms. The long-term goal of our project is to create probe arrays capable of identifying 16S rDNA sequences in unknown samples. This necessitated the authentication, categorization and alignment of the >75 000 publicly available 16S sequences. Preferably, the entire process should be computationally administrated so the aligned collection could periodically absorb 16S rDNA sequences from the public records. A complete multiple sequence alignment would provide a foundation for computational probe selection and facilitates microbial taxonomy and phylogeny.'),
(70780, 2003, 'bio', 'A comparison of statistical methods for analysis of high density oligonucleotide array data', 'Rajagopalan, Dilip', 'Bioinformatics Sciences, GlaxoSmithKline Pharmaceuticals R&D, 709 Swedeland Road, King of Prussia, PA 19406-0939, USA. dilip.2.rajagopalan@gsk.com', 'United States', 0, 'Algorithms|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg202', '12912826', 'Gene expression profiling has become an invaluable tool in functional genomics. A wide variety of statistical methods have been employed to analyze the data generated in experiments using Affymetrix GeneChip microarrays. It is important to understand the relative performance of these methods in terms of accuracy in detecting and quantifying relative gene expression levels and changes in gene expression.'),
(70781, 2003, 'bio', 'Differential expression in SAGE: accounting for normal between-library variation', 'Baggerly, Keith A|Deng, Li|Morris, Jeffrey S|Aldaz, C Marcelo', 'Department of Biostatistics, UT M.D. Anderson Cancer Center, 1515 Holcombe Blvd, Box 447, Houston, TX 77030-4009, USA. kabagg@mdanderson.org|Department of Biostatistics, UT M.D. Anderson Cancer Center, 1515 Holcombe Blvd, Box 447, Houston, TX 77030-4009, USA. kabagg@mdanderson.org|Department of Biostatistics, UT M.D. Anderson Cancer Center, 1515 Holcombe Blvd, Box 447, Houston, TX 77030-4009, USA. kabagg@mdanderson.org|Department of Biostatistics, UT M.D. Anderson Cancer Center, 1515 Holcombe Blvd, Box 447, Houston, TX 77030-4009, USA. kabagg@mdanderson.org', 'United States|United States|United States|United States', 222, 'Algorithms|Expressed Sequence Tags|Gene Expression Profiling|Gene Library|Genetic Variation|Models, Genetic|Models, Statistical|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg173', '12912827', 'In contrasting levels of gene expression between groups of SAGE libraries, the libraries within each group are often combined and the counts for the tag of interest summed, and inference is made on the basis of these larger pseudolibraries. While this captures the sampling variability inherent in the procedure, it fails to allow for normal variation in levels of the gene between individuals within the same group, and can consequently overstate the significance of the results. The effect is not slight: between-library variation can be hundreds of times the within-library variation.'),
(70782, 2003, 'bio', 'Class prediction and discovery using gene microarray and proteomics mass spectroscopy data: curses, caveats, cautions', 'Somorjai, R L|Dolenko, B|Baumgartner, R', 'Institute for Biodiagnostics, National Research Council Canada, Winnipeg, MB, Canada R3B 1Y6. Ray.Somorjai@nrc-cnrc.gc.ca|Institute for Biodiagnostics, National Research Council Canada, Winnipeg, MB, Canada R3B 1Y6. Ray.Somorjai@nrc-cnrc.gc.ca|Institute for Biodiagnostics, National Research Council Canada, Winnipeg, MB, Canada R3B 1Y6. Ray.Somorjai@nrc-cnrc.gc.ca', 'Canada|Canada|Canada', 0, 'Algorithms|Artifacts|Cluster Analysis|DNA|Gene Expression Profiling|Genetic Variation|Humans|Mass Spectrometry|Models, Genetic|Models, Statistical|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Proteomics|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg182', '12912828', 'Two practical realities constrain the analysis of microarray data, mass spectra from proteomics, and biomedical infrared or magnetic resonance spectra. One is the curse of dimensionality: the number of features characterizing these data is in the thousands or tens of thousands. The other is the curse of dataset sparsity: the number of samples is limited. The consequences of these two curses are far-reaching when such data are used to classify the presence or absence of disease.'),
(70783, 2003, 'bio', 'Serial BLAST searching', 'Korf, Ian', 'The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK. ik1@sanger.ac.uk', 'United Kingdom', 11, 'Algorithms|Amino Acid Sequence|Database Management Systems|Gene Expression Profiling|Information Storage and Retrieval|Molecular Sequence Data|National Library of Medicine (U.S.)|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|United States', 'Comparative Study', '10.1093/bioinformatics/btg199', '12912829', 'The translating BLAST algorithms are powerful tools for finding protein-coding genes because they identify amino acid similarities in nucleotide sequences. Unfortunately, these kinds of searches are computationally intensive and often represent bottlenecks in sequence analysis pipelines. Tuning parameters for speed can make the searches much faster, but one risks losing low-scoring alignments. However, high scoring alignments are relatively resistant to such changes in parameters, and this fact makes it possible to use a serial strategy where a fast, insensitive search is used to pre-screen a database for similar sequences, and a slow, sensitive search is used to produce the sequence alignments.'),
(70784, 2003, 'bio', 'Greedy method for inferring tandem duplication history', 'Zhang, Louxin|Ma, Bin|Wang, Lusheng|Xu, Ying', 'Department of Mathematics, National University of Singapore, Singapore.|Department of Mathematics, National University of Singapore, Singapore.|Department of Mathematics, National University of Singapore, Singapore.|Department of Mathematics, National University of Singapore, Singapore.', 'Singapore|Singapore|Singapore|Singapore', 28, 'Algorithms|Computer Simulation|Evolution, Molecular|Gene Expression Profiling|Models, Genetic|Mucins|Phylogeny|Receptors, Odorant|Sequence Alignment|Sequence Analysis, DNA|Software|Tandem Repeat Sequences|Zinc Fingers', 'Comparative Study', '10.1093/bioinformatics/btg191', '12912830', 'Genome analysis suggests that tandem duplication is an important mode of evolutionary novelty by permitting one copy of each gene to drift and potentially to acquire a new function. With more and more genomic sequences available, reconstructing duplication history has received extensive attention recently.'),
(70785, 2003, 'bio', 'A hidden Markov model for progressive multiple alignment', 'Löytynoja, Ari|Milinkovitch, Michel C', 'Unit of Evolutionary Genetics, Free University of Brussels (ULB), cp 300, Institute of Molecular Biology and Medicine, rue Jeener & Brachet 12, B-6041 Gosselies, Belgium. aloytyno@ulb.ac.be|Unit of Evolutionary Genetics, Free University of Brussels (ULB), cp 300, Institute of Molecular Biology and Medicine, rue Jeener & Brachet 12, B-6041 Gosselies, Belgium. aloytyno@ulb.ac.be', 'Belgium|Belgium', 0, 'Algorithms|Databases, Genetic|Gene Expression Profiling|Markov Chains|Models, Genetic|Models, Statistical|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/btg193', '12912831', 'Progressive algorithms are widely used heuristics for the production of alignments among multiple nucleic-acid or protein sequences. Probabilistic approaches providing measures of global and/or local reliability of individual solutions would constitute valuable developments.'),
(70786, 2003, 'bio', 'Molecular evaluation using in silico protein interaction profiles', 'Hayashi, Yoshiharu|Sakaguchi, Katsuyoshi|Kobayashi, Mime|Kobayashi, Masaki|Kikuchi, Yo|Ichiishi, Eiichiro', 'Division of Bioinformatics, KLIMERS (K-laboratories for Intelligent Medical Remote Services, Enkaku Iryou-laboratories) Co., Ltd., 2266-22 Anagahora, Shimoshidami, Moriyama-ku, Nagoya 463-0003, Japan. yhayashi@enkaku.co.jp|Division of Bioinformatics, KLIMERS (K-laboratories for Intelligent Medical Remote Services, Enkaku Iryou-laboratories) Co., Ltd., 2266-22 Anagahora, Shimoshidami, Moriyama-ku, Nagoya 463-0003, Japan. yhayashi@enkaku.co.jp|Division of Bioinformatics, KLIMERS (K-laboratories for Intelligent Medical Remote Services, Enkaku Iryou-laboratories) Co., Ltd., 2266-22 Anagahora, Shimoshidami, Moriyama-ku, Nagoya 463-0003, Japan. yhayashi@enkaku.co.jp|Division of Bioinformatics, KLIMERS (K-laboratories for Intelligent Medical Remote Services, Enkaku Iryou-laboratories) Co., Ltd., 2266-22 Anagahora, Shimoshidami, Moriyama-ku, Nagoya 463-0003, Japan. yhayashi@enkaku.co.jp|Division of Bioinformatics, KLIMERS (K-laboratories for Intelligent Medical Remote Services, Enkaku Iryou-laboratories) Co., Ltd., 2266-22 Anagahora, Shimoshidami, Moriyama-ku, Nagoya 463-0003, Japan. yhayashi@enkaku.co.jp|Division of Bioinformatics, KLIMERS (K-laboratories for Intelligent Medical Remote Services, Enkaku Iryou-laboratories) Co., Ltd., 2266-22 Anagahora, Shimoshidami, Moriyama-ku, Nagoya 463-0003, Japan. yhayashi@enkaku.co.jp', 'Japan|Japan|Japan|Japan|Japan|Japan', 12, 'Algorithms|Binding Sites|Computer Simulation|Energy Transfer|Macromolecular Substances|Models, Chemical|Models, Molecular|Protein Array Analysis|Protein Binding|Protein Interaction Mapping|Proteins|Quantitative Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg189', '12912832', 'To find a correlation between the activities and structures of molecules is one of the most important subjects for molecular evaluation study. Traditional quantitative structure-activity relationship (QSAR) methodologies represent those attempts using physicochemical descriptors. Creating a new molecular description factor based on the results of a computational docking study will add new dimensions to molecular evaluation.'),
(70787, 2003, 'bio', 'Identification of functional links between genes using phylogenetic profiles', 'Wu, Jie|Kasif, Simon|DeLisi, Charles', 'Department of Biomedical Engineering, USA Bioinformatics Graduate Program, Boston University, 44 Cummington St., Boston, MA, 02215, USA.|Department of Biomedical Engineering, USA Bioinformatics Graduate Program, Boston University, 44 Cummington St., Boston, MA, 02215, USA.|Department of Biomedical Engineering, USA Bioinformatics Graduate Program, Boston University, 44 Cummington St., Boston, MA, 02215, USA.', 'United States|United States|United States', 113, 'Algorithms|Computer Simulation|Gene Expression Profiling|Genetic Linkage|Genome, Bacterial|Genome, Fungal|Models, Genetic|Models, Statistical|Phylogeny|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/btg187', '12912833', 'Genes with identical patterns of occurrence across the phyla tend to function together in the same protein complexes or participate in the same biochemical pathway. However, the requirement that the profiles be identical (i) severely restricts the number of functional links that can be established by such phylogenetic profiling, (ii) limits detection to very strong functional links, failing to capture relations between genes that are not in the same pathway, but nevertheless subserve a common function and (iii) misses relations between analogous genes. Here we present and apply a method for relaxing the restriction, based on the probability that a given arbitrary degree of similarity between two profiles would occur by chance, with no biological pressure. Function is then inferred at any desired level of confidence.'),
(70788, 2003, 'bio', 'Probabilistic scoring measures for profile-profile comparison yield more accurate short seed alignments', 'Mittelman, David|Sadreyev, Ruslan|Grishin, Nick', 'Howard Hughes Medical Institute Department of Biochemistry, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-9050, USA.|Howard Hughes Medical Institute Department of Biochemistry, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-9050, USA.|Howard Hughes Medical Institute Department of Biochemistry, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-9050, USA.', 'United States|United States|United States', 64, 'Algorithms|Amino Acid Sequence|Computer Simulation|Gene Expression Profiling|Models, Genetic|Models, Statistical|Molecular Sequence Data|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg185', '12912834', 'The development of powerful automatic methods for the comparison of protein sequences has become increasingly important. Profile-to-profile comparisons allow for the use of broader information about protein families, resulting in more sensitive and accurate comparisons of distantly related sequences. A key part in the comparison of two profiles is the method for the calculation of scores for the position matches. A number of methods based on various theoretical considerations have been proposed. We implemented several previously reported scoring functions as well as our own functions, and compared them on the basis of their ability to produce accurate short ungapped alignments of a given length.'),
(70789, 2003, 'bio', 'Development of a four-body statistical pseudo-potential to discriminate native from non-native protein conformations', 'Krishnamoorthy, Bala|Tropsha, Alexander', 'Department of Operations Research, CB 3180, UNC Chapel Hill, NC 27599, USA.|Department of Operations Research, CB 3180, UNC Chapel Hill, NC 27599, USA.', 'United States|United States', 87, 'Algorithms|Amino Acid Sequence|Crystallography|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Folding|Proteins|Quantitative Structure-Activity Relationship|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg186', '12912835', 'Most scoring functions used in protein fold recognition employ two-body (pseudo) potential energies. The use of higher-order terms may improve the performance of current algorithms.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70790, 2003, 'bio', 'Rapid classification of a protein fold family using a statistical analysis of dipolar couplings', 'Valafar, Homayoun|Prestegard, James H', 'Southeast Collaboratory for Structural Genomics Complex Carbohydrate Research Center, University of Georgia, 220 Riverbend Road, Athens, GA 30602, USA.|Southeast Collaboratory for Structural Genomics Complex Carbohydrate Research Center, University of Georgia, 220 Riverbend Road, Athens, GA 30602, USA.', 'Georgia|Georgia', 35, 'Algorithms|Computer Simulation|Databases, Protein|Magnetic Resonance Spectroscopy|Models, Molecular|Protein Folding|Proteins|Quantitative Structure-Activity Relationship|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg201', '12912836', 'One of the primary aims of the structural genomics initiative is the determination of representative structures from each protein fold family. Given this objective, it is important to rapidly identify proteins that belong to a family that is already well populated (so they can be eliminated from further studies), or more importantly identify proteins that represent new families of fold.'),
(70791, 2003, 'bio', 'Pandit: a database of protein and associated nucleotide domains with inferred trees', 'Whelan, Simon|de Bakker, Paul I W|Goldman, Nick', 'Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK. simon@ebi.ac.uk|Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK. simon@ebi.ac.uk|Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK. simon@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 36, 'Algorithms|Amino Acid Sequence|Base Sequence|Database Management Systems|Databases, Nucleic Acid|Databases, Protein|Evolution, Molecular|Gene Expression Profiling|Genetic Variation|Information Storage and Retrieval|Models, Genetic|Models, Statistical|Molecular Sequence Data|Nucleotides|Phylogeny|Protein Structure, Tertiary|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg188', '12912837', 'A large, high-quality database of homologous sequence alignments with good estimates of their corresponding phylogenetic trees will be a valuable resource to those studying phylogenetics. It will allow researchers to compare current and new models of sequence evolution across a large variety of sequences. The large quantity of data may provide inspiration for new models and methodology to study sequence evolution and may allow general statements about the relative effect of different molecular processes on evolution.'),
(70792, 2003, 'bio', 'Evaluation of ontology development tools for bioinformatics', 'Lambrix, Patrick|Habbouche, Manal|Pérez, Marta', 'Department of Computer and Information Science, Linköpings universitet, 581 83 Linköping, Sweden. patla@ida.liu.se|Department of Computer and Information Science, Linköpings universitet, 581 83 Linköping, Sweden. patla@ida.liu.se|Department of Computer and Information Science, Linköpings universitet, 581 83 Linköping, Sweden. patla@ida.liu.se', 'Sweden|Sweden|Sweden', 59, 'Computational Biology|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Phylogeny|Software|Software Validation|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg194', '12912838', 'Ontologies are being used nowadays in many areas, including bioinformatics. To assist users in developing and maintaining ontologies a number of tools have been developed. In this paper we compare four such tools, Protégé-2000, Chimaera, DAG-Edit and OilEd. As test ontologies we have used ontologies from the Gene Ontology Consortium. No system is preferred in all situations, but each system has its own strengths and weaknesses.'),
(70793, 2003, 'bio', 'MrBayes 3: Bayesian phylogenetic inference under mixed models', 'Ronquist, Fredrik|Huelsenbeck, John P', 'Department of Systematic Zoology, Evolutionary Biology Centre, Uppsala University, Norbyv. 18D, SE-752 36 Uppsala, Sweden. fredrik.ronquist@ebc.uu.se|Department of Systematic Zoology, Evolutionary Biology Centre, Uppsala University, Norbyv. 18D, SE-752 36 Uppsala, Sweden. fredrik.ronquist@ebc.uu.se', 'Sweden|Sweden', 21977, 'Algorithms|Bayes Theorem|Evolution, Molecular|Gene Expression Profiling|Models, Genetic|Models, Statistical|Phylogeny|Sequence Alignment|Sequence Homology|Software|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btg180', '12912839', 'MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types-e.g. morphological, nucleotide, and protein-and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters.'),
(70794, 2003, 'bio', 'AGenDA: homology-based gene prediction', 'Taher, Leila|Rinner, Oliver|Garg, Saurabh|Sczyrba, Alexander|Brudno, Michael|Batzoglou, Serafim|Morgenstern, Burkhard', 'International Graduate School for Bioinformatics and Genome Research University of Bielefeld, Postfach 10 01 31, 33501 Bielefeld, Germany. ltaher@TechFak.Uni-Bielefeld.DE|International Graduate School for Bioinformatics and Genome Research University of Bielefeld, Postfach 10 01 31, 33501 Bielefeld, Germany. ltaher@TechFak.Uni-Bielefeld.DE|International Graduate School for Bioinformatics and Genome Research University of Bielefeld, Postfach 10 01 31, 33501 Bielefeld, Germany. ltaher@TechFak.Uni-Bielefeld.DE|International Graduate School for Bioinformatics and Genome Research University of Bielefeld, Postfach 10 01 31, 33501 Bielefeld, Germany. ltaher@TechFak.Uni-Bielefeld.DE|International Graduate School for Bioinformatics and Genome Research University of Bielefeld, Postfach 10 01 31, 33501 Bielefeld, Germany. ltaher@TechFak.Uni-Bielefeld.DE|International Graduate School for Bioinformatics and Genome Research University of Bielefeld, Postfach 10 01 31, 33501 Bielefeld, Germany. ltaher@TechFak.Uni-Bielefeld.DE|International Graduate School for Bioinformatics and Genome Research University of Bielefeld, Postfach 10 01 31, 33501 Bielefeld, Germany. ltaher@TechFak.Uni-Bielefeld.DE', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 21, 'Algorithms|Electronic Mail|Evolution, Molecular|Gene Expression Profiling|Information Storage and Retrieval|Internet|Models, Genetic|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/btg181', '12912840', 'We present a www server for homology-based gene prediction. The user enters a pair of evolutionary related genomic sequences, for example from human and mouse. Our software system uses CHAOS and DIALIGN to calculate an alignment of the input sequences and then searches for conserved splicing signals and start/stop codons around regions of local sequence similarity. This way, candidate exons are identified that are used, in turn, to calculate optimal gene models. The server returns the constructed gene model by email, together with a graphical representation of the underlying genomic alignment.'),
(70795, 2003, 'bio', 'RankGene: identification of diagnostic genes based on expression data', 'Su, Yang|Murali, T M|Pavlovic, Vladimir|Schaffer, Michael|Kasif, Simon', 'Bioinformatics Program, Boston University, Boston, MA 02215, USA.|Bioinformatics Program, Boston University, Boston, MA 02215, USA.|Bioinformatics Program, Boston University, Boston, MA 02215, USA.|Bioinformatics Program, Boston University, Boston, MA 02215, USA.|Bioinformatics Program, Boston University, Boston, MA 02215, USA.', 'United States|United States|United States|United States|United States', 141, 'Algorithms|DNA|Diagnosis, Computer-Assisted|Gene Expression Profiling|Gene Expression Regulation|Genetic Markers|Genetic Predisposition to Disease|Genetic Testing|Models, Genetic|Models, Statistical|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg179', '12912841', 'RankGene is a program for analyzing gene expression data and computing diagnostic genes based on their predictive power in distinguishing between different types of samples. The program integrates into one system a variety of popular ranking criteria, ranging from the traditional t-statistic to one-dimensional support vector machines. This flexibility makes RankGene a useful tool in gene expression analysis and feature selection.'),
(70796, 2003, 'bio', 'UniFrag and GenomePrimer: selection of primers for genome-wide production of unique amplicons', 'van Hijum, Sacha A F T|de Jong, Anne|Buist, Girbe|Kok, Jan|Kuipers, Oscar P', 'Molecular Genetics, University of Groningen, Groningen Biomolecular Sciences and Biotechnology Institute, PO Box 14, 9750 AA Haren, The Netherlands.|Molecular Genetics, University of Groningen, Groningen Biomolecular Sciences and Biotechnology Institute, PO Box 14, 9750 AA Haren, The Netherlands.|Molecular Genetics, University of Groningen, Groningen Biomolecular Sciences and Biotechnology Institute, PO Box 14, 9750 AA Haren, The Netherlands.|Molecular Genetics, University of Groningen, Groningen Biomolecular Sciences and Biotechnology Institute, PO Box 14, 9750 AA Haren, The Netherlands.|Molecular Genetics, University of Groningen, Groningen Biomolecular Sciences and Biotechnology Institute, PO Box 14, 9750 AA Haren, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 28, 'Algorithms|DNA Primers|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg203', '12912842', 'The complementary programs UniFrag and GenomePrimer were developed to provide a reliable high-throughput method to select the most unique regions within genomic DNA sequence(s) and design primers therein, involving minimal user intervention and maximum flexibility.'),
(70797, 2003, 'bio', 'GenoMap, a circular genome data viewer', 'Sato, Naoki|Ehira, Shigeki', 'Department of Molecular Biology, Faculty of Science, Saitama University, 255 Shimo-Ohkubo, Saitama, 338-8570 Japan. naokisat@molbiol.saitama-u.ac.jp|Department of Molecular Biology, Faculty of Science, Saitama University, 255 Shimo-Ohkubo, Saitama, 338-8570 Japan. naokisat@molbiol.saitama-u.ac.jp', 'Japan|Japan', 27, 'Computer Graphics|Database Management Systems|Gene Expression Profiling|Genome|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg195', '12912843', 'A Tcl/Tk-based application called GenoMap is described, a viewer for genome-wide map of microarray expression data within a circular bacterial genome. An interactive interface facilitates easy identification of the expressed region. This software is also used for drawing genome-wide quantitative data.'),
(70798, 2003, 'bio', 'ClustalW-MPI: ClustalW analysis using distributed and parallel computing', 'Li, Kuo-Bin', 'Bioinformatics Institute, 30 Medical Drive, Singapore 117609, Republic of Singapore. kuobin@bii.a-star.edu.sg', 'Singapore', 274, 'Amino Acid Sequence|Base Sequence|Cluster Analysis|Computing Methodologies|Gene Expression Profiling|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg192', '12912844', 'ClustalW is a tool for aligning multiple protein or nucleotide sequences. The alignment is achieved via three steps: pairwise alignment, guide-tree generation and progressive alignment. ClustalW-MPI is a distributed and parallel implementation of ClustalW. All three steps have been parallelized to reduce the execution time. The software uses a message-passing library called MPI (Message Passing Interface) and runs on distributed workstation clusters as well as on traditional parallel computers.'),
(70799, 2003, 'bio', 'ESTWeb: bioinformatics services for EST sequencing projects', 'Paquola, Apuã C M|Nishyiama, Milton Y|Reis, Eduardo M|da Silva, Aline M|Verjovski-Almeida, Sergio', 'Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, 05508-900, São Paulo, SP, Brazil.|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, 05508-900, São Paulo, SP, Brazil.|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, 05508-900, São Paulo, SP, Brazil.|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, 05508-900, São Paulo, SP, Brazil.|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, 05508-900, São Paulo, SP, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil', 30, 'Computational Biology|Database Management Systems|Documentation|Expressed Sequence Tags|Gene Expression Profiling|Information Storage and Retrieval|Internet|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg196', '12912845', 'ESTWeb is an internet based software package designed for uniform data processing and storage for large-scale EST sequencing projects. The package provides for: (a) reception of sequencing chromatograms, (b) sequence processing such as base-calling, vector screening, comparison with public databases, (c) storage of data and analysis in a relational database, (d) generation of a graphical report of individual sequence quality, and (e) issuing of reports with statistics of productivity and redundancy. The software facilitates real-time monitoring and evaluation of EST sequence acquisition progress along an EST sequencing project.'),
(70800, 2003, 'bio', 'PISCES: a protein sequence culling server', 'Wang, Guoli|Dunbrack, Roland L', 'Institute for Cancer Research, Fox Chase Cancer Center, 7701 Burholme Avenue, Philadelphia, PA 19111, USA.|Institute for Cancer Research, Fox Chase Cancer Center, 7701 Burholme Avenue, Philadelphia, PA 19111, USA.', 'United States|United States', 1115, 'Algorithms|Computing Methodologies|Conserved Sequence|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/btg224', '12912846', 'PISCES is a public server for culling sets of protein sequences from the Protein Data Bank (PDB) by sequence identity and structural quality criteria. PISCES can provide lists culled from the entire PDB or from lists of PDB entries or chains provided by the user. The sequence identities are obtained from PSI-BLAST alignments with position-specific substitution matrices derived from the non-redundant protein sequence database. PISCES therefore provides better lists than servers that use BLAST, which is unable to identify many relationships below 40% sequence identity and often overestimates sequence identity by aligning only well-conserved fragments. PDB sequences are updated weekly. PISCES can also cull non-PDB sequences provided by the user as a list of GenBank identifiers, a FASTA format file, or BLAST/PSI-BLAST output.'),
(70801, 2003, 'bio', 'QAlign: quality-based multiple alignments with dynamic phylogenetic analysis', 'Sammeth, M|Rothgänger, J|Esser, W|Albert, J|Stoye, J|Harmsen, D', 'Department of Computer Science II, University of Würzburg, 97074 Würzburg, Germany.|Department of Computer Science II, University of Würzburg, 97074 Würzburg, Germany.|Department of Computer Science II, University of Würzburg, 97074 Würzburg, Germany.|Department of Computer Science II, University of Würzburg, 97074 Würzburg, Germany.|Department of Computer Science II, University of Würzburg, 97074 Würzburg, Germany.|Department of Computer Science II, University of Würzburg, 97074 Würzburg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 10, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Genetic|Documentation|Gene Expression Profiling|Information Storage and Retrieval|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg197', '12912847', 'Integrating different alignment strategies, a layout editor and tools deriving phylogenetic trees in a multiple alignment environment helps to investigate and enhance results of multiple sequence alignment by hand. QAlign combines algorithms for fast progressive and accurate simultaneous multiple alignment with a versatile editor and a dynamic phylogenetic analysis in a convenient graphical user interface.'),
(70802, 2003, 'bio', 'Digital extractor: analysis of digital differential display output', 'Madden, Stephen F|ODonovan, Barry|Furney, Simon J|Brady, Hugh R|Silvestre, Guenole|Doran, Peter P', 'Human Genomics and Bioinformatics Research Unit, Department of Medicine and Therapeutics, University College Dublin, Mater Misericordiae Hospital, The Dublin Molecular Medicine Centre, 41 Eccles St, Dublin 7, Ireland.|Human Genomics and Bioinformatics Research Unit, Department of Medicine and Therapeutics, University College Dublin, Mater Misericordiae Hospital, The Dublin Molecular Medicine Centre, 41 Eccles St, Dublin 7, Ireland.|Human Genomics and Bioinformatics Research Unit, Department of Medicine and Therapeutics, University College Dublin, Mater Misericordiae Hospital, The Dublin Molecular Medicine Centre, 41 Eccles St, Dublin 7, Ireland.|Human Genomics and Bioinformatics Research Unit, Department of Medicine and Therapeutics, University College Dublin, Mater Misericordiae Hospital, The Dublin Molecular Medicine Centre, 41 Eccles St, Dublin 7, Ireland.|Human Genomics and Bioinformatics Research Unit, Department of Medicine and Therapeutics, University College Dublin, Mater Misericordiae Hospital, The Dublin Molecular Medicine Centre, 41 Eccles St, Dublin 7, Ireland.|Human Genomics and Bioinformatics Research Unit, Department of Medicine and Therapeutics, University College Dublin, Mater Misericordiae Hospital, The Dublin Molecular Medicine Centre, 41 Eccles St, Dublin 7, Ireland.', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland', 0, 'Database Management Systems|Databases, Nucleic Acid|Documentation|Expressed Sequence Tags|Gene Expression Profiling|Gene Library|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg198', '12912848', 'Digital Extractor is a program for the high-throughput processing of data sets derived from digital differential display-based comparisons of EST libraries. These comparisons can be utilized to identify discrete subsets of genes whose expression is restricted to distinct tissue types. The program facilitates these investigations by permitting parallel annotation of genes identified as being differentially expressed.'),
(70803, 2003, 'bio', 'A comparative analysis of HGSC and Celera human genome assemblies and gene sets', 'Li, Shuyu|Cutler, Gene|Liu, Jane Jijun|Hoey, Timothy|Chen, Liangbiao|Schultz, Peter G|Liao, Jiayu|Ling, Xuefeng Bruce', 'Tularik, Inc 112 Veterans Blvd, South San Francisco, CA 94080, USA.|Tularik, Inc 112 Veterans Blvd, South San Francisco, CA 94080, USA.|Tularik, Inc 112 Veterans Blvd, South San Francisco, CA 94080, USA.|Tularik, Inc 112 Veterans Blvd, South San Francisco, CA 94080, USA.|Tularik, Inc 112 Veterans Blvd, South San Francisco, CA 94080, USA.|Tularik, Inc 112 Veterans Blvd, South San Francisco, CA 94080, USA.|Tularik, Inc 112 Veterans Blvd, South San Francisco, CA 94080, USA.|Tularik, Inc 112 Veterans Blvd, South San Francisco, CA 94080, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 5, 'Databases, Protein|Gene Expression Profiling|Genome, Human|Human Genome Project|Humans|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg219', '12967954', 'Since the simultaneous publication of the human genome assembly by the International Human Genome Sequencing Consortium (HGSC) and Celera Genomics, several comparisons have been made of various aspects of these two assemblies. In this work, we set out to provide a more comprehensive comparative analysis of the two assemblies and their associated gene sets.'),
(70804, 2003, 'bio', 'ddbRNA: detection of conserved secondary structures in multiple alignments', 'di Bernardo, Diego|Down, Thomas|Hubbard, Tim', 'Telethon Institute of Genetics and Medicine, Via P Castellino 111, 80133 Naples, Italy. dibernardo@tigem.it|Telethon Institute of Genetics and Medicine, Via P Castellino 111, 80133 Naples, Italy. dibernardo@tigem.it|Telethon Institute of Genetics and Medicine, Via P Castellino 111, 80133 Naples, Italy. dibernardo@tigem.it', 'Italy|Italy|Italy', 54, 'Algorithms|Base Pairing|Base Sequence|Conserved Sequence|Gene Expression Profiling|Genes, BRCA2|Molecular Sequence Data|RNA, Untranslated|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, RNA|Software', 'Comparative Study', '10.1093/bioinformatics/btg229', '12967955', 'Structured non-coding RNAs (ncRNAs) have a very important functional role in the cell. No distinctive general features common to all ncRNA have yet been discovered. This makes it difficult to design computational tools able to detect novel ncRNAs in the genomic sequence.'),
(70805, 2003, 'bio', 'Diametrical clustering for identifying anti-correlated gene clusters', 'Dhillon, Inderjit S|Marcotte, Edward M|Roshan, Usman', 'Department of Computer Sciences, Institute for Cellular and Molecular Medicine, University of Texas, Austin, TX 78712, USA.|Department of Computer Sciences, Institute for Cellular and Molecular Medicine, University of Texas, Austin, TX 78712, USA.|Department of Computer Sciences, Institute for Cellular and Molecular Medicine, University of Texas, Austin, TX 78712, USA.', 'United States|United States|United States', 0, 'Algorithms|Cluster Analysis|Fibroblasts|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Genetic|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, RNA|Statistics as Topic|Yeasts', 'Comparative Study', '10.1093/bioinformatics/btg209', '12967956', 'Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways.'),
(70806, 2003, 'bio', 'The effect of replication on gene expression microarray experiments', 'Pavlidis, Paul|Li, Qinghong|Noble, William Stafford', 'Columbia Genome Center, Columbia University, 1150 St Nicholas Avenue, New York, NY 10032, USA. pp175@columbia.edu|Columbia Genome Center, Columbia University, 1150 St Nicholas Avenue, New York, NY 10032, USA. pp175@columbia.edu|Columbia Genome Center, Columbia University, 1150 St Nicholas Avenue, New York, NY 10032, USA. pp175@columbia.edu', 'United States|United States|United States', 113, 'Animals|DNA Replication|Data Interpretation, Statistical|Databases, Nucleic Acid|Gene Expression Profiling|Humans|Models, Genetic|Models, Statistical|Neoplasms|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Research Design|Sample Size|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg227', '12967957', 'We examine the effect of replication on the detection of apparently differentially expressed genes in gene expression microarray experiments. Our analysis is based on a random sampling approach using real data sets from 16 published studies. We consider both the ability to find genes that meet particular statistical criteria as well as the stability of the results in the face of changing levels of replication.'),
(70807, 2003, 'bio', 'Statistical significance analysis of longitudinal gene expression data', 'Guo, Xu|Qi, Huilin|Verfaillie, Catherine M|Pan, Wei', 'Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, Minneapolis, MN 55455-0378, USA.|Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, Minneapolis, MN 55455-0378, USA.|Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, Minneapolis, MN 55455-0378, USA.|Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, Minneapolis, MN 55455-0378, USA.', 'United States|United States|United States|United States', 29, 'Adaptation, Physiological|Algorithms|Cell Differentiation|Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Osteoblasts|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Sequence Alignment|Stem Cells|Stochastic Processes|Time Factors', 'Comparative Study', '10.1093/bioinformatics/btg206', '12967958', 'Time-course microarray experiments are designed to study biological processes in a temporal fashion. Longitudinal gene expression data arise when biological samples taken from the same subject at different time points are used to measure the gene expression levels. It has been observed that the gene expression patterns of samples of a given tumor measured at different time points are likely to be much more similar to each other than are the expression patterns of tumor samples of the same type taken from different subjects. In statistics, this phenomenon is called the within-subject correlation of repeated measurements on the same subject, and the resulting data are called longitudinal data. It is well known in other applications that valid statistical analyses have to appropriately take account of the possible within-subject correlation in longitudinal data.'),
(70808, 2003, 'bio', 'Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data', 'Wu, Baolin|Abbott, Tom|Fishman, David|McMurray, Walter|Mor, Gil|Stone, Kathryn|Ward, David|Williams, Kenneth|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.|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.|Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 352, 'Algorithms|Biomarkers, Tumor|Diagnosis, Computer-Assisted|Female|Humans|Models, Biological|Models, Statistical|Neoplasm Proteins|Ovarian Neoplasms|Reproducibility of Results|Sensitivity and Specificity|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Comparative Study', '10.1093/bioinformatics/btg210', '12967959', 'Novel methods, both molecular and statistical, are urgently needed to take advantage of recent advances in biotechnology and the human genome project for disease diagnosis and prognosis. Mass spectrometry (MS) holds great promise for biomarker identification and genome-wide protein profiling. It has been demonstrated in the literature that biomarkers can be identified to distinguish normal individuals from cancer patients using MS data. Such progress is especially exciting for the detection of early-stage ovarian cancer patients. Although various statistical methods have been utilized to identify biomarkers from MS data, there has been no systematic comparison among these approaches in their relative ability to analyze MS data.'),
(70809, 2003, 'bio', 'An algorithm for constraint-based structural template matching: application to 3D templates with statistical analysis', 'Barker, Jonathan A|Thornton, Janet M', 'European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. jbarker@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. jbarker@ebi.ac.uk', 'United Kingdom|United Kingdom', 168, 'Algorithms|Amino Acid Motifs|Computer Simulation|Enzymes|Models, Molecular|Models, Statistical|Pattern Recognition, Automated|Protein Conformation|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg226', '12967960', 'Structural templates consisting of a few atoms in a specific geometric conformation provide a powerful tool for studying the relationship between protein structure and function. Current methods for template searching constrain template syntax and semantics by their design. Hence there is a need for a more flexible core algorithm upon which to build more sophisticated tools. Statistical analysis of structural similarity is still in its infancy when compared with its analogue in sequence alignment. In the context of template matching, there is an urgent need for normalization of scores so that results from templates with differing sensitivity may be compared directly.'),
(70810, 2003, 'bio', 'Secondary structure prediction with support vector machines', 'Ward, J J|McGuffin, L J|Buxton, B F|Jones, D T', 'Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK.|Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK.|Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK.|Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 177, 'Algorithms|Artificial Intelligence|Benchmarking|Cluster Analysis|Computing Methodologies|Models, Statistical|Pattern Recognition, Automated|Protein Structure, Secondary|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg223', '12967961', 'A new method that uses support vector machines (SVMs) to predict protein secondary structure is described and evaluated. The study is designed to develop a reliable prediction method using an alternative technique and to investigate the applicability of SVMs to this type of bioinformatics problem.'),
(70811, 2003, 'bio', 'Prediction of protein subcellular locations by support vector machines using compositions of amino acids and amino acid pairs', 'Park, Keun-Joon|Kanehisa, Minoru', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.', 'Japan|Japan', 316, 'Algorithms|Amino Acid Sequence|Amino Acids|Artificial Intelligence|Cellular Structures|Computing Methodologies|Databases, Protein|Molecular Sequence Data|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software|Subcellular Fractions|Tissue Distribution', 'Comparative Study', '10.1093/bioinformatics/btg222', '12967962', 'The subcellular location of a protein is closely correlated to its function. Thus, computational prediction of subcellular locations from the amino acid sequence information would help annotation and functional prediction of protein coding genes in complete genomes. We have developed a method based on support vector machines (SVMs).'),
(70812, 2003, 'bio', 'PRECIS: protein reports engineered from concise information in SWISS-PROT', 'Mitchell, A L|Reich, J R|Attwood, T K', 'School of Biological Sciences, University of Manchester, Oxford Road, Manchester M13 9PT, UK. mitchell@ebi.ac.uk|School of Biological Sciences, University of Manchester, Oxford Road, Manchester M13 9PT, UK. mitchell@ebi.ac.uk|School of Biological Sciences, University of Manchester, Oxford Road, Manchester M13 9PT, UK. mitchell@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 4, 'Abstracting and Indexing as Topic|Animals|Cataloging|Database Management Systems|Databases, Protein|Documentation|Humans|Information Storage and Retrieval|Proteins|Sequence Analysis, Protein|Software|Software Design|User-Computer Interface|Vocabulary, Controlled', 'Comparative Study', '10.1093/bioinformatics/btg204', '12967963', 'There have been several endeavours to address the problem of annotating sequence data computationally, but the task is non-trivial and few tools have emerged that gather useful information on a given sequence, or set of sequences, in a simple and convenient manner. As more genome projects bear fruit, the mass of uncharacterized sequence data accumulating in public repositories grows ever larger. There is thus a pressing need for tools to support the process of automatic analysis and annotation of newly determined sequences. With this in mind, we have developed PRECIS, which automatically creates protein reports from sets of SWISS-PROT entries, collating results into structured reports, detailing known biological and medical information, literature and database cross-references, and relevant keywords.'),
(70813, 2003, 'bio', 'Comparison of sequence masking algorithms and the detection of biased protein sequence regions', 'Kreil, David P|Ouzounis, Christos A', 'Department of Genetics/Inference Group (Cavendish Laboratory), University of Cambridge, Cambridge, UK. kreil@ebi.ac.uk|Department of Genetics/Inference Group (Cavendish Laboratory), University of Cambridge, Cambridge, UK. kreil@ebi.ac.uk', 'United Kingdom|United Kingdom', 15, 'Aeropyrum|Algorithms|Amino Acid Sequence|Bacterial Proteins|Bias|Gene Expression Profiling|Models, Genetic|Models, Statistical|Molecular Sequence Data|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg212', '12967964', 'Separation of protein sequence regions according to their local information complexity and subsequent masking of low complexity regions has greatly enhanced the reliability of function prediction by sequence similarity. Comparisons with alternative methods that focus on compositional sequence bias rather than information complexity measures have shown that removal of compositional bias yields at least as sensitive and much more specific results. Besides the application of sequence masking algorithms to sequence similarity searches, the study of the masked regions themselves is of great interest. Traditionally, however, these have been neglected despite evidence of their functional relevance.'),
(70814, 2003, 'bio', 'Consensus alignment for reliable framework prediction in homology modeling', 'Prasad, J C|Comeau, S R|Vajda, S|Camacho, C J', 'Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.|Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.|Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.|Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.', 'United States|United States|United States|United States', 24, 'Algorithms|Amino Acid Sequence|Consensus Sequence|Gene Expression Profiling|Models, Molecular|Molecular Sequence Data|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg211', '12967965', 'Even the best sequence alignment methods frequently fail to correctly identify the framework regions for which backbones can be copied from the template into the target structure. Since the underprediction and, more significantly, the overprediction of these regions reduces the quality of the final model, it is of prime importance to attain as much as possible of the true structural alignment between target and template.'),
(70815, 2003, 'bio', 'PathMiner: predicting metabolic pathways by heuristic search', 'McShan, D C|Rao, S|Shah, I', 'School of Medicine, University of Colorado, 4200 East Ninth Avenue, C-245 Denver, Colorado 80262, USA.|School of Medicine, University of Colorado, 4200 East Ninth Avenue, C-245 Denver, Colorado 80262, USA.|School of Medicine, University of Colorado, 4200 East Ninth Avenue, C-245 Denver, Colorado 80262, USA.', 'United States|United States|United States', 68, 'Algorithms|Artificial Intelligence|Computer Simulation|Metabolism|Models, Biological|Models, Chemical|Multienzyme Complexes|Software', 'Comparative Study', '10.1093/bioinformatics/btg217', '12967966', 'Automated methods for biochemical pathway inference are becoming increasingly important for understanding biological processes in living and synthetic systems. With the availability of data on complete genomes and increasing information about enzyme-catalyzed biochemistry it is becoming feasible to approach this problem computationally. In this paper we present PathMiner, a system for automatic metabolic pathway inference. PathMiner predicts metabolic routes by reasoning over transformations using chemical and biological information.'),
(70816, 2003, 'bio', 'MedScan, a natural language processing engine for MEDLINE abstracts', 'Novichkova, Svetlana|Egorov, Sergei|Daraselia, Nikolai', 'Ariadne Genomics, Inc, 9100 Great Seneca HWY, Rockville, MD 20850, USA.|Ariadne Genomics, Inc, 9100 Great Seneca HWY, Rockville, MD 20850, USA.|Ariadne Genomics, Inc, 9100 Great Seneca HWY, Rockville, MD 20850, USA.', 'United States|United States|United States', 155, 'Abstracting and Indexing as Topic|Artificial Intelligence|Database Management Systems|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Subject Headings|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/btg207', '12967967', 'The importance of extracting biomedical information from scientific publications is well recognized. A number of information extraction systems for the biomedical domain have been reported, but none of them have become widely used in practical applications. Most proposals to date make rather simplistic assumptions about the syntactic aspect of natural language. There is an urgent need for a system that has broad coverage and performs well in real-text applications.'),
(70817, 2003, 'bio', 'STRING: finding tandem repeats in DNA sequences', 'Parisi, Valerio|De Fonzo, Valeria|Aluffi-Pentini, Filippo', 'Sez. INFM, EuroBioPark, Univ. Roma Tor Vergata Via della Ricerca Scientifica 1, 00133 Roma, Italy. valerio.parisi@roma2.infn.it|Sez. INFM, EuroBioPark, Univ. Roma Tor Vergata Via della Ricerca Scientifica 1, 00133 Roma, Italy. valerio.parisi@roma2.infn.it|Sez. INFM, EuroBioPark, Univ. Roma Tor Vergata Via della Ricerca Scientifica 1, 00133 Roma, Italy. valerio.parisi@roma2.infn.it', 'Italy|Italy|Italy', 44, 'Algorithms|Animals|Base Sequence|Databases, Nucleic Acid|Gene Expression Profiling|Genome|Genome, Bacterial|Genome, Protozoan|Molecular Sequence Data|Mycobacterium tuberculosis|Plasmodium falciparum|Sequence Alignment|Sequence Analysis, DNA|Software|Tandem Repeat Sequences', 'Comparative Study', '10.1093/bioinformatics/btg268', '14512342', 'The importance of Tandem Repeats in some genomes is now well established. We have reported elsewhere some interesting new results obtained by means of a preliminary program for finding Tandem Repeats in DNA sequences, together with a brief description of the basic ideas of the algorithm. We describe here a completely new program based only in part on those ideas, we briefly discuss the interpretation of the results, and, by way of example, we provide a few novel results relative to the parasites responsible of two re-emerging diseases, Plasmodium falciparum and Mycobacterium tuberculosis. Our program is portable, effective, powerful and fast: it can run on current desktop computers, and it finds all significant Tandem Repeats also in the longest segments of sequences in databases (up to millions of bases), in short times (minutes).'),
(70818, 2003, 'bio', 'Designing hardware for protein sequence analysis', 'Marongiu, Alessandro|Palazzari, Paolo|Rosato, Vittorio', 'IPITEC s.r.l.-Rome, Italy.|IPITEC s.r.l.-Rome, Italy.|IPITEC s.r.l.-Rome, Italy.', 'Italy|Italy|Italy', 11, 'Algorithms|Amino Acid Sequence|Computers|Computing Methodologies|Conserved Sequence|Equipment Design|Equipment Failure Analysis|Molecular Sequence Data|Proteins|Proteome|Proteomics|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg228', '14512343', 'We present the architecture of PROSIDIS, a special purpose co-processor designed to search for the occurrence of substrings similar to a given template string within a proteome. Actual tests show speed up figures ranging from 5 to 50 with respect to conventional general-purpose processors.'),
(70819, 2003, 'bio', 'Characterizing proteolytic cleavage site activity using bio-basis function neural networks', 'Thomson, Rebecca|Hodgman, T Charles|Yang, Zheng Rong|Doyle, Austin K', 'Department of Structure Biology, Oxford University, UK.|Department of Structure Biology, Oxford University, UK.|Department of Structure Biology, Oxford University, UK.|Department of Structure Biology, Oxford University, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 79, 'Amino Acid Sequence|Binding Sites|Cluster Analysis|Databases, Protein|Enzyme Activation|HIV Protease|Hydrolysis|Molecular Sequence Data|Nerve Net|Pattern Recognition, Automated|Peptide Fragments|Peptide Hydrolases|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Trypsin', 'Comparative Study', '10.1093/bioinformatics/btg237', '14512344', 'In protein chemistry, proteomics and biopharmaceutical development, there is a desire to know not only where a protein is cleaved by a protease, but also the susceptibility of its cleavage sites. The current tools for proteolytic cleavage prediction have often relied purely on regular expressions, or involve models that do not represent biological data well.'),
(70820, 2003, 'bio', 'Recognizing the fold of a protein structure', 'Harrison, Andrew|Pearl, Frances|Sillitoe, Ian|Slidel, Tim|Mott, Richard|Thornton, Janet|Orengo, Christine', 'Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK.|Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK.|Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK.|Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK.|Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK.|Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK.|Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 68, 'Algorithms|Amino Acid Sequence|Cluster Analysis|Databases, Protein|Molecular Sequence Data|Pattern Recognition, Automated|Protein Conformation|Protein Folding|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg240', '14512345', 'This paper reports a graph-theoretic program, GRATH, that rapidly, and accurately, matches a novel structure against a library of domain structures to find the most similar ones. GRATH generates distributions of scores by comparing the novel domain against the different types of folds that have been classified previously in the CATH database of structural domains. GRATH uses a measure of similarity that details the geometric information, number of secondary structures and number of residues within secondary structures, that any two protein structures share. Although GRATH builds on well established approaches for secondary structure comparison, a novel scoring scheme has been introduced to allow ranking of any matches identified by the algorithm. More importantly, we have benchmarked the algorithm using a large dataset of 1702 non-redundant structures from the CATH database which have already been classified into fold groups, with manual validation. This has facilitated introduction of further constraints, optimization of parameters and identification of reliable thresholds for fold identification. Following these benchmarking trials, the correct fold can be identified with the top score with a frequency of 90%. It is identified within the ten most likely assignments with a frequency of 98%. GRATH has been implemented to use via a server (http://www.biochem.ucl.ac.uk/cgi-bin/cath/Grath.pl). GRATHs speed and accuracy means that it can be used as a reliable front-end filter for the more accurate, but computationally expensive, residue based structure comparison algorithm SSAP, currently used to classify domain structures in the CATH database. With an increasing number of structures being solved by the structural genomics initiatives, the GRATH server also provides an essential resource for determining whether newly determined structures are related to any known structures from which functional properties may be inferred.'),
(70821, 2003, 'bio', 'DDBASE20: updated domain database with improved identification of structural domains', 'Vinayagam, A|Shi, J|Pugalenthi, G|Meenakshi, B|Blundell, T L|Sowdhamini, R', 'National Centre for Biological Sciences, Tata Institute of Fundamental Research, UAS-GKVK campus, Bellary Road, Bangalore, Karnataka 560 065, India.|National Centre for Biological Sciences, Tata Institute of Fundamental Research, UAS-GKVK campus, Bellary Road, Bangalore, Karnataka 560 065, India.|National Centre for Biological Sciences, Tata Institute of Fundamental Research, UAS-GKVK campus, Bellary Road, Bangalore, Karnataka 560 065, India.|National Centre for Biological Sciences, Tata Institute of Fundamental Research, UAS-GKVK campus, Bellary Road, Bangalore, Karnataka 560 065, India.|National Centre for Biological Sciences, Tata Institute of Fundamental Research, UAS-GKVK campus, Bellary Road, Bangalore, Karnataka 560 065, India.|National Centre for Biological Sciences, Tata Institute of Fundamental Research, UAS-GKVK campus, Bellary Road, Bangalore, Karnataka 560 065, India.', 'India|India|India|India|India|India', 11, 'Amino Acid Sequence|Database Management Systems|Databases, Protein|Documentation|Information Storage and Retrieval|Internet|Molecular Sequence Data|Protein Conformation|Protein Structure, Tertiary|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg233', '14512346', 'Although many methods are available for the identification of structural domains from protein three-dimensional structures, accurate definition of protein domains and the curation of such data for a large number of proteins are often possible only after manual intervention. The availability of domain definitions for protein structural entries is useful for the sequence analysis of aligned domains, structure comparison, fold recognition procedures and understanding protein folding, domain stability and flexibility.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70822, 2003, 'bio', 'Examining the independent binding assumption for binding of peptide epitopes to MHC-I molecules', 'Peters, Björn|Tong, Weiwei|Sidney, John|Sette, Alessandro|Weng, Zhiping', 'Institut für Biochemie, Charite, Humboldt Universität Berlin, Monbijoustr. 2, 10117 Berlin, Germany.|Institut für Biochemie, Charite, Humboldt Universität Berlin, Monbijoustr. 2, 10117 Berlin, Germany.|Institut für Biochemie, Charite, Humboldt Universität Berlin, Monbijoustr. 2, 10117 Berlin, Germany.|Institut für Biochemie, Charite, Humboldt Universität Berlin, Monbijoustr. 2, 10117 Berlin, Germany.|Institut für Biochemie, Charite, Humboldt Universität Berlin, Monbijoustr. 2, 10117 Berlin, Germany.', 'Germany|Germany|Germany|Germany|Germany', 90, 'Algorithms|Amino Acid Sequence|Binding Sites|Epitopes|HLA-A2 Antigen|Histocompatibility Antigens Class I|Models, Chemical|Molecular Sequence Data|Oligopeptides|Protein Binding|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg247', '14512347', 'Various methods have been proposed to predict the binding affinities of peptides to Major Histocompatibility Complex class I (MHC-I) molecules based on experimental binding data. They can be classified into two groups: (1) AIB methods that assume independent contributions of all peptide positions to the binding to MHC-I molecule (e.g. scoring matrices) and (2) general methods which can take into account interactions between different positions (e.g. artificial neural networks). We aim to compare the prediction accuracies of these methods, and quantify the impact of interactions between peptide positions.'),
(70823, 2003, 'bio', 'Haplotype inference by maximum parsimony', 'Wang, Lusheng|Xu, Ying', 'Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, Peoples Republic of China. lwang@cs.citu.edu.hk|Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, Peoples Republic of China. lwang@cs.citu.edu.hk', 'China|China', 112, 'Algorithms|Gene Expression Profiling|Gene Frequency|Haplotypes|Humans|Linkage Disequilibrium|Models, Genetic|Polymorphism, Single Nucleotide|Receptors, Adrenergic, beta-2|Recombination, Genetic|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg239', '14512348', 'Haplotypes have been attracting increasing attention because of their importance in analysis of many fine-scale molecular-genetics data. Since direct sequencing of haplotype via experimental methods is both time-consuming and expensive, haplotype inference methods that infer haplotypes based on genotype samples become attractive alternatives.'),
(70824, 2003, 'bio', 'Identification and quantification of disease-related gene clusters', 'Firneisz, Gábor|Zehavi, Idit|Vermes, Csaba|Hanyecz, Anita|Frieman, Joshua A|Glant, Tibor T', 'Section of Biochemistry and Molecular Biology, Departments of Biochemistry, Orthopedic Surgery and Internal Medicine, Rush University at Rush-Presbyterian-St Lukes Medical Center Chicago, IL 60612, USA.|Section of Biochemistry and Molecular Biology, Departments of Biochemistry, Orthopedic Surgery and Internal Medicine, Rush University at Rush-Presbyterian-St Lukes Medical Center Chicago, IL 60612, USA.|Section of Biochemistry and Molecular Biology, Departments of Biochemistry, Orthopedic Surgery and Internal Medicine, Rush University at Rush-Presbyterian-St Lukes Medical Center Chicago, IL 60612, USA.|Section of Biochemistry and Molecular Biology, Departments of Biochemistry, Orthopedic Surgery and Internal Medicine, Rush University at Rush-Presbyterian-St Lukes Medical Center Chicago, IL 60612, USA.|Section of Biochemistry and Molecular Biology, Departments of Biochemistry, Orthopedic Surgery and Internal Medicine, Rush University at Rush-Presbyterian-St Lukes Medical Center Chicago, IL 60612, USA.|Section of Biochemistry and Molecular Biology, Departments of Biochemistry, Orthopedic Surgery and Internal Medicine, Rush University at Rush-Presbyterian-St Lukes Medical Center Chicago, IL 60612, USA.', 'United States|United States|United States|United States|United States|United States', 14, 'Algorithms|Animals|Arthritis, Rheumatoid|Base Sequence|Cluster Analysis|Gene Expression Profiling|Gene Expression Regulation|Genetic Predisposition to Disease|Genetic Testing|Mice|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg252', '14512349', 'DNA microarray technology and the completion of human and mouse genome sequencing programs are now offering new avenues for the investigation of complex genetic diseases. In particular, this makes possible the study of the spatial distribution of disease-related genes within the genome. We report on the first systematic search for clustering of genes associated with a polygenic autoimmune disease.'),
(70825, 2003, 'bio', 'CLICK and EXPANDER: a system for clustering and visualizing gene expression data', 'Sharan, Roded|Maron-Katz, Adi|Shamir, Ron', 'International Computer Science Institute, 1947 Center St., Suite 600, Berkeley, CA 94704-1198, USA. roded@icsi.berkeley.edu|International Computer Science Institute, 1947 Center St., Suite 600, Berkeley, CA 94704-1198, USA. roded@icsi.berkeley.edu|International Computer Science Institute, 1947 Center St., Suite 600, Berkeley, CA 94704-1198, USA. roded@icsi.berkeley.edu', 'United States|United States|United States', 267, 'Algorithms|Base Sequence|Cell Cycle|Cluster Analysis|Fibroblasts|Gene Expression Profiling|Gene Expression Regulation|HeLa Cells|Humans|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Saccharomyces cerevisiae|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg232', '14512350', 'Microarrays have become a central tool in biological research. Their applications range from functional annotation to tissue classification and genetic network inference. A key step in the analysis of gene expression data is the identification of groups of genes that manifest similar expression patterns. This translates to the algorithmic problem of clustering genes based on their expression patterns.'),
(70826, 2003, 'bio', 'New algorithms for multi-class cancer diagnosis using tumor gene expression signatures', 'Bagirov, A M|Ferguson, B|Ivkovic, S|Saunders, G|Yearwood, J', 'Centre for Informatics and Applied Optimization, University of Ballarat, Ballarat 3353, Australia. a.bagirov@ballarat.edu.au|Centre for Informatics and Applied Optimization, University of Ballarat, Ballarat 3353, Australia. a.bagirov@ballarat.edu.au|Centre for Informatics and Applied Optimization, University of Ballarat, Ballarat 3353, Australia. a.bagirov@ballarat.edu.au|Centre for Informatics and Applied Optimization, University of Ballarat, Ballarat 3353, Australia. a.bagirov@ballarat.edu.au|Centre for Informatics and Applied Optimization, University of Ballarat, Ballarat 3353, Australia. a.bagirov@ballarat.edu.au', 'Australia|Australia|Australia|Australia|Australia', 0, 'Algorithms|Amino Acid Sequence|Biomarkers, Tumor|Cluster Analysis|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Molecular Sequence Data|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg238', '14512351', 'The increasing use of DNA microarray-based tumor gene expression profiles for cancer diagnosis requires mathematical methods with high accuracy for solving clustering, feature selection and classification problems of gene expression data.'),
(70827, 2003, 'bio', 'Controlling false-negative errors in microarray differential expression analysis: a PRIM approach', 'Cole, Steve W|Galic, Zoran|Zack, Jerome A', 'Department of Medicine, Immunology, and Molecular Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1678, USA. coles@ucla.edu|Department of Medicine, Immunology, and Molecular Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1678, USA. coles@ucla.edu|Department of Medicine, Immunology, and Molecular Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1678, USA. coles@ucla.edu', 'United States|United States|United States', 86, 'Algorithms|Artificial Intelligence|False Negative Reactions|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg242', '14512352', 'Theoretical considerations suggest that current microarray screening algorithms may fail to detect many true differences in gene expression (Type II analytic errors). We assessed false negative error rates in differential expression analyses by conventional linear statistical models (e.g. t-test), microarray-adapted variants (e.g. SAM, Cyber-T), and a novel strategy based on hold-out cross-validation. The latter approach employs the machine-learning algorithm Patient Rule Induction Method (PRIM) to infer minimum thresholds for reliable change in gene expression from Boolean conjunctions of fold-induction and raw fluorescence measurements.'),
(70828, 2003, 'bio', 'Transformation and normalization of oligonucleotide microarray data', 'Geller, Sue C|Gregg, Jeff P|Hagerman, Paul|Rocke, David M', 'Department of Mathematics, Texas A&M University, College Station, TX 77843-3368, USA. geller@math.tamu.edu|Department of Mathematics, Texas A&M University, College Station, TX 77843-3368, USA. geller@math.tamu.edu|Department of Mathematics, Texas A&M University, College Station, TX 77843-3368, USA. geller@math.tamu.edu|Department of Mathematics, Texas A&M University, College Station, TX 77843-3368, USA. geller@math.tamu.edu', 'United States|United States|United States|United States', 57, 'Algorithms|Computer Simulation|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg245', '14512353', 'Most methods of analyzing microarray data or doing power calculations have an underlying assumption of constant variance across all levels of gene expression. The most common transformation, the logarithm, results in data that have constant variance at high levels but not at low levels. Rocke and Durbin showed that data from spotted arrays fit a two-component model and Durbin, Hardin, Hawkins, and Rocke, Huber et al. and Munson provided a transformation that stabilizes the variance as well as symmetrizes and normalizes the error structure. We wish to evaluate the applicability of this transformation to the error structure of GeneChip microarrays.'),
(70829, 2003, 'bio', 'Automatic registration of microarray images I Rectangular grid', 'Galinsky, Vitaly L', 'Illumina, Inc., 9885 Towne Centre Dr., San Diego CA 92121, USA. vit@ucsd.edu', 'United States', 0, 'Algorithms|Computer Simulation|Gene Expression Profiling|Image Interpretation, Computer-Assisted|Microscopy, Fluorescence|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg259', '14512354', 'The analysis of high-throughput experiment data provided by microarrays becomes increasingly more and more important part of modern biological science. Microarrays allow to conduct genotyping or gene expression experiments on hundreds of thousands of test genes in parallel. Because of the large and constantly growing amount of experimental data the necessity of efficiency, robustness and complete automation of microarray image analysis algorithms is gaining significant attention in the field of microarray processing.'),
(70830, 2003, 'bio', 'Automatic registration of microarray images II Hexagonal grid', 'Galinsky, Vitaly L', 'Illumina, Inc., 9885 Towne Centre Dr., San Diego, CA 92121, USA. vit@ucsd.edu', 'United States', 36, 'Algorithms|Computer Simulation|Gene Expression Profiling|Image Interpretation, Computer-Assisted|Microscopy, Fluorescence|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg260', '14512355', 'In the first part of this paper the author presented an efficient, robust and completely automated algorithm for spot and block indexing in microarray images with rectangular grids. Although the rectangular grid is currently the most common type of grouping the probes on microarray slides, there is another microarray technology based on bundles of optical fibers where the probes are packed in hexagonal grids. The hexagonal grid provides both advantages and drawbacks over the standard rectangular packing and of course requires adaptation and/or modification of the algorithm of spot indexing presented in the first part of the paper.'),
(70831, 2003, 'bio', 'The design of Jemboss: a graphical user interface to EMBOSS', 'Carver, Tim|Bleasby, Alan', 'MRC UK HGMP Resource Centre, Hinxton, Cambridge CB10 1SB, UK.|MRC UK HGMP Resource Centre, Hinxton, Cambridge CB10 1SB, UK.', 'United Kingdom|United Kingdom', 86, 'Computer Graphics|Database Management Systems|Databases, Factual|Europe|Hypermedia|Information Storage and Retrieval|Internet|Local Area Networks|Molecular Biology|Programming Languages|Software Design|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg251', '14512356', 'Jemboss is a graphical user interface (GUI) for the European Molecular Biology Open Software Suite (EMBOSS). It is being developed at the MRC UK HGMP-RC as part of the EMBOSS project. This paper explains the technical aspects of the Jemboss client-server design. The client-server model optionally allows that a Jemboss user have an account on the remote server. The Jemboss client is written in Java and is downloaded automatically to a users workstation via Java Web Start using the HTML protocol. The client then communicates with the remote server using SOAP (Simple Object Access Protocol). A Tomcat server listens on the remote machine and communicates the SOAP requests to a Jemboss server, again written in Java. This Java server interprets the client requests and executes them through Java Native Interface (JNI) code written in the C language. Another C program having setuid privilege, jembossctl, is called by the JNI code to perform the client requests under the users account on the server. The commands include execution of EMBOSS applications, file management and project management tasks. Jemboss allows the use of JSSE for encryption of communication between the client and server. The GUI parses the EMBOSS Ajax Command Definition language for form generation and maximum input flexibility. Jemboss interacts directly with the EMBOSS libraries to allow dynamic generation of application default settings.'),
(70832, 2003, 'bio', 'An XML message broker framework for exchange and integration of microarray data', 'Tjandra, Donny|Wong, Stephen|Shen, Weimin|Pulliam, Brian|Yu, Elaine|Esserman, Laura', 'UCSF Department of Radiology, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143-0628, USA. donny.tjandra@radiology.ucsf.edu|UCSF Department of Radiology, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143-0628, USA. donny.tjandra@radiology.ucsf.edu|UCSF Department of Radiology, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143-0628, USA. donny.tjandra@radiology.ucsf.edu|UCSF Department of Radiology, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143-0628, USA. donny.tjandra@radiology.ucsf.edu|UCSF Department of Radiology, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143-0628, USA. donny.tjandra@radiology.ucsf.edu|UCSF Department of Radiology, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143-0628, USA. donny.tjandra@radiology.ucsf.edu', 'United States|United States|United States|United States|United States|United States', 4, 'Database Management Systems|Databases, Genetic|Hypermedia|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Software|Software Design|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg246', '14512357', 'Microarrays are an important research tool for the advancement of basic biological sciences. However this technology has yet to be integrated with clinical decision making. We have implemented an information framework based on the Microarray Gene Expression Markup Language (MAGE-ML) specification. We are using this framework to develop a test-bed integrated database application to identify genomic and imaging markers for diagnosis of breast cancer.'),
(70833, 2003, 'bio', 'A tool-kit for cDNA microarray and promoter analysis', 'Shah, N H|King, D C|Shah, P N|Fedoroff, N V', 'The Huck Institute of Life Sciences and The Department of Biology, Pennsylvania State University, University Park, PA 16802, USA. nigam@psu.edu|The Huck Institute of Life Sciences and The Department of Biology, Pennsylvania State University, University Park, PA 16802, USA. nigam@psu.edu|The Huck Institute of Life Sciences and The Department of Biology, Pennsylvania State University, University Park, PA 16802, USA. nigam@psu.edu|The Huck Institute of Life Sciences and The Department of Biology, Pennsylvania State University, University Park, PA 16802, USA. nigam@psu.edu', 'United States|United States|United States|United States', 1, 'Algorithms|Arabidopsis|Database Management Systems|Expressed Sequence Tags|Gene Expression Profiling|Genome, Plant|Oligonucleotide Array Sequence Analysis|Promoter Regions, Genetic|Quality Control|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg253', '14512358', 'We describe two sets of programs for expediting routine tasks in analysis of cDNA microarray data and promoter sequences. The first set permits bad data points to be flagged with respect to a number of parameters and performs normalization in three different ways. It allows combining of result files into comprehensive data sets, evaluation of the quality of both technical and biological replicates and row and/or column standardization of data matrices. The second set supports mapping ESTs in the genome, identifying the corresponding genes and recovering their promoters, analyzing promoters for transcription factor binding sites, and visual representation of the results. The programs are designed primarily for Arabidopsis thaliana researchers, but can be adapted readily for other model systems. Availability and Supplementary information: http://www.personal.psu.edu/nhs109/Programs/'),
(70834, 2003, 'bio', 'RVP-net: online prediction of real valued accessible surface area of proteins from single sequences', 'Ahmad, Shandar|Gromiha, M Michael|Sarai, Akinori', 'Department of Biochemical Engineering and Science, Kyushu Institute of Technology, IZUKA, 820 8502, Fukuoka-ken, Japan and Computational Biology Research Center (CBRC), AIST, 2-41-6, Koto-ku, Tokyo 135 0064, Japan.|Department of Biochemical Engineering and Science, Kyushu Institute of Technology, IZUKA, 820 8502, Fukuoka-ken, Japan and Computational Biology Research Center (CBRC), AIST, 2-41-6, Koto-ku, Tokyo 135 0064, Japan.|Department of Biochemical Engineering and Science, Kyushu Institute of Technology, IZUKA, 820 8502, Fukuoka-ken, Japan and Computational Biology Research Center (CBRC), AIST, 2-41-6, Koto-ku, Tokyo 135 0064, Japan.', 'Japan|Japan|Japan', 81, 'Algorithms|Amino Acid Sequence|Amino Acids|Binding Sites|Databases, Protein|Internet|Macromolecular Substances|Molecular Sequence Data|Online Systems|Protein Binding|Protein Conformation|Proteins|Sequence Analysis, Protein|Software|Solvents|Surface Properties', 'Comparative Study', '10.1093/bioinformatics/btg249', '14512359', 'RVP-net is an online program for the prediction of real valued solvent accessibility. All previous methods of accessible surface area (ASA) predictions classify amino acid residues into exposure states and named them buried or exposed based on different thresholds. Real values in some cases were generated by taking the mid points of these state thresholds. This is the first method, which provides a direct prediction of ASA without making exposure categories and achieves results better than 19% mean absolute error. To facilitate batch processing of several sequences, a standalone version of this tool is also provided.'),
(70835, 2003, 'bio', 'Disulfide by Design: a computational method for the rational design of disulfide bonds in proteins', 'Dombkowski, Alan A', 'Institute of Environmental Health Sciences, Wayne State University, Detroit, MI 48201, USA. domski@wayne.edu', 'United States', 0, 'Algorithms|Binding Sites|Computer Simulation|Computer-Aided Design|Databases, Protein|Disulfides|Drug Design|Information Storage and Retrieval|Models, Molecular|Protein Binding|Protein Engineering|Proteins|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg231', '14512360', 'Disulfide by Design is a program for the design of novel disulfide bonds in proteins. Protein structure files in PDB format are analyzed to identify residue pairs that are likely to form a disulfide bond if the respective amino acids are mutated to cysteines. The output displays residue pairs having the appropriate geometric characteristics for disulfide formation and provides automated generation of modified PDB files including modeled disulfides. Validation demonstrates a high level of accuracy for the algorithm.'),
(70836, 2003, 'bio', 'Batch mode generation of residue-based diagrams of proteins', 'Campagne, Fabien|Bettler, Emmanuel|Vriend, Gert|Weinstein, Harel', 'Institute for Computational Biomedicine and Department of Physiology and Biophysics, Mount Sinai School of Medicine, Box 1218, New York, NY 10029, USA. Fabien.Campagne@mssm.edu|Institute for Computational Biomedicine and Department of Physiology and Biophysics, Mount Sinai School of Medicine, Box 1218, New York, NY 10029, USA. Fabien.Campagne@mssm.edu|Institute for Computational Biomedicine and Department of Physiology and Biophysics, Mount Sinai School of Medicine, Box 1218, New York, NY 10029, USA. Fabien.Campagne@mssm.edu|Institute for Computational Biomedicine and Department of Physiology and Biophysics, Mount Sinai School of Medicine, Box 1218, New York, NY 10029, USA. Fabien.Campagne@mssm.edu', 'United States|United States|United States|United States', 8, 'Amino Acid Sequence|Amino Acids|Computer Graphics|Computer Simulation|Computing Methodologies|Databases, Protein|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg236', '14512361', 'Residue-based diagrams of proteins are graphical representations that can be used in protein information systems. These diagrams make it possible to visually integrate different types of biological information. The approach has been used successfully for membrane proteins. We developed the Residue-based diagram generator to (i) make it possible to generate residue-based diagrams of proteins in a batch mode that is compatible with the needs of information system curators, (ii) allow the generation of residue-based diagrams for families of soluble proteins or domains.'),
(70837, 2003, 'bio', 'L/D Protein Ligand Database (PLD): additional understanding of the nature and specificity of protein-ligand complexes', 'Puvanendrampillai, Dushyanthan|Mitchell, John B O', 'Unilever Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.|Unilever Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.', 'United Kingdom|United Kingdom', 0, 'Amino Acid Sequence|Binding Sites|Database Management Systems|Databases, Protein|Energy Transfer|Information Storage and Retrieval|Internet|Ligands|Macromolecular Substances|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Proteins|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btg243', '14512362', 'The Protein Ligand Database (PLD) is a publicly available web-based database that aims to provide further understanding of protein-ligand interactions. The PLD contains biomolecular data including calculated binding energies, Tanimoto ligand similarity scores and protein percentage sequence similarities. The database has potential for application as a tool in molecular design.'),
(70838, 2003, 'bio', 'MutDB: annotating human variation with functionally relevant data', 'Mooney, Sean D|Altman, Russ B', 'Department of Genetics, Stanford Medical Informatics, Stanford University, 251 Campus Drive, MSOB X-215 Stanford, CA 94305-5479, USA. sdm@stanford.edu|Department of Genetics, Stanford Medical Informatics, Stanford University, 251 Campus Drive, MSOB X-215 Stanford, CA 94305-5479, USA. sdm@stanford.edu', 'United States|United States', 34, 'Database Management Systems|Databases, Genetic|Databases, Protein|Documentation|Genetic Predisposition to Disease|Genetic Variation|Genome, Human|Humans|Information Storage and Retrieval|Mutation|Phenotype|Polymorphism, Single Nucleotide|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btg241', '14512363', 'We have developed a resource, MutDB (http://mutdb.org/), to aid in determining which single nucleotide polymorphisms (SNPs) are likely to alter the function of their associated protein product. MutDB contains protein structure annotations and comparative genomic annotations for 8000 disease-associated mutations and SNPs found in the UCSC Annotated Genome and the human RefSeq gene set. MutDB provides interactive mutation maps at the gene and protein levels, and allows for ranking of their predicted functional consequences based on conservation in multiple sequence alignments.'),
(70839, 2003, 'bio', 'The EMBL sequence version archive', 'Leinonen, Rasko|Nardone, Francesco|Oyewole, Olalekan|Redaschi, Nicole|Stoehr, Peter', 'EMBL Outstation The European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL Outstation The European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL Outstation The European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL Outstation The European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL Outstation The European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 10, 'Archives|Base Sequence|Database Management Systems|Databases, Nucleic Acid|Documentation|Europe|Information Storage and Retrieval|Internet|Online Systems|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btg248', '14512364', 'The EMBL Nucleotide Sequence Database, maintained at the European Bioinformatics institute, is Europes primary nucleotide sequences database. Its entries are subject to changes, but only the most recent versions are preserved in the database. The EMBL Sequence Version Archive is a new publicly available database retaining also the earlier versions of these entries.'),
(70840, 2003, 'bio', 'Soap-HT-BLAST: high throughput BLAST based on Web services', 'Wang, Jiren|Mu, Qing', 'BioInformatics Institute, 30 Medical Drive, Singapore 117609. jiren@bii.a-star.edu.sg|BioInformatics Institute, 30 Medical Drive, Singapore 117609. jiren@bii.a-star.edu.sg', 'Singapore|Singapore', 32, 'Amino Acid Sequence|Computing Methodologies|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btg244', '14512365', 'A high throughput Basic Local Alignment Search Tool (BLAST) system based on Web services is implemented. It provides an alternative BLAST service and allows users to perform multiple BLAST queries at one run in a distributed, parallel environment through the Internet.'),
(70841, 2003, 'bio', 'Parallel BLAST on split databases', 'Mathog, David R', 'Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA. mathog@caltech.edu', 'United States', 56, 'Amino Acid Sequence|Computing Methodologies|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btg250', '14512366', 'BLAST programs often run on large SMP machines where multiple threads can work simultaneously and there is enough memory to cache the databases between program runs. A group of programs is described which allows comparable performance to be achieved with a Beowulf configuration in which no node has enough memory to cache a database but the cluster as an aggregate does. To achieve this result, databases are split into equal sized pieces and stored locally on each node. Each query is run on all nodes in parallel and the resultant BLAST output files from all nodes merged to yield the final output.'),
(70842, 2003, 'bio', 'Computational detection of cis -regulatory modules', 'Aerts, Stein|Van Loo, Peter|Thijs, Gert|Moreau, Yves|De Moor, Bart', 'Department of Electrical Engineering ESAT-SCD, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, Leuven, Belgium. stein.aerts@esat.kuleuven.ac.be|Department of Electrical Engineering ESAT-SCD, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, Leuven, Belgium. stein.aerts@esat.kuleuven.ac.be|Department of Electrical Engineering ESAT-SCD, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, Leuven, Belgium. stein.aerts@esat.kuleuven.ac.be|Department of Electrical Engineering ESAT-SCD, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, Leuven, Belgium. stein.aerts@esat.kuleuven.ac.be|Department of Electrical Engineering ESAT-SCD, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, Leuven, Belgium. stein.aerts@esat.kuleuven.ac.be', 'Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Algorithms|Base Sequence|Binding Sites|Chromosome Mapping|Molecular Sequence Data|Protein Binding|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Software|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btg1052', '14534164', 'The transcriptional regulation of a metazoan gene depends on the cooperative action of multiple transcription factors that bind to cis-regulatory modules (CRMs) located in the neighborhood of the gene. By integrating multiple signals, CRMs confer an organism specific spatial and temporal rate of transcription.'),
(70843, 2003, 'bio', 'Searching for statistically significant regulatory modules', 'Bailey, Timothy L|Noble, William Stafford', 'Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia. tlb@maths.uq.edu.au|Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia. tlb@maths.uq.edu.au', 'Australia|Australia', 96, 'Algorithms|Base Sequence|Binding Sites|Chromosome Mapping|Computer Simulation|Data Interpretation, Statistical|Models, Genetic|Models, Statistical|Molecular Sequence Data|Protein Binding|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Software|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btg1054', '14534166', 'The regulatory machinery controlling gene expression is complex, frequently requiring multiple, simultaneous DNA-protein interactions. The rate at which a gene is transcribed may depend upon the presence or absence of a collection of transcription factors bound to the DNA near the gene. Locating transcription factor binding sites in genomic DNA is difficult because the individual sites are small and tend to occur frequently by chance. True binding sites may be identified by their tendency to occur in clusters, sometimes known as regulatory modules.'),
(70844, 2003, 'bio', 'Ab initio reconstruction of metabolic pathways', 'Boyer, Frédéric|Viari, Alain', 'LSR-IMAG, Saint Martin dHères Cedex, France.|LSR-IMAG, Saint Martin dHères Cedex, France.', 'France|France', 29, 'Algorithms|Binding Sites|Computer Simulation|Models, Biological|Models, Chemical|Protein Binding|Protein Interaction Mapping|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btg1055', '14534167', 'We propose a new formulation for the problem of ab initio metabolic pathway reconstruction. Given a set of biochemical reactions together with their substrates and products, we consider the reactions as transfers of atoms between the chemical compounds and we look for successions of reactions transferring a maximal (or preset) number of atoms between a given source and sink compound. We state this problem as the one of finding a composition of partial injections that maximizes the image size. First, we study the theoretical complexity of this problem, state some related problems and then give a practical algorithm to solve them. Finally, we present two applications of this approach to the reconstruction of the tryptophan biosynthesis pathway and to the glycolysis.'),
(70845, 2003, 'bio', 'HMM sampling and applications to gene finding and alternative splicing', 'Cawley, Simon L|Pachter, Lior', 'Affymetrix, Emeryville, CA 94608, USA.|Affymetrix, Emeryville, CA 94608, USA.', 'United States|United States', 51, 'Algorithms|Alternative Splicing|Artificial Intelligence|Base Sequence|Conserved Sequence|Markov Chains|Molecular Sequence Data|Pattern Recognition, Automated|RNA Splice Sites|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Evaluation Studies', '10.1093/bioinformatics/btg1057', '14534169', 'The standard method of applying hidden Markov models to biological problems is to find a Viterbi (maximal weight) path through the HMM graph. The Viterbi algorithm reduces the problem of finding the most likely hidden state sequence that explains given observations, to a dynamic programming problem for corresponding directed acyclic graphs. For example, in the gene finding application, the HMM is used to find the most likely underlying gene structure given a DNA sequence. In this note we discuss the applications of sampling methods for HMMs. The standard sampling algorithm for HMMs is a variant of the common forward-backward and backtrack algorithms, and has already been applied in the context of Gibbs sampling methods. Nevetheless, the practice of sampling state paths from HMMs does not seem to have been widely adopted, and important applications have been overlooked. We show how sampling can be used for finding alternative splicings for genes, including alternative splicings that are conserved between genes from related organisms. We also show how sampling from the posterior distribution is a natural way to compute probabilities for predicted exons and gene structures being correct under the assumed model. Finally, we describe a new memory efficient sampling algorithm for certain classes of HMMs which provides a practical sampling alternative to the Hirschberg algorithm for optimal alignment. The ideas presented have applications not only to gene finding and HMMs but more generally to stochastic context free grammars and RNA structure prediction.'),
(70846, 2003, 'bio', 'Predicting gene function in Saccharomyces cerevisiae', 'Clare, A|King, R D', 'Department of Computer Science, University of Wales, Aberystwyth, Penglais, Aberystwyth, Wales, UK. afc@aber.ac.uk|Department of Computer Science, University of Wales, Aberystwyth, Penglais, Aberystwyth, Wales, UK. afc@aber.ac.uk', 'United Kingdom|United Kingdom', 90, 'Chromosome Mapping|Computer Simulation|Database Management Systems|Databases, Protein|Gene Expression Profiling|Genome, Fungal|Information Storage and Retrieval|Models, Biological|Open Reading Frames|Saccharomyces cerevisiae Proteins|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/btg1058', '14534170', 'S.cerevisiae is one of the most important model organisms, and has has been the focus of over a century of study. In spite of these efforts, 40% of its open reading frames (ORFs) remain classified as having unknown function (MIPS: Munich Information Center for Protein Sequences). We wished to make predictions for the function of these ORFs using data mining, as we have previously successfully done for the genomes of M.tuberculosis and E.coli. Applying this approach to the larger and eukaryotic S.cerevisiae genome involves modifying the machine learning and data mining algorithms, as this is a larger organism with more data available, and a more challenging functional classification.'),
(70847, 2003, 'bio', 'Exploring potential target genes of signaling pathways by predicting conserved transcription factor binding sites', 'Dieterich, C|Herwig, R|Vingron, M', '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', 0, 'Algorithms|Base Sequence|Binding Sites|Chromosome Mapping|Conserved Sequence|Gene Targeting|Molecular Sequence Data|Protein Binding|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Signal Transduction|Software|Transcription Factors|Transcription, Genetic', 'Evaluation Studies', '10.1093/bioinformatics/btg1059', '14534171', 'Many cellular signaling pathways induce gene expression by activating specific transcription factor complexes. Conventional approaches to the prediction of transcription factor binding sites lead to a notoriously high number of false discoveries. To alleviate this problem, we consider only binding sites that are conserved in man-mouse genomic sequence comparisons. We employ two alternative methods for predicting binding sites: exact matches to validated binding site sequences and weight matrix scans. We then ask the question whether there is a characteristic association between a transcription factor or set thereof to a particular group of genes. Our approach is tested on genes, which are induced in dendritic cells in response to the cells exposure to LPS. We chose this example because the underlying signaling pathways are well understood. We demonstrate the benefit of conserved predicted binding sites in interpreting the LPS experiment. Additionally, we find that both methods for the prediction of conserved binding sites complement one another. Finally, our results suggest a distinct role for SRF in the context of LPS-induced gene expression.'),
(70848, 2003, 'bio', 'Inferring strengths of protein-protein interactions from experimental data using linear programming', 'Hayashida, Morihiro|Ueda, Nobuhisa|Akutsu, Tatsuya', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan.', 'Japan|Japan|Japan', 23, 'Algorithms|Artificial Intelligence|Databases, Protein|Information Storage and Retrieval|Likelihood Functions|Pattern Recognition, Automated|Programming, Linear|Protein Interaction Mapping|Research', 'Journal Article', '10.1093/bioinformatics/btg1061', '14534173', 'Several computational methods have been proposed for inference of protein-protein interactions. Most of the existing methods assume that protein-protein interaction data are given as binary data (i.e. whether or not each protein pair interacts). However, multiple biological experiments are performed for the same protein pairs and thus the ratio (strength) of the number of observed interactions to the number of experiments is available for each protein pair.'),
(70849, 2003, 'bio', 'Upper bounds on maximum likelihood for phylogenetic trees', 'Hendy, Michael D|Holland, Barbara R', 'Allan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North, New Zealand. m.hendy@massey.ac.nz|Allan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North, New Zealand. m.hendy@massey.ac.nz', 'New Zealand|New Zealand', 7, 'Algorithms|Base Sequence|Computer Simulation|Data Interpretation, Statistical|Evolution, Molecular|Likelihood Functions|Models, Genetic|Models, Statistical|Molecular Sequence Data|Phylogeny|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btg1062', '14534174', 'We introduce a mechanism for analytically deriving upper bounds on the maximum likelihood for genetic sequence data on sets of phylogenies. A simple partition bound is introduced for general models. Tighter bounds are developed for the simplest model of evolution, the two state symmetric model of nucleotide substitution under the molecular clock. This follows earlier theoretical work which has been restricted to this model by analytic complexity. A weakness of current numerical computation is that reported maximum likelihood results cannot be guaranteed, both for a specified tree (because of the possibility of multiple maxima) or over the full tree space (as the computation is intractable for large sets of trees). The bounds we develop here can be used to conclusively eliminate large proportions of tree space in the search for the maximum likelihood tree. This is vital in the development of a branch and bound search strategy for identifying the maximum likelihood tree. We report the results from a simulation study of approximately 10(6) data sets generated on clock-like trees of five leaves. In each trial a likelihood value of one specific instance of a parameterised tree is compared to the bound determined for each of the 105 possible rooted binary trees. The proportion of trees that are eliminated from the search for the maximum likelihood tree ranged from 92% to almost 98%, indicating a computational speed-up factor of between 12 and 44.'),
(70850, 2003, 'bio', 'A rapid method for detection of putative RNAi target genes in genomic data', 'Horesh, Yair|Amir, Amihood|Michaeli, Shulamit|Unger, Ron', 'Department of Computer Science and Faculty of Life Sciences Bar-Ilan University, Ramat-Gan, Israel.|Department of Computer Science and Faculty of Life Sciences Bar-Ilan University, Ramat-Gan, Israel.|Department of Computer Science and Faculty of Life Sciences Bar-Ilan University, Ramat-Gan, Israel.|Department of Computer Science and Faculty of Life Sciences Bar-Ilan University, Ramat-Gan, Israel.', 'Israel|Israel|Israel|Israel', 1, 'Animals|Base Sequence|Caenorhabditis|Chromosome Mapping|Databases, Genetic|Gene Targeting|Molecular Sequence Data|RNA Interference|RNA, Small Interfering|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btg1063', '14534175', 'RNAi, inhibition of gene expression by double stranded RNA molecules, has rapidly become a powerful laboratory technique to study gene function. The effectiveness of the procedure raised the question of whether this laboratory technique may actually mimic a natural cellular control mechanism that works on similar principles. Indeed recent evidence is accumulating to suggest that RNAi is a natural control mechanism that might even serve as a primitive immune response against RNA viruses and retroposons. Three different interference scenarios seem to be utilized by various RNAi mechanisms. One of the mechanisms involves degradation of mRNA molecules. Here we suggest a method to systematically scan entire genomes simultaneously for RNAi elements and the presence of cellular genes that are degraded by these RNAi elements via exact short base-pair matching. The method is based on scanning the genomes using a suffix tree data structure that was specifically modified to identify sets of combinations of repeated and inverted repeated sequences of 20 bp or more. Initial scan suggest that a large number, about 7% of C.elegans and 3% of C.briggsae genes, have the potential to be subject to natural RNAi control. Two methods are proposed to further analyze these genes to select the cases that are more likely to be actual cases of RNAi control. One method involves looking for ESTs that can provide direct evidence that RNAi control element are indeed expressed. The other method looks for synteny between C.elegans and C.briggsae assuming that genes that might be under RNAi control in both organisms are more likely to be biological significant. Taken together, supportive evidence was found for about 70 genes to be under RNAi control. Among these genes are: transposase, hormone receptors, homeobox proteins, defensin, actins, and several types of collagens. While our method is not capable of detecting all cases of natural RNAi control, it points to a large number of potential cases that can be further verified by experimental work.'),
(70851, 2003, 'bio', 'A novel approach to fold recognition using sequence-derived properties from sets of structurally similar local fragments of proteins', 'Hvidsten, Torgeir R|Kryshtafovych, Andriy|Komorowski, Jan|Fidelis, Krzysztof', 'The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden.', 'Sweden|Sweden|Sweden|Sweden', 0, 'Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Folding|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btg1064', '14534176', 'Comparative modeling methods can consistently produce reliable structural models for protein sequences with more than 25% sequence identity to proteins with known structure. However, there is a good chance that also sequences with lower sequence identity have their structural components represented in structural databases. To this end, we present a novel fragment-based method using sets of structurally similar local fragments of proteins. The approach differs from other fragment-based methods that use only single backbone fragments. Instead, we use a library of groups containing sets of sequence fragments with geometrically similar local structures and extract sequence related properties to assign these specific geometrical conformations to target sequences. We test the ability of the approach to recognize correct SCOP folds for 273 sequences from the 49 most popular folds. 49% of these sequences have the correct fold as their top prediction, while 82% have the correct fold in one of the top five predictions. Moreover, the approach shows no performance reduction on a subset of sequence targets with less than 10% sequence identity to any protein used to build the library.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70852, 2003, 'bio', 'Discovery of significant rules for classifying cancer diagnosis data', 'Li, Jinyan|Liu, Huiqing|Ng, See-Kiong|Wong, Limsoon', 'Institute for Infocomm Research, Heng Mui Keng Terrace, Singapore. jinyan@i2r.a-star.edu.sg|Institute for Infocomm Research, Heng Mui Keng Terrace, Singapore. jinyan@i2r.a-star.edu.sg|Institute for Infocomm Research, Heng Mui Keng Terrace, Singapore. jinyan@i2r.a-star.edu.sg|Institute for Infocomm Research, Heng Mui Keng Terrace, Singapore. jinyan@i2r.a-star.edu.sg', 'Singapore|Singapore|Singapore|Singapore', 0, 'Algorithms|Biomarkers, Tumor|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Neoplasm Proteins|Neoplasms|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1093/bioinformatics/btg1066', '14534178', 'We introduce a new method to discover many diversified and significant rules from high dimensional profiling data. We also propose to aggregate the discriminating power of these rules for reliable predictions. The discovered rules are found to contain low-ranked features, these features are found to be sometimes necessary for classifiers to achieve perfect accuracy. The use of low-ranked but essential features in our method is in contrast to the prevailing use of an ad-hoc number of only top-ranked features. On a wide range of data sets, our method displayed highly competitive accuracy compared to the best performance of other kinds of classification models. In addition to accuracy, our method also provides comprehensible rules to help elucidate the translation between raw data and useful knowledge.'),
(70853, 2003, 'bio', 'Modeling sequencing errors by combining Hidden Markov models', 'Lottaz, C|Iseli, C|Jongeneel, C V|Bucher, P', 'Swiss Institute of Bioinformatics, Switzerland. Claudio.Lottaz@molgen.mpg.de|Swiss Institute of Bioinformatics, Switzerland. Claudio.Lottaz@molgen.mpg.de|Swiss Institute of Bioinformatics, Switzerland. Claudio.Lottaz@molgen.mpg.de|Swiss Institute of Bioinformatics, Switzerland. Claudio.Lottaz@molgen.mpg.de', 'Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Algorithms|Base Sequence|Computer Simulation|Data Interpretation, Statistical|Databases, Genetic|Expressed Sequence Tags|Information Storage and Retrieval|Markov Chains|Models, Genetic|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btg1067', '14534179', 'Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.'),
(70854, 2003, 'bio', 'A suffix tree approach to the interpretation of tandem mass spectra: applications to peptides of non-specific digestion and post-translational modifications', 'Lu, Bingwen|Chen, Ting', 'Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.|Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.', 'United States|United States', 37, 'Algorithms|Amino Acid Sequence|Mass Spectrometry|Molecular Sequence Data|Peptide Mapping|Protein Processing, Post-Translational|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btg1068', '14534180', 'Tandem mass spectrometry combined with sequence database searching is one of the most powerful tools for protein identification. As thousands of spectra are generated by a mass spectrometer in one hour, the speed of database searching is critical, especially when searching against a large sequence database, or when the peptide is generated by some unknown or non-specific enzyme, even or when the target peptides have post-translational modifications (PTM). In practice, about 70-90% of the spectra have no match in the database. Many believe that a significant portion of them are due to peptides of non-specific digestions by unknown enzymes or amino acid modifications. In another case, scientists may choose to use some non-specific enzymes such as pepsin or thermolysin for proteolysis in proteomic study, in that not all proteins are amenable to be digested by some site-specific enzymes, and furthermore many digested peptides may not fall within the rang of molecular weight suitable for mass spectrometry analysis. Interpreting mass spectra of these kinds will cost a lot of computational time of database search engines.'),
(70855, 2003, 'bio', 'Artificial gene networks for objective comparison of analysis algorithms', 'Mendes, Pedro|Sha, Wei|Ye, Keying', 'Virginia Bioinformatics Institute, USA. mendes@vt.edu|Virginia Bioinformatics Institute, USA. mendes@vt.edu|Virginia Bioinformatics Institute, USA. mendes@vt.edu', 'United States|United States|United States', 0, 'Algorithms|Computer Simulation|Gene Expression|Gene Expression Profiling|Models, Biological|Proteome|Sensitivity and Specificity|Signal Transduction|Software|Software Validation', 'Comparative Study', '10.1093/bioinformatics/btg1069', '14534181', 'Large-scale gene expression profiling generates data sets that are rich in observed features but poor in numbers of observations. The analysis of such data sets is a challenge that has been object of vigorous research. The algorithms in use for this purpose have been poorly documented and rarely compared objectively, posing a problem of uncertainty about the outcomes of the analyses. One way to objectively test such analysis algorithms is to apply them on computational gene network models for which the mechanisms are completely know.'),
(70856, 2003, 'bio', 'MCMC genome rearrangement', 'Miklós, István', 'Department of Statistics, University of Oxford, Oxford, UK. miklos@stats.ox.ac.uk', 'United Kingdom', 22, 'Algorithms|Base Sequence|Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Evolution, Molecular|Gene Rearrangement|Linkage Disequilibrium|Markov Chains|Models, Genetic|Models, Statistical|Molecular Sequence Data|Monte Carlo Method|Mutation|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btg1070', '14534182', 'As more and more genomes have been sequenced, genomic data is rapidly accumulating. Genome-wide mutations are believed more neutral than local mutations such as substitutions, insertions and deletions, therefore phylogenetic investigations based on inversions, transpositions and inverted transpositions are less biased by the hypothesis on neutral evolution. Although efficient algorithms exist for obtaining the inversion distance of two signed permutations, there is no reliable algorithm when both inversions and transpositions are considered. Moreover, different type of mutations happen with different rates, and it is not clear how to weight them in a distance based approach.'),
(70857, 2003, 'bio', 'Gene networks inference using dynamic Bayesian networks', 'Perrin, Bruno-Edouard|Ralaivola, Liva|Mazurie, Aurélien|Bottani, Samuele|Mallet, Jacques|dAlché-Buc, Florence', 'Laboratoire dInformatique de Paris 6, CNRS UMR 7606, Paris, France. perrin@poleia.lip6.fr|Laboratoire dInformatique de Paris 6, CNRS UMR 7606, Paris, France. perrin@poleia.lip6.fr|Laboratoire dInformatique de Paris 6, CNRS UMR 7606, Paris, France. perrin@poleia.lip6.fr|Laboratoire dInformatique de Paris 6, CNRS UMR 7606, Paris, France. perrin@poleia.lip6.fr|Laboratoire dInformatique de Paris 6, CNRS UMR 7606, Paris, France. perrin@poleia.lip6.fr|Laboratoire dInformatique de Paris 6, CNRS UMR 7606, Paris, France. perrin@poleia.lip6.fr', 'France|France|France|France|France|France', 311, 'Algorithms|Artificial Intelligence|Bayes Theorem|Computer Simulation|DNA Repair|Data Interpretation, Statistical|Escherichia coli|Escherichia coli Proteins|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Pattern Recognition, Automated|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btg1071', '14534183', 'This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactions capable of handling missing variables is proposed. It can be described as a dynamic Bayesian network particularly well suited to tackle the stochastic nature of gene regulation and gene expression measurement. Parameters of the model are learned through a penalized likelihood maximization implemented through an extended version of EM algorithm. Our approach is tested against experimental data relative to the S.O.S. DNA Repair network of the Escherichia coli bacterium. It appears to be able to extract the main regulations between the genes involved in this network. An added missing variable is found to model the main protein of the network. Good prediction abilities on unlearned data are observed. These first results are very promising: they show the power of the learning algorithm and the ability of the model to capture gene interactions.'),
(70858, 2003, 'bio', 'Finding subtle motifs by branching from sample strings', 'Price, Alkes|Ramabhadran, Sriram|Pevzner, Pavel A', 'Department of Computer Science and Engineering, University of California at San Diego, La Jolla, CA 92093-0114, USA. aprice@cs.ucsd.edu|Department of Computer Science and Engineering, University of California at San Diego, La Jolla, CA 92093-0114, USA. aprice@cs.ucsd.edu|Department of Computer Science and Engineering, University of California at San Diego, La Jolla, CA 92093-0114, USA. aprice@cs.ucsd.edu', 'United States|United States|United States', 72, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Base Sequence|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btg1072', '14534184', 'Many motif finding algorithms apply local search techniques to a set of seeds. For example, GibbsDNA (Lawrence et al. 1993, Science, 262, 208-214) applies Gibbs sampling to random seeds, and MEME (Bailey and Elkan, 1994, Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology (ISMB-94), 28-36) applies the EM algorithm to selected sample strings, i.e. substrings of the sample. In the case of subtle motifs, recent benchmarking efforts show that both random seeds and selected sample strings may never get close to the globally optimal motif. We propose a new approach which searches motif space by branching from sample strings, and implement this idea in both pattern-based and profile-based settings. Our PatternBranching and ProfileBranching algorithms achieve favorable results relative to other motif finding algorithms.'),
(70859, 2003, 'bio', 'The shortest common supersequence problem in a microarray production setting', 'Rahmann, Sven', 'Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. Sven.Rahmann@molgen.mpg.de', 'Germany', 29, 'Algorithms|Base Sequence|DNA|DNA Probes|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg1073', '14534185', 'During microarray production, several thousands of oligonucleotides (short DNA sequences) are synthesized in parallel, one nucleotide at a time. We are interested in finding the shortest possible nucleotide deposition sequence to synthesize all oligos in order to reduce production time and increase oligo quality. Thus we study the shortest common super-sequence problem of several thousand short strings over a four-letter alphabet.'),
(70860, 2003, 'bio', 'Reconstructing tumor genome architectures', 'Raphael, Benjamin J|Volik, Stanislav|Collins, Colin|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|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|United States|United States', 47, 'Algorithms|Base Sequence|Breast Neoplasms|Chromosome Mapping|DNA Mutational Analysis|DNA, Neoplasm|Genetic Predisposition to Disease|Humans|Molecular Sequence Data|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btg1074', '14534186', 'Although cancer progression is often associated with genome rearrangements, little is known about the detailed genomic architecture of tumor genomes. The attempt to reconstruct the genomic organization of a tumor genome recently resulted in the development of the End Sequence Profiling (ESP) technique, and the application of this technique to human MCF7 tumor cells. We formulate the ESP Genome Reconstruction Problem, and develop an algorithm to solve this problem in the case of sparse ESP data. We apply our algorithm to analyze human MCF7 tumor cells, and obtain the first reconstruction of the putative architecture of human MCF7 tumor genome. Our results assist in the ongoing ESP analysis of MCF7 tumors by suggesting additional ESP experiments for the completion of a reliable reconstruction of the MCF7 tumor genome, and by focusing BAC re-sequencing efforts.'),
(70861, 2003, 'bio', 'A description of dynamical graphs associated to elementary regulatory circuits', 'Remy, E|Mossé, B|Chaouiya, C|Thieffry, D', 'Institut de Mathématiques de Luminy, Campus de Luminy, Marseille cedex 9, France. remy@iml.univ-mrs.fr|Institut de Mathématiques de Luminy, Campus de Luminy, Marseille cedex 9, France. remy@iml.univ-mrs.fr|Institut de Mathématiques de Luminy, Campus de Luminy, Marseille cedex 9, France. remy@iml.univ-mrs.fr|Institut de Mathématiques de Luminy, Campus de Luminy, Marseille cedex 9, France. remy@iml.univ-mrs.fr', 'France|France|France|France', 46, 'Algorithms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btg1075', '14534187', 'The biological and dynamical importance of feedback circuits in regulatory graphs has often been emphasized. The work presented here aims at completely describing the dynamics of isolated elementary regulatory circuits. Our analytical approach is based on a discrete formal framework, built upon the logical approach of R. Thomas. Given a regulatory circuit, we show that the structure of synchronous and asynchronous dynamical graphs depends only on the length of the circuit (number of genes) and on its sign (which depends on the parity of the number of negative interactions). This work constitutes a first step towards the analytical characterisation of discrete dynamical graphs for more complex regulatory networks in terms of contributions corresponding to their embedded elementary circuits.'),
(70862, 2003, 'bio', 'Fast feature selection using a simple estimation of distribution algorithm: a case study on splice site prediction', 'Saeys, Yvan|Degroeve, Sven|Aeyels, Dirk|Van De Peer, Yves|Rouzé, Pierre', 'Department of Plant Systems Biology, Ghent University, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent, Belgium. yvsae@gengenp.rug.ac.be|Department of Plant Systems Biology, Ghent University, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent, Belgium. yvsae@gengenp.rug.ac.be|Department of Plant Systems Biology, Ghent University, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent, Belgium. yvsae@gengenp.rug.ac.be|Department of Plant Systems Biology, Ghent University, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent, Belgium. yvsae@gengenp.rug.ac.be|Department of Plant Systems Biology, Ghent University, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent, Belgium. yvsae@gengenp.rug.ac.be', 'Belgium|Belgium|Belgium|Belgium|Belgium', 49, 'Algorithms|Alternative Splicing|Arabidopsis|Artificial Intelligence|Chromosome Mapping|Computer Simulation|DNA, Plant|Genome, Plant|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Sequence Analysis, DNA|Statistical Distributions', 'Evaluation Studies', '10.1093/bioinformatics/btg1076', '14534188', 'Feature subset selection is an important preprocessing step for classification. In biology, where structures or processes are described by a large number of features, the elimination of irrelevant and redundant information in a reasonable amount of time has a number of advantages. It enables the classification system to achieve good or even better solutions with a restricted subset of features, allows for a faster classification, and it helps the human expert focus on a relevant subset of features, hence providing useful biological knowledge.'),
(70863, 2003, 'bio', 'Divide-and-conquer multiple alignment with segment-based constraints', 'Sammeth, Michael|Morgenstern, Burkhard|Stoye, Jens', 'Bielefeld University, Department of Genome Informatics, Technical Faculty, Bielefeld, Germany. micha@sammeth.net|Bielefeld University, Department of Genome Informatics, Technical Faculty, Bielefeld, Germany. micha@sammeth.net|Bielefeld University, Department of Genome Informatics, Technical Faculty, Bielefeld, Germany. micha@sammeth.net', 'Germany|Germany|Germany', 13, 'Algorithms|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btg1077', '14534189', 'A large number of methods for multiple sequence alignment are currently available. Recent benchmarking tests demonstrated that strengths and drawbacks of these methods differ substantially. Global strategies can be outperformed by approaches based on local similarities and vice versa, depending on the characteristics of the input sequences. In recent years, mixed approaches that include both global and local features have shown promising results. Herein, we introduce a new algorithm for multiple sequence alignment that integrates the global divide-and-conquer approach with the local segment-based approach, thereby combining the strengths of those two strategies.'),
(70864, 2003, 'bio', 'Biclustering microarray data by Gibbs sampling', 'Sheng, Qizheng|Moreau, Yves|De Moor, Bart', 'Department of Electrical Engineering ESAT-SCD, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium. qizheng.sheng@esat.kuleuven.ac.be|Department of Electrical Engineering ESAT-SCD, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium. qizheng.sheng@esat.kuleuven.ac.be|Department of Electrical Engineering ESAT-SCD, Katholieke Universiteit Leuven, Leuven-Heverlee, Belgium. qizheng.sheng@esat.kuleuven.ac.be', 'Belgium|Belgium|Belgium', 139, 'Biomarkers, Tumor|Cluster Analysis|Data Interpretation, Statistical|Gene Expression Profiling|Genetic Predisposition to Disease|Humans|Leukemia|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btg1078', '14534190', 'Gibbs sampling has become a method of choice for the discovery of noisy patterns, known as motifs, in DNA and protein sequences. Because handling noise in microarray data presents similar challenges, we have adapted this strategy to the biclustering of discretized microarray data.'),
(70865, 2003, 'bio', 'Finding optimal degenerate patterns in DNA sequences', 'Shinozaki, Daisuke|Akutsu, Tatsuya|Maruyama, Osamu', 'Graduate School of Mathematics, Kyushu University, Fukuoka, Japan.|Graduate School of Mathematics, Kyushu University, Fukuoka, Japan.|Graduate School of Mathematics, Kyushu University, Fukuoka, Japan.', 'Japan|Japan|Japan', 14, 'Algorithms|Base Sequence|Binding Sites|Chromosome Mapping|DNA Mutational Analysis|Molecular Sequence Data|Mutation|Protein Binding|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Software|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btg1079', '14534191', 'The problem of finding transcription factor binding sites in the upstream regions of given genes is algorithmically an interesting and challenging problem in computational biology. A degenerate pattern over a finite alphabet Sigma is a sequence of subsets of Sigma. A string over IUPAC nucleic acid codes is also a degenerate pattern over Sigma = {A, C, G, T}, and is used as one of the major patterns modeling transcription factor binding sites in the upstream regions of genes. However, it is known that the problem of finding a degenerate pattern consistent with both positive and negative string sets is in general NP-complete. Our aim is to devise a heuristic algorithm to find a degenerate pattern which is optimal for positive and negative string sets w.r.t. a given score function.'),
(70866, 2003, 'bio', 'Gene prediction with a hidden Markov model and a new intron submodel', 'Stanke, Mario|Waack, Stephan', 'Institut für Mikrobiologie und Genetik, Abteilung Bioinformatik, Universität Göttingen, Göttingen, Germany. mstanke@gwdg.de|Institut für Mikrobiologie und Genetik, Abteilung Bioinformatik, Universität Göttingen, Göttingen, Germany. mstanke@gwdg.de', 'Germany|Germany', 641, 'Algorithms|Animals|Artificial Intelligence|Base Sequence|Computer Simulation|Humans|Introns|Markov Chains|Models, Genetic|Molecular Sequence Data|Pattern Recognition, Automated|RNA Splice Sites|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btg1080', '14534192', 'The problem of finding the genes in eukaryotic DNA sequences by computational methods is still not satisfactorily solved. Gene finding programs have achieved relatively high accuracy on short genomic sequences but do not perform well on longer sequences with an unknown number of genes in them. Here existing programs tend to predict many false exons.'),
(70867, 2003, 'bio', 'Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection', 'Tamada, Yoshinori|Kim, SunYong|Bannai, Hideo|Imoto, Seiya|Tashiro, Kousuke|Kuhara, Satoru|Miyano, Satoru', 'Human Genome Center, Institute of Medical Science, The University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan.|Human Genome Center, Institute of Medical Science, The University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 139, 'Bayes Theorem|Computer Simulation|Data Interpretation, Statistical|Gene Expression|Gene Expression Profiling|Models, Biological|Promoter Regions, Genetic|Proteome|Sequence Analysis, DNA|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btg1082', '14534194', 'We present a statistical method for estimating gene networks and detecting promoter elements simultaneously. When estimating a network from gene expression data alone, a common problem is that the number of microarrays is limited compared to the number of variables in the network model, making accurate estimation a difficult task. Our method overcomes this problem by integrating the microarray gene expression data and the DNA sequence information into a Bayesian network model. The basic idea of our method is that, if a parent gene is a transcription factor, its children may share a consensus motif in their promoter regions of the DNA sequences. Our method detects consensus motifs based on the structure of the estimated network, then re-estimates the network using the result of the motif detection. We continue this iteration until the network becomes stable. To show the effectiveness of our method, we conducted Monte Carlo simulations and applied our method to Saccharomyces cerevisiae data as a real application.'),
(70868, 2003, 'bio', 'Extracting active pathways from gene expression data', 'Vert, Jean Philippe|Kanehisa, Minoru', 'Centre de Géostatistique, Ecole des Mines de Paris, Fontainebleau cedex, France. Jean-Philippe.Vert@mines.org|Centre de Géostatistique, Ecole des Mines de Paris, Fontainebleau cedex, France. Jean-Philippe.Vert@mines.org', 'France|France', 39, 'Algorithms|Computer Simulation|Database Management Systems|Databases, Protein|Gene Expression|Gene Expression Profiling|Information Storage and Retrieval|Models, Biological|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btg1084', '14534196', 'A promising way to make sense out of gene expression profiles is to relate them to the activity of metabolic and signalling pathways. Each pathway usually involves many genes, such as enzymes, which can themselves participate in many pathways. The set of all known pathways can therefore be represented by a complex network of genes. Searching for regularities in the set of gene expression profiles with respect to the topology of this gene network is a way to automatically extract active pathways and their associated patterns of activity.'),
(70869, 2003, 'bio', 'Flexible structure alignment by chaining aligned fragment pairs allowing twists', 'Ye, Yuzhen|Godzik, Adam', 'Program in Bioinformatics and Systems Biology, The Burnham Institute, La Jolla, CA 92037, USA.|Program in Bioinformatics and Systems Biology, The Burnham Institute, La Jolla, CA 92037, USA.', 'United States|United States', 428, 'Algorithms|Amino Acid Sequence|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btg1086', '14534198', 'Protein structures are flexible and undergo structural rearrangements as part of their function, and yet most existing protein structure comparison methods treat them as rigid bodies, which may lead to incorrect alignment.'),
(70870, 2003, 'bio', 'Greedily building protein networks with confidence', 'Bader, Joel S', 'CuraGen Corporation, 555 Long Wharf Drive, New Haven, CT 06511, USA. jbader@bme.jhu.edu', 'United States', 47, 'Algorithms|Combinatorial Chemistry Techniques|Computer Simulation|DNA Repair|Models, Biological|Protein Binding|Protein Interaction Mapping|Proteins|Proteome|Quality Control|Signal Transduction|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg358', '14555618', 'With genome sequences complete for human and model organisms, it is essential to understand how individual genes and proteins are organized into biological networks. Much of the organization is revealed by proteomics experiments that now generate torrents of data. Extracting relevant complexes and pathways from high-throughput proteomics data sets has posed a challenge, however, and new methods to identify and extract networks are essential. We focus on the problem of building pathways starting from known proteins of interest.'),
(70871, 2003, 'bio', 'Learning to predict protein-protein interactions from protein sequences', 'Gomez, Shawn M|Noble, William Stafford|Rzhetsky, Andrey', 'Unité de Biochimie et Biologie Moléculaire des Insectes, Institut Pasteur, 75724 Paris Cedex 15, France. sgomez@pasteur.fr|Unité de Biochimie et Biologie Moléculaire des Insectes, Institut Pasteur, 75724 Paris Cedex 15, France. sgomez@pasteur.fr|Unité de Biochimie et Biologie Moléculaire des Insectes, Institut Pasteur, 75724 Paris Cedex 15, France. sgomez@pasteur.fr', 'France|France|France', 131, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Binding Sites|Computer Simulation|Fungal Proteins|Models, Biological|Models, Chemical|Molecular Sequence Data|Pattern Recognition, Automated|Protein Binding|Protein Interaction Mapping|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg352', '14555619', 'In order to understand the molecular machinery of the cell, we need to know about the multitude of protein-protein interactions that allow the cell to function. High-throughput technologies provide some data about these interactions, but so far that data is fairly noisy. Therefore, computational techniques for predicting protein-protein interactions could be of significant value. One approach to predicting interactions in silico is to produce from first principles a detailed model of a candidate interaction. We take an alternative approach, employing a relatively simple model that learns dynamically from a large collection of data. In this work, we describe an attraction-repulsion model, in which the interaction between a pair of proteins is represented as the sum of attractive and repulsive forces associated with small, domain- or motif-sized features along the length of each protein. The model is discriminative, learning simultaneously from known interactions and from pairs of proteins that are known (or suspected) not to interact. The model is efficient to compute and scales well to very large collections of data. In a cross-validated comparison using known yeast interactions, the attraction-repulsion method performs better than several competing techniques.'),
(70872, 2003, 'bio', 'A fast layout algorithm for protein interaction networks', 'Han, Kyungsook|Ju, Byong-Hyon', 'School of Computer Science & Engineering, Inha University, Inchon 402-751, Korea. khan@inha.ac.kr|School of Computer Science & Engineering, Inha University, Inchon 402-751, Korea. khan@inha.ac.kr', '-|-', 27, 'Algorithms|Combinatorial Chemistry Techniques|Computer Graphics|DNA Repair|Models, Biological|Models, Chemical|Protein Binding|Protein Interaction Mapping|Proteins|Proteome|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Signal Transduction|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg346', '14555620', 'Graph drawing algorithms are often used for visualizing relational information, but a naive implementation of a graph drawing algorithm encounters real difficulties when drawing large-scale graphs such as protein interaction networks.'),
(70873, 2003, 'bio', 'Simple stochastic birth and death models of genome evolution: was there enough time for us to evolve?', 'Karev, Georgy P|Wolf, Yuri I|Koonin, Eugene V', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.', 'United States|United States|United States', 41, 'Computer Simulation|Evolution, Molecular|Gene Deletion|Gene Duplication|Genetic Variation|Genome|Models, Genetic|Models, Statistical|Mutation|Protein Structure, Tertiary|Proteins|Stochastic Processes', 'Evaluation Studies', '10.1093/bioinformatics/btg351', '14555621', 'The distributions of many genome-associated quantities, including the membership of paralogous gene families can be approximated with power laws. We are interested in developing mathematical models of genome evolution that adequately account for the shape of these distributions and describe the evolutionary dynamics of their formation.'),
(70874, 2003, 'bio', 'A comprehensive set of protein complexes in yeast: mining large scale protein-protein interaction screens', 'Krause, Roland|von Mering, Christian|Bork, Peer', 'Cellzome AG, Meyerhofstrasse 1, 69117 Heidelberg, Germany. roland.krause@cellzome.com|Cellzome AG, Meyerhofstrasse 1, 69117 Heidelberg, Germany. roland.krause@cellzome.com|Cellzome AG, Meyerhofstrasse 1, 69117 Heidelberg, Germany. roland.krause@cellzome.com', 'Germany|Germany|Germany', 0, 'Algorithms|Cluster Analysis|Fungal Proteins|Information Storage and Retrieval|Mass Spectrometry|Pattern Recognition, Automated|Protein Interaction Mapping|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Software', 'Comparative Study', '10.1093/bioinformatics/btg344', '14555622', 'The analysis of protein-protein interactions allows for detailed exploration of the cellular machinery. The biochemical purification of protein complexes followed by identification of components by mass spectrometry is currently the method, which delivers the most reliable information--albeit that the data sets are still difficult to interpret. Consolidating individual experiments into protein complexes, especially for high-throughput screens, is complicated by many contaminants, the occurrence of proteins in otherwise dissimilar purifications due to functional re-use and technical limitations in the detection. A non-redundant collection of protein complexes from experimental data would be useful for biological interpretation, but manual assembly is tedious and often inconsistent.'),
(70875, 2003, 'bio', 'Topology of gene expression networks as revealed by data mining and modeling', 'Lukashin, Alexander V|Lukashev, Matvey E|Fuchs, Rainer', 'Biogen Inc., 14 Cambridge Center, Cambridge, MA 02142, USA. alex_lukashin@biogen.com|Biogen Inc., 14 Cambridge Center, Cambridge, MA 02142, USA. alex_lukashin@biogen.com|Biogen Inc., 14 Cambridge Center, Cambridge, MA 02142, USA. alex_lukashin@biogen.com', 'United States|United States|United States', 0, 'Algorithms|Cell Line, Tumor|Cell Physiological Phenomena|Cluster Analysis|Computer Simulation|Databases, Protein|Gene Expression Profiling|Gene Expression Regulation|Humans|Information Storage and Retrieval|Models, Biological|Neoplasms|Protein Interaction Mapping|Signal Transduction|Yeasts', 'Journal Article', '10.1093/bioinformatics/btg333', '14555623', 'Interpretation of high-throughput gene expression profiling requires a knowledge of the design principles underlying the networks that sustain cellular machinery. Recently a novel approach based on the study of network topologies has been proposed. This methodology has proven to be useful for the analysis of a variety of biological systems, including metabolic networks, networks of protein-protein interactions, and gene networks that can be derived from gene expression data. In the present paper, we focus on several important issues related to the topology of gene expression networks that have not yet been fully studied.'),
(70876, 2003, 'bio', 'Prediction of regulatory networks: genome-wide identification of transcription factor targets from gene expression data', 'Qian, Jiang|Lin, Jimmy|Luscombe, Nicholas M|Yu, Haiyuan|Gerstein, Mark', 'Department of Ophthalmology, Johns Hopkins Medical School, Baltimore, MD 21287, USA.|Department of Ophthalmology, Johns Hopkins Medical School, Baltimore, MD 21287, USA.|Department of Ophthalmology, Johns Hopkins Medical School, Baltimore, MD 21287, USA.|Department of Ophthalmology, Johns Hopkins Medical School, Baltimore, MD 21287, USA.|Department of Ophthalmology, Johns Hopkins Medical School, Baltimore, MD 21287, USA.', 'United States|United States|United States|United States|United States', 100, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computer Simulation|Databases, Protein|Gene Expression Profiling|Gene Expression Regulation|Gene Targeting|Genome|Models, Biological|Protein Binding|Protein Interaction Mapping|Proteome|Transcription Factors|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg347', '14555624', 'Defining regulatory networks, linking transcription factors (TFs) to their targets, is a central problem in post-genomic biology. One might imagine one could readily determine these networks through inspection of gene expression data. However, the relationship between the expression timecourse of a transcription factor and its target is not obvious (e.g. simple correlation over the timecourse), and current analysis methods, such as hierarchical clustering, have not been very successful in deciphering them.'),
(70877, 2003, 'bio', 'Automatic discovery and classification of bioinformatics Web sources', 'Rocco, Daniel|Critchlow, Terence', 'College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, USA. rockdj@gatech.edu|College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, USA. rockdj@gatech.edu', 'Georgia|Georgia', 0, 'Algorithms|Computational Biology|Database Management Systems|Databases, Protein|Hypermedia|Information Storage and Retrieval|Internet|Proteins', 'Evaluation Studies', '10.1093/bioinformatics/btg353', '14555625', 'The World Wide Web provides an incredible resource to genomics researchers in the form of query access to distributed data sources--e.g. BLAST sequence homology search interfaces. The number of these autonomous sources and their rate of change outpaces the speed at which they can be manually classified, meaning that the available data is not being utilized to its full potential. Manually maintaining a wrapper library will not scale to accommodate the growth of genomics data sources on the Web, challenging us to produce an automated system that can find, classify and wrap new sources without constant human intervention. Previous research has not addressed the problem of automatically locating, classifying and integrating classes of bioinformatics data sources.'),
(70878, 2003, 'bio', 'The fiction of function', 'Shrager, Jeff', 'Department of Plant Biology, The Carnegie Instution of Washington, Stanford, CA 94305, USA.', 'United States', 24, 'Databases, Protein|Information Storage and Retrieval|Models, Biological|Proteins|Structure-Activity Relationship|Terminology as Topic', 'Journal Article', '10.1093/bioinformatics/btg277', '14555626', '-'),
(70879, 2003, 'bio', 'Modes and clustering for time-warped gene expression profile data', 'Liu, Xueli|Müller, Hans-Georg', 'Department of Human Genetics, UCLA School of Medicine, Los Angeles, CA 90095, USA.|Department of Human Genetics, UCLA School of Medicine, Los Angeles, CA 90095, USA.', 'United States|United States', 0, 'Adaptation, Physiological|Aging|Algorithms|Animals|Cluster Analysis|Databases as Topic|Drosophila|Gene Expression Profiling|Gene Expression Regulation|Life Cycle Stages|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Time Factors', 'Comparative Study', '10.1093/bioinformatics/btg257', '14555627', 'The study of the dynamics of regulatory processes has led to increased interest for the analysis of temporal gene expression level data. To address the dynamics of regulation, expression data are collected repeatedly over time. It is difficult to statistically represent the resulting high-dimensional data. When regulatory processes determine gene expression, time-warping is likely to be present, i.e. the sample of gene expression trajectories reflects variation not only in terms of the expression amplitudes, but also in terms of the temporal structure of gene expression.'),
(70880, 2003, 'bio', 'Local-pooled-error test for identifying differentially expressed genes with a small number of replicated microarrays', 'Jain, Nitin|Thatte, Jayant|Braciale, Thomas|Ley, Klaus|OConnell, Michael|Lee, Jae K', 'Hospital West Complex, Rm. 3181, P.O. Box 800717, University of Virginia School of Medicine, Charlottesville, VA 22908, USA. nj7w@virginia.edu|Hospital West Complex, Rm. 3181, P.O. Box 800717, University of Virginia School of Medicine, Charlottesville, VA 22908, USA. nj7w@virginia.edu|Hospital West Complex, Rm. 3181, P.O. Box 800717, University of Virginia School of Medicine, Charlottesville, VA 22908, USA. nj7w@virginia.edu|Hospital West Complex, Rm. 3181, P.O. Box 800717, University of Virginia School of Medicine, Charlottesville, VA 22908, USA. nj7w@virginia.edu|Hospital West Complex, Rm. 3181, P.O. Box 800717, University of Virginia School of Medicine, Charlottesville, VA 22908, USA. nj7w@virginia.edu|Hospital West Complex, Rm. 3181, P.O. Box 800717, University of Virginia School of Medicine, Charlottesville, VA 22908, USA. nj7w@virginia.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation|Genetic Variation|Humans|Mice|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sample Size|T-Lymphocytes', 'Comparative Study', '10.1093/bioinformatics/btg264', '14555628', 'In microarray studies gene discovery based on fold-change values is often misleading because error variability for each gene is heterogeneous under different biological conditions and intensity ranges. Several statistical testing methods for differential gene expression have been suggested, but some of these approaches are underpowered and result in high false positive rates because within-gene variance estimates are based on a small number of replicated arrays.'),
(70881, 2003, 'bio', 'Background rareness-based iterative multiple sequence alignment algorithm for regulatory element detection', 'Narasimhan, Chandrasegaran|LoCascio, Philip|Uberbacher, Edward', 'Life Sciences Division, Oak Ridge National Laboratory, PO Box 3480, Oak Ridge, TN 37830, USA.|Life Sciences Division, Oak Ridge National Laboratory, PO Box 3480, Oak Ridge, TN 37830, USA.|Life Sciences Division, Oak Ridge National Laboratory, PO Box 3480, Oak Ridge, TN 37830, USA.', 'United States|United States|United States', 14, 'Algorithms|Amino Acid Motifs|Binding Sites|Gene Expression Profiling|Gene Expression Regulation|Genes, Regulator|Oligonucleotide Array Sequence Analysis|Protein Structure, Tertiary|Reproducibility of Results|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg266', '14555629', 'Experimental methods capable of generating sets of co-regulated genes have become commonplace, however, recognizing the regulatory motifs responsible for this regulation remains difficult. As a result, computational detection of transcription factor binding sites in such data sets has been an active area of research. Most approaches have utilized either Gibbs sampling or greedy strategies to identify such elements in sets of sequences. These existing methods have varying degrees of success depending on the strength and length of the signals and the number of available sequences. We present a new deterministic iterative algorithm for regulatory element detection based on a Markov chain background. As in other methods, sequences in the entire genome and the training set are taken into account in order to discriminate against commonly occurring signals and produce patterns, which are significant in the training set.'),
(70882, 2003, 'bio', 'Sequence alignment kernel for recognition of promoter regions', 'Gordon, Leo|Chervonenkis, Alexey Ya|Gammerman, Alex J|Shahmuradov, Ilham A|Solovyev, Victor V', 'Department of Computer Science, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK. leo@cs.rhul.ac.uk|Department of Computer Science, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK. leo@cs.rhul.ac.uk|Department of Computer Science, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK. leo@cs.rhul.ac.uk|Department of Computer Science, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK. leo@cs.rhul.ac.uk|Department of Computer Science, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK. leo@cs.rhul.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 92, 'Algorithms|Artificial Intelligence|Escherichia coli|Gene Expression Profiling|Pattern Recognition, Automated|Promoter Regions, Genetic|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg265', '14555630', 'In this paper we propose a new method for recognition of prokaryotic promoter regions with startpoints of transcription. The method is based on Sequence Alignment Kernel, a function reflecting the quantitative measure of match between two sequences. This kernel function is further used in Dual SVM, which performs the recognition. Several recognition methods have been trained and tested on positive data set, consisting of 669 sigma70-promoter regions with known transcription startpoints of Escherichia coli and two negative data sets of 709 examples each, taken from coding and non-coding regions of the same genome. The results show that our method performs well and achieves 16.5% average error rate on positive & coding negative data and 18.6% average error rate on positive & non-coding negative data.'),
(70883, 2003, 'bio', 'Recognizing translation initiation sites of eukaryotic genes based on the cooperatively scanning model', 'Wang, Yonghong|Liu, Jinwei|Zhao, Tongju|Ji, Qing', 'Department of Physics, Hebei University of Technology, Tianjin 300130, China. yhwangwz@263.net|Department of Physics, Hebei University of Technology, Tianjin 300130, China. yhwangwz@263.net|Department of Physics, Hebei University of Technology, Tianjin 300130, China. yhwangwz@263.net|Department of Physics, Hebei University of Technology, Tianjin 300130, China. yhwangwz@263.net', 'China|China|China|China', 0, 'Algorithms|Animals|Discriminant Analysis|Eukaryotic Cells|Exons|Gene Expression Profiling|Humans|Pattern Recognition, Automated|Promoter Regions, Genetic|Protein Biosynthesis|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/btg261', '14555631', 'Translation initiation sites (TISs) of genes are the key points of protein synthesis. Exact recognition of TISs in eukaryotic genes is one of the most important tasks in gene-finding algorithms. However, the task has not been satisfactorily fulfilled up to the present. Here, we propose a cooperatively scanning model for recognizing TISs and the first exons of eukaryotic genes on the basis of the structural characteristics of multi-exon genes.'),
(70884, 2003, 'bio', 'Application of support vector machines for T-cell epitopes prediction', 'Zhao, Yingdong|Pinilla, Clemencia|Valmori, Danila|Martin, Roland|Simon, Richard', 'Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.|Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.|Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.|Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.|Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Antigen-Antibody Complex|Artificial Intelligence|Cluster Analysis|Databases, Protein|Epitopes, T-Lymphocyte|Histocompatibility Antigens Class I|Neural Networks (Computer)|Protein Binding|Protein Interaction Mapping|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg255', '14555632', 'The T-cell receptor, a major histocompatibility complex (MHC) molecule, and a bound antigenic peptide, play major roles in the process of antigen-specific T-cell activation. T-cell recognition was long considered exquisitely specific. Recent data also indicate that it is highly flexible, and one receptor may recognize thousands of different peptides. Deciphering the patterns of peptides that elicit a MHC restricted T-cell response is critical for vaccine development.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70885, 2003, 'bio', 'A computational pipeline for protein structure prediction and analysis at genome scale', 'Shah, Manesh|Passovets, Sergei|Kim, Dongsup|Ellrott, Kyle|Wang, Li|Vokler, Inna|LoCascio, Philip|Xu, Dong|Xu, Ying', 'Life Sciences Division, Oak Ridge National Laboratory, TN 37830-6480, USA.|Life Sciences Division, Oak Ridge National Laboratory, TN 37830-6480, USA.|Life Sciences Division, Oak Ridge National Laboratory, TN 37830-6480, USA.|Life Sciences Division, Oak Ridge National Laboratory, TN 37830-6480, USA.|Life Sciences Division, Oak Ridge National Laboratory, TN 37830-6480, USA.|Life Sciences Division, Oak Ridge National Laboratory, TN 37830-6480, USA.|Life Sciences Division, Oak Ridge National Laboratory, TN 37830-6480, USA.|Life Sciences Division, Oak Ridge National Laboratory, TN 37830-6480, USA.|Life Sciences Division, Oak Ridge National Laboratory, TN 37830-6480, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Caenorhabditis elegans Proteins|Computer Simulation|Computing Methodologies|Database Management Systems|Databases, Protein|Genome|Information Storage and Retrieval|Models, Molecular|Molecular Sequence Data|Proteins|Proteome|Pyrococcus furiosus|Sequence Alignment|Sequence Analysis, Protein|Software|Systems Integration|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg262', '14555633', 'Experimental techniques alone cannot keep up with the production rate of protein sequences, while computational techniques for protein structure predictions have matured to such a level to provide reliable structural characterization of proteins at large scale. Integration of multiple computational tools for protein structure prediction can complement experimental techniques.'),
(70886, 2003, 'bio', 'Intersect: identification and visualization of overlaps in database search results', 'Pegg, Scott C-H|Novak, Walter R P|Babbitt, Patricia C', 'Department of Biopharmaceutical Sciences, University of California, San Francisco, San Francisco, CA 94143, USA.|Department of Biopharmaceutical Sciences, University of California, San Francisco, San Francisco, CA 94143, USA.|Department of Biopharmaceutical Sciences, University of California, San Francisco, San Francisco, CA 94143, USA.', 'United States|United States|United States', 0, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Protein|Evolution, Molecular|Genetic Linkage|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg256', '14555634', 'The determination of distant evolutionary relationships remains an important biological problem, and distant homologs often appear in statistically insignificant regions of sequence similarity searches. Intersect is a computer program designed to identify and visualize the overlaps between sets of sequences reported by multiple database searches. This capability extends the usefulness of database search results and aids researchers in identifying the individual sequences that best bridge sequence families and superfamilies.'),
(70887, 2003, 'bio', 'Analysing gene expressions with GRANK', 'de Boer, W P H|Oudejans, J J|Meijer, C J L M|Lankelma, J', 'Department of Medical Oncology, VU Medical Center, PO Box 7057, 1081 Hv Amsterdam, The Netherlands. wph.deboer@vumc.nl|Department of Medical Oncology, VU Medical Center, PO Box 7057, 1081 Hv Amsterdam, The Netherlands. wph.deboer@vumc.nl|Department of Medical Oncology, VU Medical Center, PO Box 7057, 1081 Hv Amsterdam, The Netherlands. wph.deboer@vumc.nl|Department of Medical Oncology, VU Medical Center, PO Box 7057, 1081 Hv Amsterdam, The Netherlands. wph.deboer@vumc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands', 4, 'Algorithms|Cluster Analysis|Database Management Systems|Databases, Protein|Gene Expression Profiling|Humans|Information Storage and Retrieval|Lymphoma, B-Cell|Oligonucleotide Array Sequence Analysis|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btg267', '14555635', 'Unravelling overlapping clusters of functionally linked genes is a major challenge to current clustering programs. Algorithm GRANK permits systematic study of overlap between clusters of genes of a similar expression profile and large variation across a series of microarrays.'),
(70888, 2003, 'bio', 'GCHap: fast MLEs for haplotype frequencies by gene counting', 'Thomas, Alun', 'Department of Medical Informatics and Center for High Performance Computing, University of Utah, 391 Chipeta Way Suite D, Salt Lake City, UT 84108, USA. alun@genepi.med.utah.edu', 'United States', 0, 'Algorithms|Gene Expression Profiling|Gene Frequency|Genetic Linkage|Haplotypes|Hypermedia|Likelihood Functions|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btg254', '14555636', 'GCHap quickly finds maximum likelihood estimates (MLEs) of frequencies of haplotypes given genotype information on a random sample of individuals. It uses the gene counting method but by excluding haplotypes with zero MLE at an early stage, this implementation uses many orders of magnitude less space and time than naive implementations. A second program, ApproxGCHap, is provided to give alternate estimates for data sets with large numbers of loci or large amounts of missing genotypes.'),
(70889, 2003, 'bio', 'Codon adaptation index as a measure of dominating codon bias', 'Carbone, A|Zinovyev, A|Képès, F', 'Institut des Hautes Etudes Scientifiques, 35, route de Chartres, 91440 Bures-sur-Yvette, France. carbone@ihes.fr|Institut des Hautes Etudes Scientifiques, 35, route de Chartres, 91440 Bures-sur-Yvette, France. carbone@ihes.fr|Institut des Hautes Etudes Scientifiques, 35, route de Chartres, 91440 Bures-sur-Yvette, France. carbone@ihes.fr', 'France|France|France', 197, 'Adaptation, Physiological|Algorithms|Animals|Bacteria|Base Sequence|Caenorhabditis elegans|Codon|Drosophila melanogaster|Gene Expression Profiling|Gene Frequency|Genetic Variation|Genome|Models, Genetic|Models, Statistical|Reproducibility of Results|Saccharomyces cerevisiae|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg272', '14594704', 'We propose a simple algorithm to detect dominating synonymous codon usage bias in genomes. The algorithm is based on a precise mathematical formulation of the problem that lead us to use the Codon Adaptation Index (CAI) as a universal measure of codon bias. This measure has been previously employed in the specific context of translational bias. With the set of coding sequences as a sole source of biological information, the algorithm provides a reference set of genes which is highly representative of the bias. This set can be used to compute the CAI of genes of prokaryotic and eukaryotic organisms, including those whose functional annotation is not yet available. An important application concerns the detection of a reference set characterizing translational bias which is known to correlate to expression levels, in this case, the algorithm becomes a key tool to predict gene expression levels, to guide regulatory circuit reconstruction, and to compare species. The algorithm detects also leading-lagging strands bias, GC-content bias, GC3 bias, and horizontal gene transfer. The approach is validated on 12 slow-growing and fast-growing bacteria, Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster.'),
(70890, 2003, 'bio', 'Applying signal theory to the analysis of biomolecules', 'Kauer, Gerhard|Blöcker, Helmut', 'Department of Genome Analysis, GBF-German Research Centre for Biotechnology, Mascheroder Weg 1, D-38124 Braunschweig, Germany. GerhardKauer@t-online.de|Department of Genome Analysis, GBF-German Research Centre for Biotechnology, Mascheroder Weg 1, D-38124 Braunschweig, Germany. GerhardKauer@t-online.de', 'Germany|Germany', 23, 'Algorithms|Amino Acid Motifs|Biopolymers|Computational Biology|Feasibility Studies|Fourier Analysis|Heat-Shock Proteins|Models, Biological|Models, Chemical|Sequence Analysis, Protein|Signal Processing, Computer-Assisted|Structure-Activity Relationship|Systems Theory', 'Evaluation Studies', '10.1093/bioinformatics/btg273', '14594705', 'The accumulation of sequence-related and other biological data for basic research and application purposes invites disaster. It appears very likely that neither traditional thinking nor current technologies (including their foreseeable evolutionary developments) will be able to cope with this ever intensifying situation.'),
(70891, 2003, 'bio', 'Development of an integrated laboratory information management system for the maize mapping project', 'Sanchez-Villeda, H|Schroeder, S|Polacco, M|McMullen, M|Havermann, S|Davis, G|Vroh-Bi, I|Cone, K|Sharopova, N|Yim, Y|Schultz, L|Duru, N|Musket, T|Houchins, K|Fang, Z|Gardiner, J|Coe, E', 'Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, USA.|Department of Agronomy, Division of Biological Sciences and USDA-ARS, University of Missouri, Columbia, MO 65211, 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|United States|United States|United States|United States|United States', 29, 'Chromosome Mapping|Database Management Systems|Databases, Genetic|Documentation|Gene Expression Profiling|Genome, Plant|Information Dissemination|Information Storage and Retrieval|Internet|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Systems Integration|User-Computer Interface|Zea mays', 'Journal Article', '10.1093/bioinformatics/btg274', '14594706', 'The development of an integrated genetic and physical map for the maize genome involves the generation of an enormous amount of data. Managing this data requires a system to aid in genotype scoring for different types of markers coming from both local and remote users. In addition, researchers need an efficient way to interact with genetic mapping software and with data files from automated DNA sequencing. They also need ways to manage primer data for mapping and sequencing and provide views of the integrated physical and genetic map and views of genetic map comparisons.'),
(70892, 2003, 'bio', 'A novel strategy for microarray quality control using Bayesian networks', 'Hautaniemi, Sampsa|Edgren, Henrik|Vesanen, Petri|Wolf, Maija|Järvinen, Anna-Kaarina|Yli-Harja, Olli|Astola, Jaakko|Kallioniemi, Olli|Monni, Outi', 'Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland. sampsa.hautaniemi@tut.fi|Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland. sampsa.hautaniemi@tut.fi|Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland. sampsa.hautaniemi@tut.fi|Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland. sampsa.hautaniemi@tut.fi|Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland. sampsa.hautaniemi@tut.fi|Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland. sampsa.hautaniemi@tut.fi|Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland. sampsa.hautaniemi@tut.fi|Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland. sampsa.hautaniemi@tut.fi|Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland. sampsa.hautaniemi@tut.fi', 'Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland', 41, 'Algorithms|Base Sequence|Bayes Theorem|Computer Simulation|Gene Expression Profiling|Models, Genetic|Models, Statistical|Molecular Sequence Data|Normal Distribution|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg275', '14594707', 'High-throughput microarray technologies enable measurements of the expression levels of thousands of genes in parallel. However, microarray printing, hybridization and washing may create substantial variability in the quality of the data. As erroneous measurements may have a drastic impact on the results by disturbing the normalization schemes and by introducing expression patterns that lead to incorrect conclusions, it is crucial to discard low quality observations in the early phases of a microarray experiment. A typical microarray experiment consists of tens of thousands of spots on a microarray, making manual extraction of poor quality spots impossible. Thus, there is a need for a reliable and general microarray spot quality control strategy.'),
(70893, 2003, 'bio', 'Inferring protein interactions from phylogenetic distance matrices', 'Gertz, Jason|Elfond, Georgiy|Shustrova, Anna|Weisinger, Matt|Pellegrini, Matteo|Cokus, Shawn|Rothschild, Bruce', 'Department of Mathematics, 310 Malott Hall, Cornell University, Ithaca, NY 14853-4201, USA.|Department of Mathematics, 310 Malott Hall, Cornell University, Ithaca, NY 14853-4201, USA.|Department of Mathematics, 310 Malott Hall, Cornell University, Ithaca, NY 14853-4201, USA.|Department of Mathematics, 310 Malott Hall, Cornell University, Ithaca, NY 14853-4201, USA.|Department of Mathematics, 310 Malott Hall, Cornell University, Ithaca, NY 14853-4201, USA.|Department of Mathematics, 310 Malott Hall, Cornell University, Ithaca, NY 14853-4201, USA.|Department of Mathematics, 310 Malott Hall, Cornell University, Ithaca, NY 14853-4201, USA.', 'United States|United States|United States|United States|United States|United States|United States', 52, 'Algorithms|Amino Acid Sequence|Binding Sites|Chemokines|Chromosome Mapping|Cluster Analysis|Conserved Sequence|Gene Expression Profiling|Molecular Sequence Data|Monte Carlo Method|Phylogeny|Protein Binding|Protein Interaction Mapping|Proteins|Receptors, Chemokine|Receptors, Transforming Growth Factor beta|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Transforming Growth Factor beta', 'Comparative Study', '10.1093/bioinformatics/btg278', '14594708', 'Finding the interacting pairs of proteins between two different protein families whose members are known to interact is an important problem in molecular biology. We developed and tested an algorithm that finds optimal matches between two families of proteins by comparing their distance matrices. A distance matrix provides a measure of the sequence similarity of proteins within a family. Since the protein sets of interest may have dozens of proteins each, the use of an efficient approximate solution is necessary. Therefore the approach we have developed consists of a Metropolis Monte Carlo optimization algorithm which explores the search space of possible matches between two distance matrices. We demonstrate that by using this algorithm we are able to accurately match chemokines and chemokine-receptors as well as the tgfbeta family of ligands and their receptors.'),
(70894, 2003, 'bio', 'Extraction of protein interaction information from unstructured text using a context-free grammar', 'Temkin, Joshua M|Gilder, Mark R', 'GE Global Research, 1 Research Circle, Niskayuna, NY 12309, USA.|GE Global Research, 1 Research Circle, Niskayuna, NY 12309, USA.', 'United States|United States', 133, 'Algorithms|Database Management Systems|Databases, Protein|Dictionaries as Topic|Information Storage and Retrieval|Natural Language Processing|Protein Binding|Protein Interaction Mapping|Proteins|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/btg279', '14594709', 'As research into disease pathology and cellular function continues to generate vast amounts of data pertaining to protein, gene and small molecule (PGSM) interactions, there exists a critical need to capture these results in structured formats allowing for computational analysis. Although many efforts have been made to create databases that store this information in computer readable form, populating these sources largely requires a manual process of interpreting and extracting interaction relationships from the biological research literature. Being able to efficiently and accurately automate the extraction of interactions from unstructured text, would greatly improve the content of these databases and provide a method for managing the continued growth of new literature being published.'),
(70895, 2003, 'bio', 'Protein structural class identification directly from NMR spectra using averaged chemical shifts', 'Mielke, S P|Krishnan, V V', 'Biophysics Graduate Group, University of California, Davis, CA 95616, USA.|Biophysics Graduate Group, University of California, Davis, CA 95616, USA.', 'United States|United States', 28, 'Algorithms|Amino Acid Sequence|Crystallography|Databases, Protein|Magnetic Resonance Spectroscopy|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg280', '14594710', 'Knowledge of the three-dimensional structure of proteins is integral to understanding their functions, and a necessity in the era of proteomics. A wide range of computational methods is employed to estimate the secondary, tertiary, and quaternary structures of proteins. Comprehensive experimental methods, on the other hand, are limited to nuclear magnetic resonance (NMR) and X-ray crystallography. The full characterization of individual structures, using either of these techniques, is extremely time intensive. The demands of high throughput proteomics necessitate the development of new, faster experimental methods for providing structural information. As a first step toward such a method, we explore the possibility of determining the structural classes of proteins directly from their NMR spectra, prior to resonance assignment, using averaged chemical shifts. This is achieved by correlating NMR-based information with empirical structure-based information available in widely used electronic databases. The results are analyzed statistically for their significance. The robustness of the method as a structure predictor is probed by applying it to a set of proteins of unknown structure. Our results show that this NMR-based method can be used as a low-resolution tool for protein structural class identification.'),
(70896, 2003, 'bio', 'Venn Mapping: clustering of heterologous microarray data based on the number of co-occurring differentially expressed genes', 'Smid, Marcel|Dorssers, Lambert C J|Jenster, Guido', 'Department of Pathology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands.|Department of Pathology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands.|Department of Pathology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 61, 'Algorithms|Base Sequence|Breast Neoplasms|Chromosome Mapping|Cluster Analysis|Female|Gene Expression Profiling|Humans|Male|Models, Genetic|Models, Statistical|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Prostatic Neoplasms|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg282', '14594711', 'To evaluate microarray data, clustering is widely used to group biological samples or genes. However, problems arise when comparing heterologous databases. As the clustering algorithm searches for similarities between experiments, it will most likely first separate the data sets, masking relationships that exist between samples from different databases.'),
(70897, 2003, 'bio', 'Linear regression and two-class classification with gene expression data', 'Huang, Xiaohong|Pan, Wei', 'Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building (MMC 303), Minneapolis, MN 55455-0378, USA.|Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building (MMC 303), Minneapolis, MN 55455-0378, USA.', 'United States|United States', 84, 'Algorithms|Cluster Analysis|Colonic Neoplasms|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Leukemia|Linear Models|Models, Genetic|Models, Statistical|Neoplasms|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg283', '14594712', 'Using gene expression data to classify (or predict) tumor types has received much research attention recently. Due to some special features of gene expression data, several new methods have been proposed, including the weighted voting scheme of Golub et al., the compound covariate method of Hedenfalk et al. (originally proposed by Tukey), and the shrunken centroids method of Tibshirani et al. These methods look different and are more or less ad hoc.'),
(70898, 2003, 'bio', 'Markovian negentropies in bioinformatics 1 A picture of footprints after the interaction of the HIV-1 Psi-RNA packaging region with drugs', 'Díaz, Humberto González|de Armas, Ronal Ramos|Molina, Reinaldo', 'Chemical Bioactives Center, Central University of Las Villas 54830, Cuba. humbertogd@vodafone.es|Chemical Bioactives Center, Central University of Las Villas 54830, Cuba. humbertogd@vodafone.es|Chemical Bioactives Center, Central University of Las Villas 54830, Cuba. humbertogd@vodafone.es', 'Cuba|Cuba|Cuba', 73, 'Binding Sites|Computational Biology|Computer Simulation|DNA Footprinting|Drug Design|Entropy|HIV-1|Humans|Macromolecular Substances|Markov Chains|Models, Chemical|Models, Molecular|Models, Statistical|Paromomycin|Pharmaceutical Preparations|RNA, Viral|Sequence Analysis, RNA', 'Comparative Study', '10.1093/bioinformatics/btg285', '14594713', 'Many experts worldwide have highlighted the potential of RNA molecules as drug targets for the chemotherapeutic treatment of a range of diseases. In particular, the molecular pockets of RNA in the HIV-1 packaging region have been postulated as promising sites for antiviral action. The discovery of simpler methods to accurately represent drug-RNA interactions could therefore become an interesting and rapid way to generate models that are complementary to docking-based systems.'),
(70899, 2003, 'bio', 'A Bayesian missing value estimation method for gene expression profile data', 'Oba, Shigeyuki|Sato, Masa-aki|Takemasa, Ichiro|Monden, Morito|Matsubara, Ken-ichi|Ishii, Shin', 'Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma 630-0192, Japan.|Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma 630-0192, Japan.|Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma 630-0192, Japan.|Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma 630-0192, Japan.|Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma 630-0192, Japan.|Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma 630-0192, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 428, 'Algorithms|Artifacts|Bayes Theorem|Cell Cycle|Colorectal Neoplasms|Gene Expression Profiling|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Yeasts', 'Comparative Study', '10.1093/bioinformatics/btg287', '14594714', 'Gene expression profile analyses have been used in numerous studies covering a broad range of areas in biology. When unreliable measurements are excluded, missing values are introduced in gene expression profiles. Although existing multivariate analysis methods have difficulty with the treatment of missing values, this problem has received little attention. There are many options for dealing with missing values, each of which reaches drastically different results. Ignoring missing values is the simplest method and is frequently applied. This approach, however, has its flaws. In this article, we propose an estimation method for missing values, which is based on Bayesian principal component analysis (BPCA). Although the methodology that a probabilistic model and latent variables are estimated simultaneously within the framework of Bayes inference is not new in principle, actual BPCA implementation that makes it possible to estimate arbitrary missing variables is new in terms of statistical methodology.'),
(70900, 2003, 'bio', 'Kernel hierarchical gene clustering from microarray expression data', 'Qin, Jie|Lewis, Darrin P|Noble, William Stafford', 'Columbia Genome Center, Columbia University, 1150 St. Nicholas Avenue, New York, NY 10032, USA. jq22@columbia.edu|Columbia Genome Center, Columbia University, 1150 St. Nicholas Avenue, New York, NY 10032, USA. jq22@columbia.edu|Columbia Genome Center, Columbia University, 1150 St. Nicholas Avenue, New York, NY 10032, USA. jq22@columbia.edu', 'United States|United States|United States', 54, 'Algorithms|Animals|Artificial Intelligence|Cell Cycle|Cluster Analysis|Gene Expression Profiling|Humans|Mice|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Yeasts', 'Comparative Study', '10.1093/bioinformatics/btg288', '14594715', 'Unsupervised analysis of microarray gene expression data attempts to find biologically significant patterns within a given collection of expression measurements. For example, hierarchical clustering can be applied to expression profiles of genes across multiple experiments, identifying groups of genes that share similar expression profiles. Previous work using the support vector machine supervised learning algorithm with microarray data suggests that higher-order features, such as pairwise and tertiary correlations across multiple experiments, may provide significant benefit in learning to recognize classes of co-expressed genes.'),
(70901, 2003, 'bio', 'iMap: a database-driven utility to integrate and access the genetic and physical maps of maize', 'Fang, Z|Cone, K|Sanchez-Villeda, H|Polacco, M|McMullen, M|Schroeder, S|Gardiner, J|Davis, G|Havermann, S|Yim, Y|Vroh Bi, I|Coe, E', 'Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu|Department of Agronomy, University of Missouri, Columbia, MO 65211, USA. fangz@missouri.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 12, 'Chromosome Mapping|Database Management Systems|Databases, Genetic|Documentation|Gene Expression Profiling|Genome, Plant|Information Dissemination|Information Storage and Retrieval|Internet|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Systems Integration|User-Computer Interface|Zea mays', 'Journal Article', '10.1093/bioinformatics/btg289', '14594716', 'Because of the unique biological features, a bioinformatic platform for the integrated genetic and physical map of maize is required for storing, integrating, accessing and visualizing the underlying data.'),
(70902, 2003, 'bio', 'Inhomogeneous molecular density: reference packing densities and distribution of cavities within proteins', 'Rother, Kristian|Preissner, Robert|Goede, Andrean|Frömmel, Cornelius', 'Berlin Center of Genome Based Bioinformatics (BCB), Humboldt University, Institute of Biochemistry at the Charite, Monbijoustr. 2, 10117 Berlin, Germany.|Berlin Center of Genome Based Bioinformatics (BCB), Humboldt University, Institute of Biochemistry at the Charite, Monbijoustr. 2, 10117 Berlin, Germany.|Berlin Center of Genome Based Bioinformatics (BCB), Humboldt University, Institute of Biochemistry at the Charite, Monbijoustr. 2, 10117 Berlin, Germany.|Berlin Center of Genome Based Bioinformatics (BCB), Humboldt University, Institute of Biochemistry at the Charite, Monbijoustr. 2, 10117 Berlin, Germany.', 'Germany|Germany|Germany|Germany', 32, 'Amino Acid Sequence|Anisotropy|Binding Sites|Cell Surface Extensions|Databases, Protein|Energy Transfer|Models, Molecular|Protein Conformation|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins', 'Comparative Study', '10.1093/bioinformatics/btg292', '14594717', 'There is no consensus in the literature about how the deepest portions of protein structures are packed. Using an improved Voronoi procedure, we calculate reference packing densities for different regions in the protein interior. Furthermore, we want to clarify where cavities are located.'),
(70903, 2003, 'bio', 'A new sequence distance measure for phylogenetic tree construction', 'Otu, Hasan H|Sayood, Khalid', 'Department of Electrical Engineering, University of Nebraska-Lincoln, 209N WSEC, Lincoln, NE 68503, USA. hotu@bidmc.harvard.edu|Department of Electrical Engineering, University of Nebraska-Lincoln, 209N WSEC, Lincoln, NE 68503, USA. hotu@bidmc.harvard.edu', 'United States|United States', 262, 'Algorithms|Animals|Chromosome Mapping|Evolution, Molecular|Gene Expression Profiling|Humans|Mitochondria|Phylogeny|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Species Specificity', 'Comparative Study', '10.1093/bioinformatics/btg295', '14594718', 'Most existing approaches for phylogenetic inference use multiple alignment of sequences and assume some sort of an evolutionary model. The multiple alignment strategy does not work for all types of data, e.g. whole genome phylogeny, and the evolutionary models may not always be correct. We propose a new sequence distance measure based on the relative information between the sequences using Lempel-Ziv complexity. The distance matrix thus obtained can be used to construct phylogenetic trees.'),
(70904, 2003, 'bio', 'An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data', 'Hsu, Arthur L|Tang, Sen-Lin|Halgamuge, Saman K', 'Mechatronics Research Group, Department of Mechanical and Manufacturing Engineering, University of Melbourne, Victoria, Australia 3010. alhs@mame.mu.oz.au|Mechatronics Research Group, Department of Mechanical and Manufacturing Engineering, University of Melbourne, Victoria, Australia 3010. alhs@mame.mu.oz.au|Mechatronics Research Group, Department of Mechanical and Manufacturing Engineering, University of Melbourne, Victoria, Australia 3010. alhs@mame.mu.oz.au', 'Australia|Australia|Australia', 60, 'Algorithms|Biomarkers, Tumor|Cluster Analysis|Colonic Neoplasms|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Markers|Genetic Testing|Humans|Leukemia|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg296', '14594719', 'Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches.'),
(70905, 2003, 'bio', 'SNP cherry picker: maximizing the chance of finding an association with a disease SNP', 'Harris, Mark|Martin, Jeremy M R|Peden, John F|Rawlings, Christopher J', 'Oxagen Ltd, 91 Milton Park, Abingdon, Oxon OX14 4RY, UK. SD@oxagen.co.uk|Oxagen Ltd, 91 Milton Park, Abingdon, Oxon OX14 4RY, UK. SD@oxagen.co.uk|Oxagen Ltd, 91 Milton Park, Abingdon, Oxon OX14 4RY, UK. SD@oxagen.co.uk|Oxagen Ltd, 91 Milton Park, Abingdon, Oxon OX14 4RY, UK. SD@oxagen.co.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 3, 'Algorithms|Base Sequence|Gene Expression Profiling|Gene Frequency|Genetic Diseases, Inborn|Genetic Predisposition to Disease|Genetic Testing|Humans|Molecular Sequence Data|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btg258', '14594720', 'The high cost of genotyping single nucleotide polymorphisms (SNPs) generally prohibits the systematic mapping of entire genetic linkage regions in order to find the polymorphisms associated with increased risk of disease. In practice, SNPs are selected at approximately equal spacing across the linkage region to try to locate a SNP lying in the haplotype block of the disease SNP. The size of the haplotype block may not be known, however, and SNPs taken from public domain sources may not in fact be polymorphic. Our program will choose a subset of the SNPs in a linkage region so as to maximize the expected proportion of the sequence that lies within a given distance of a real SNP.'),
(70906, 2003, 'bio', 'MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis', 'Lee, Dong-Yup|Yun, Hongsoek|Park, Sunwon|Lee, Sang Yup', 'Metabolic and Biomolecular Engineering National Research Laboratory, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea.|Metabolic and Biomolecular Engineering National Research Laboratory, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea.|Metabolic and Biomolecular Engineering National Research Laboratory, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea.|Metabolic and Biomolecular Engineering National Research Laboratory, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea.', '-|-|-|-', 98, 'Database Management Systems|Information Storage and Retrieval|Metabolism|Models, Biological|Proteome|Proteomics|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg271', '14594721', 'MetaFluxNet is a program package for managing information on the metabolic reaction network and for quantitatively analyzing metabolic fluxes in an interactive and customized way. It allows users to interpret and examine metabolic behavior in response to genetic and/or environmental modifications. As a result, quantitative in silico simulations of metabolic pathways can be carried out to understand the metabolic status and to design the metabolic engineering strategies. The main features of the program include a well-developed model construction environment, user-friendly interface for metabolic flux analysis (MFA), comparative MFA of strains having different genotypes under various environmental conditions, and automated pathway layout creation.'),
(70907, 2003, 'bio', 'LDA--a java-based linkage disequilibrium analyzer', 'Ding, Keyue|Zhou, Kaixin|He, Fuchu|Shen, Yan', 'Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences (and Peking Union Medical College, National Laboratory of Medical Molecular Biology, Beijing, 100005, Peoples Republic of China.|Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences (and Peking Union Medical College, National Laboratory of Medical Molecular Biology, Beijing, 100005, Peoples Republic of China.|Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences (and Peking Union Medical College, National Laboratory of Medical Molecular Biology, Beijing, 100005, Peoples Republic of China.|Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences (and Peking Union Medical College, National Laboratory of Medical Molecular Biology, Beijing, 100005, Peoples Republic of China.', 'China|China|China|China', 115, 'Algorithms|Database Management Systems|Gene Expression Profiling|Gene Frequency|Hypermedia|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Sequence Alignment|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg276', '14594722', 'We describe an integrated java-based program that provides elaborate graphic and plain-text output of pairwise linkage disequilibrium (LD) analysis of single nucleotide polymorphisms genotypic data. It is most suitable for molecular geneticists, who are focusing on LD measures estimation, statistical significance test and extent prediction.'),
(70908, 2003, 'bio', 'The UAB Proteomics Database', 'Hill, Aubrey|Kim, Helen', 'UAB Comprehensive Cancer Center, UAB Mass Spectrometry and Proteomics Shared Facility, University of Alabama at Birmingham, 1530 3rd Ave South, Kaul 602A, Birmingham, AL 35294, USA. ahill@uab.edu|UAB Comprehensive Cancer Center, UAB Mass Spectrometry and Proteomics Shared Facility, University of Alabama at Birmingham, 1530 3rd Ave South, Kaul 602A, Birmingham, AL 35294, USA. ahill@uab.edu', 'United States|United States', 14, 'Alabama|Database Management Systems|Databases, Protein|Electrophoresis, Gel, Two-Dimensional|Hypermedia|Information Storage and Retrieval|Mass Spectrometry|Protein Array Analysis|Proteome|Proteomics|Universities|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg281', '14594723', 'The University of Alabama at Birmingham (UAB) Proteomics Database (UPD) (http://www.uab.edu/proteinmenu) was created to provide a repository for the storage and linkage of two-dimensional (2D) gel images and the associated information obtained through mass spectrometry analysis of the proteins excised from the 2D gels in a manner similar to the SWISS-2DPAGE database and the Stanford Microarray Database. This was accomplished through the development of a web interface, a relational database, image maps and hyperlinks stored in the database. In addition to the internally generated data, UPD provides links to the National Center for Biotechnology Information via accession number hyperlinks. UPD currently contains information on 44 individual proteins derived from four experiments conducted by four UAB faculty members. Images of the gels from which each of these proteins was isolated are accessed by hyperlinks embedded in the database.'),
(70909, 2003, 'bio', 'RED-T: utilizing the Ratios of Evolutionary Distances for determination of alternative phylogenetic events', 'Farahi, Kamyar|Whitman, William B|Kraemer, Eileen T', 'Department of Microbiology and Computer Science Department, The University of Georgia, Athens, GA 30602, USA.|Department of Microbiology and Computer Science Department, The University of Georgia, Athens, GA 30602, USA.|Department of Microbiology and Computer Science Department, The University of Georgia, Athens, GA 30602, USA.', 'Georgia|Georgia|Georgia', 0, 'Biological Evolution|Chromosome Mapping|Evolution, Molecular|Gene Expression Profiling|Genetic Linkage|Hypermedia|Internet|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg284', '14594724', 'RED-T is a Java application for phylogenetic analysis based on a unique method, RED, that utilizes the ratios of evolutionary distances E(d) to distinguish between alternative evolutionary histories. RED-T allows the user to examine if any given experimental gene shares the same evolutionary history as the designated control gene(s). Moreover, the tool detects any differences in evolutionary history and allows the user to examine comparisons of E(d) for a likely explanation. Lateral gene transfer, which may have a significant influence in organismal evolution is one mechanism that could explain the findings of these RED-T analyses.'),
(70910, 2003, 'bio', 'Pathway studio--the analysis and navigation of molecular networks', 'Nikitin, Alexander|Egorov, Sergei|Daraselia, Nikolai|Mazo, Ilya', 'Ariadne Genomics, Inc., 9700 Great Seneca Hgwy, Rockville, MD 20850, USA.|Ariadne Genomics, Inc., 9700 Great Seneca Hgwy, Rockville, MD 20850, USA.|Ariadne Genomics, Inc., 9700 Great Seneca Hgwy, Rockville, MD 20850, USA.|Ariadne Genomics, Inc., 9700 Great Seneca Hgwy, Rockville, MD 20850, USA.', 'United States|United States|United States|United States', 0, 'Database Management Systems|Databases, Protein|Gene Expression Regulation|Information Storage and Retrieval|Metabolism|Models, Biological|Protein Interaction Mapping|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg290', '14594725', 'PathwayAssist is a software application developed for navigation and analysis of biological pathways, gene regulation networks and protein interaction maps. It comes with the built-in natural language processing module MedScan and the comprehensive database describing more than 100 000 events of regulation, interaction and modification between proteins, cell processes and small molecules.'),
(70911, 2003, 'bio', 'GARBAN: genomic analysis and rapid biological annotation of cDNA microarray and proteomic data', 'Martínez-Cruz, Luis A|Rubio, Angel|Martínez-Chantar, María L|Labarga, Alberto|Barrio, Isabel|Podhorski, Adam|Segura, Victor|Sevilla Campo, José L|Avila, Matías A|Mato, Jose M', 'Department of Internal Medicine, Unit of Proteomics, Genomics and Bioinformatics, University of Navarra, Pamplona-31008, Spain.|Department of Internal Medicine, Unit of Proteomics, Genomics and Bioinformatics, University of Navarra, Pamplona-31008, Spain.|Department of Internal Medicine, Unit of Proteomics, Genomics and Bioinformatics, University of Navarra, Pamplona-31008, Spain.|Department of Internal Medicine, Unit of Proteomics, Genomics and Bioinformatics, University of Navarra, Pamplona-31008, Spain.|Department of Internal Medicine, Unit of Proteomics, Genomics and Bioinformatics, University of Navarra, Pamplona-31008, Spain.|Department of Internal Medicine, Unit of Proteomics, Genomics and Bioinformatics, University of Navarra, Pamplona-31008, Spain.|Department of Internal Medicine, Unit of Proteomics, Genomics and Bioinformatics, University of Navarra, Pamplona-31008, Spain.|Department of Internal Medicine, Unit of Proteomics, Genomics and Bioinformatics, University of Navarra, Pamplona-31008, Spain.|Department of Internal Medicine, Unit of Proteomics, Genomics and Bioinformatics, University of Navarra, Pamplona-31008, Spain.|Department of Internal Medicine, Unit of Proteomics, Genomics and Bioinformatics, University of Navarra, Pamplona-31008, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 21, 'Algorithms|Database Management Systems|Databases, Nucleic Acid|Databases, Protein|Documentation|Gene Expression Profiling|Genomics|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Proteomics|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg291', '14594726', 'Genomic Analysis and Rapid Biological ANnotation (GARBAN) is a new tool that provides an integrated framework to analyze simultaneously and compare multiple data sets derived from microarray or proteomic experiments. It carries out automated classifications of genes or proteins according to the criteria of the Gene Ontology Consortium at a level of depth defined by the user. Additionally, it performs clustering analysis of all sets based on functional categories or on differential expression levels. GARBAN also provides graphical representations of the biological pathways in which all the genes/proteins participate.'),
(70912, 2003, 'bio', 'RankViaContact: ranking and visualization of amino acid contacts', 'Shen, Bairong|Vihinen, Mauno', 'Institute of Medical Technology, University of Tampere, FIN-33014 and Research Unit, Tampere University Hospital, FIN-33520 Tampere, Finland.|Institute of Medical Technology, University of Tampere, FIN-33014 and Research Unit, Tampere University Hospital, FIN-33520 Tampere, Finland.', 'Finland|Finland', 0, 'Amino Acids|Binding Sites|Computer Simulation|Internet|Macromolecular Substances|Models, Chemical|Models, Molecular|Protein Binding|Protein Conformation|Proteins|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg293', '14594727', 'RankViaContact is a web service for calculation of residue-residue contact energies in proteins based on a coarse-grained model, and for visualization of interactions. The service provides information about ranked contact energies of residues, coordination numbers and the relative solvent accessibility of selected residues, as well as sequence and structure information. The program can be used to design stabilizing mutations, to analyze residue-residue contacts and to study the consequences of mutations.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70913, 2003, 'bio', 'Electrophoretic data classification for phylogenetics and biostatistics', 'Cardinali, Gianluigi|Maraziti, Francesco|Selvi, Sabrina', 'Dipartimento di Biologia Vegetale e Biotecnologie Agroambientali, Sect. Microbiologia Agroalimentare ed Ambientale, Borgo 20 Giugno 74, I-06121 Perugia, Italy. gianlu@unipg.it|Dipartimento di Biologia Vegetale e Biotecnologie Agroambientali, Sect. Microbiologia Agroalimentare ed Ambientale, Borgo 20 Giugno 74, I-06121 Perugia, Italy. gianlu@unipg.it|Dipartimento di Biologia Vegetale e Biotecnologie Agroambientali, Sect. Microbiologia Agroalimentare ed Ambientale, Borgo 20 Giugno 74, I-06121 Perugia, Italy. gianlu@unipg.it', 'Italy|Italy|Italy', 7, 'Algorithms|Biopolymers|Cluster Analysis|Combinatorial Chemistry Techniques|Data Interpretation, Statistical|Electrophoresis|Molecular Weight|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btg294', '14594728', 'This paper presents ClassMaker, a macro of MS Excel able to classify continuous data of molecular weight data as binary (1/0) values. The output is represented by a binary matrix, which can be introduced in every software application for phylogenetics or multivariate statistics. This application is designed in order to be a link between image analysis programs and statistical or phylogenetic applications, in order to produce a complete series of free programs able to carry out the complete analysis from the gel to the dendrogram.'),
(70914, 2003, 'bio', 'Silent DNA: speaking RNA language?', 'Vinogradov, Alexander E', 'Institute of Cytology, Russian Academy of Sciences, Tikhoretsky Ave. 4, St Petersburg 194064, Russia. aevin@mail.cytspb.rssi.ru', '-', 4, 'Animals|Base Composition|Base Sequence|Codon|DNA|Evolution, Molecular|GC Rich Sequence|Gene Silencing|Genome, Human|Humans|Introns|Molecular Sequence Data|Mutation, Missense|Nucleic Acid Conformation|Nucleic Acid Denaturation|RNA|Sequence Analysis, DNA|Sequence Analysis, RNA|Species Specificity|Structure-Activity Relationship|Temperature', 'Comparative Study', '10.1093/bioinformatics/btg320', '14630644', 'The sequence of silent DNA in the human genome (intergenic spacers, introns and synonymous codon positions of protein-coding genes) was found here to have the higher thermostability of corresponding RNA/RNA and RNA/DNA duplexes as compared with randomized sequence. This difference increased with elevation of GC content. The revealed effect was not due to correlation of RNA/RNA and RNA/DNA thermostabilities with thermostability of the DNA/DNA duplex, which, on the contrary, was lower than in the randomized sequence and lagged behind the elevation of GC content. The same picture was observed in the genomes of other warm-blooded vertebrates but not in the lower organisms. This finding suggests that RNA-RNA and RNA-DNA interactions could be involved in the putative function of silent DNA.'),
(70915, 2003, 'bio', 'Disease-associated variants in PYPAF1 and NOD2 result in similar alterations of conserved sequence', 'Albrecht, Mario|Lengauer, Thomas|Schreiber, Stefan', 'Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. maario.albrecht@mpi-sb.mpg.de|Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. maario.albrecht@mpi-sb.mpg.de|Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. maario.albrecht@mpi-sb.mpg.de', 'Germany|Germany|Germany', 21, 'Animals|Autoimmune Diseases|Carrier Proteins|Cattle|Conserved Sequence|Gene Expression Profiling|Genetic Markers|Genetic Predisposition to Disease|Genetic Variation|Humans|Inflammation|Intracellular Signaling Peptides and Proteins|Mutation, Missense|NLR Family, Pyrin Domain-Containing 3 Protein|Nod2 Signaling Adaptor Protein|Sequence Alignment|Sequence Analysis, Protein|Species Specificity|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg370', '14630645', 'Sequence variations in the gene products PYPAF1/CIAS1 and NOD2/CARD15 have been associated with several autoinflammatory diseases that, although clinically different, share a similar inflammatory pathophysiology. A multiple sequence alignment of homologous proteins demonstrates that some of the missense variants are located in highly conserved regions of the NTPase domain and possibly impair NTP-hydrolysis. Intriguingly, one of the variations, which is found identically in PYPAF1 and NOD2, is located at the same alignment position. Our findings suggest that evolutionary gene duplication can give rise to disease families because variants affect conserved sequence in a similar fashion.'),
(70916, 2003, 'bio', 'Early bioinformatics: the birth of a discipline--a personal view', 'Ouzounis, Christos A|Valencia, Alfonso', 'Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK. ouzounis@ebi.ac.uk|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK. ouzounis@ebi.ac.uk', 'United Kingdom|United Kingdom', 71, 'Algorithms|Animals|Computational Biology|Databases, Genetic|Evolution, Molecular|Gene Expression Profiling|History, 20th Century|History, 21st Century|Humans|Sequence Analysis', 'Historical Article', '10.1093/bioinformatics/btg309', '14630646', 'The field of bioinformatics has experienced an explosive growth in the last decade, yet this new field has a long history. Some historical perspectives have been previously provided by the founders of this field. Here, we take the opportunity to review the early stages and follow developments of this discipline from a personal perspective.'),
(70917, 2003, 'bio', 'Automatic design of gene-specific sequence tags for genome-wide functional studies', 'Thareau, Vincent|Déhais, Patrice|Serizet, Carine|Hilson, Pierre|Rouzé, Pierre|Aubourg, Sébastien', 'Laboratoire Associé de lInstitut National de Recherche Agronomique, France.|Laboratoire Associé de lInstitut National de Recherche Agronomique, France.|Laboratoire Associé de lInstitut National de Recherche Agronomique, France.|Laboratoire Associé de lInstitut National de Recherche Agronomique, France.|Laboratoire Associé de lInstitut National de Recherche Agronomique, France.|Laboratoire Associé de lInstitut National de Recherche Agronomique, France.', 'France|France|France|France|France|France', 37, 'Algorithms|DNA Probes|Expressed Sequence Tags|Gene Expression Profiling|Genome|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btg286', '14630647', 'The availability of complete genome sequences allows the identification of short DNA segments that are specific to each annotated gene. Such unique gene sequence tags (GSTs) replace advantageously cDNAs in microarray transcript profiling experiments. In particular, probes corresponding to individual members of multigene families can be chosen carefully to avoid cross-hybridization events.'),
(70918, 2003, 'bio', 'A comparative study of machine-learning methods to predict the effects of single nucleotide polymorphisms on protein function', 'Krishnan, V G|Westhead, D R', 'School of Biochemistry and Molecular Biology, University of Leeds, Leeds LS2 9JT, UK.|School of Biochemistry and Molecular Biology, University of Leeds, Leeds LS2 9JT, UK.', 'United Kingdom|United Kingdom', 117, 'Algorithms|Animals|Artificial Intelligence|Caenorhabditis elegans Proteins|Cluster Analysis|Gene Expression Profiling|Pattern Recognition, Automated|Polymorphism, Single Nucleotide|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Species Specificity|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg297', '14630648', 'The large volume of single nucleotide polymorphism data now available motivates the development of methods for distinguishing neutral changes from those which have real biological effects. Here, two different machine-learning methods, decision trees and support vector machines (SVMs), are applied for the first time to this problem. In common with most other methods, only non-synonymous changes in protein coding regions of the genome are considered.'),
(70919, 2003, 'bio', 'MGraph: graphical models for microarray data analysis', 'Wang, Junbai|Myklebost, Ola|Hovig, Eivind', 'Tumor Biology Department, The Norwegian Radium Hospital, Montebello, 0310 Oslo, Norway. junbai.wang@radium.uio.no|Tumor Biology Department, The Norwegian Radium Hospital, Montebello, 0310 Oslo, Norway. junbai.wang@radium.uio.no|Tumor Biology Department, The Norwegian Radium Hospital, Montebello, 0310 Oslo, Norway. junbai.wang@radium.uio.no', 'Norway|Norway|Norway', 22, 'Algorithms|Computer Graphics|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg298', '14630649', 'This paper introduces a MATLAB toolbox, MGraph, which applies graphical models as a natural environment to formulate and solve problems in microarray data analysis. MGraph with its graphical interface allows the user to predict genetic regulatory networks by a graphical gaussian model (GGM), and to quantify the effects of different experimental treatment conditions on gene expression profiles by a graphical log-linear model (GLM). The power of graphical models was explored and illustrated through two example applications. First, four MAPK pathways in yeast were meaningfully reconstructed through GGM. Second, GLM was used to quantify the contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster. This application may provide a valuable aid in the prediction of genetic regulatory networks, as well as in investigations of various experimental conditions that affect global gene expression profiles.'),
(70920, 2003, 'bio', 'Linking the growth inhibition response from the National Cancer Institutes anticancer screen to gene expression levels and other molecular target data', 'Wallqvist, Anders|Rabow, Alfred A|Shoemaker, Robert H|Sausville, Edward A|Covell, David G', 'Science Applications International Corporation, National Cancer Institute at Frederick, National Institutes of Health Frederick, MD 21702, USA. wallqvist@ncifrcf.gov|Science Applications International Corporation, National Cancer Institute at Frederick, National Institutes of Health Frederick, MD 21702, USA. wallqvist@ncifrcf.gov|Science Applications International Corporation, National Cancer Institute at Frederick, National Institutes of Health Frederick, MD 21702, USA. wallqvist@ncifrcf.gov|Science Applications International Corporation, National Cancer Institute at Frederick, National Institutes of Health Frederick, MD 21702, USA. wallqvist@ncifrcf.gov|Science Applications International Corporation, National Cancer Institute at Frederick, National Institutes of Health Frederick, MD 21702, USA. wallqvist@ncifrcf.gov', 'United States|United States|United States|United States|United States', 23, 'Antineoplastic Agents|Biomarkers, Tumor|Cell Division|Cell Line, Tumor|Databases, Factual|Drug Screening Assays, Antitumor|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Targeting|Growth Inhibitors|Humans|Information Storage and Retrieval|Lethal Dose 50|National Institutes of Health (U.S.)|Neoplasms|United States', 'Evaluation Studies', '10.1093/bioinformatics/btg302', '14630650', 'Data mining tools are proposed to establish mechanistic connections between chemotypes and specific cellular functions. Drawing on a previous study that classified the cellular response patterns of growth inhibition measurements log( GI(50)) from the National Cancer Institutes (NCIs) anticancer screen, we have examined additional data for mRNA expression, sets of known molecular targets and mutational status against these same tumor cell lines to relate chemosensitivity more precisely to biochemical pathways.'),
(70921, 2003, 'bio', 'In silico analysis reveals substantial variability in the gene contents of the gamma proteobacteria LexA-regulon', 'Erill, Ivan|Escribano, Marcos|Campoy, Susana|Barbé, Jordi', 'Biomedical Applications Group, Centro Nacional de Microelectrónica, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.|Biomedical Applications Group, Centro Nacional de Microelectrónica, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.|Biomedical Applications Group, Centro Nacional de Microelectrónica, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.|Biomedical Applications Group, Centro Nacional de Microelectrónica, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.', 'Spain|Spain|Spain|Spain', 55, 'Algorithms|Bacterial Proteins|Consensus Sequence|Escherichia coli|Evolution, Molecular|Feasibility Studies|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Genetic Variation|Genome, Bacterial|Regulon|Sequence Alignment|Sequence Analysis, DNA|Serine Endopeptidases|Software|Software Validation', 'Comparative Study', '10.1093/bioinformatics/btg303', '14630651', 'Motif-prediction algorithm capabilities for the analysis of bacterial regulatory networks and the prediction of new regulatory sites can be greatly enhanced by the use of comparative genomics approaches. In this study, we make use of a consensus-building algorithm and comparative genomics to conduct an in-depth analysis of the LexA-regulon of gamma proteobacteria, and we use the inferred results to study the evolution of this regulatory network and to examine the usefulness of the control sequences and gene contents of regulons in phylogenetic analysis.'),
(70922, 2003, 'bio', 'Parametric alignment of ordered trees', 'Wang, Lusheng|Zhao, Jianyun', 'Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, Peoples Republic of China. lwang@cs.cityu.edu.hk|Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, Peoples Republic of China. lwang@cs.cityu.edu.hk', 'China|China', 16, 'Algorithms|Pattern Recognition, Automated|RNA|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/btg305', '14630652', 'Computing the similarity between two ordered trees has applications in RNA secondary structure comparison, genetics and chemical structure analysis. Alignment of tree is one of the proposed measures. Similar to pair-wise sequence comparison, there is often disagreement about how to weight matches, mismatches, indels and gaps when we compare two trees. For sequence comparison, the parametric sequence alignment tools have been developed. The users are allowed to see explicitly and completely the effect of parameter choices on the optimal sequence alignments. A similar tool for aligning two ordered trees is required in practice.'),
(70923, 2003, 'bio', 'A simple and efficient algorithm for gene selection using sparse logistic regression', 'Shevade, S K|Keerthi, S S', 'Department of Computer Science and Automation, Indian Institute of Science, Bangalore 560012, India.|Department of Computer Science and Automation, Indian Institute of Science, Bangalore 560012, India.', 'India|India', 253, 'Algorithms|Biomarkers, Tumor|Breast Neoplasms|Cluster Analysis|Colonic Neoplasms|Gene Expression Profiling|Genetic Testing|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Regression Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg308', '14630653', 'This paper gives a new and efficient algorithm for the sparse logistic regression problem. The proposed algorithm is based on the Gauss-Seidel method and is asymptotically convergent. It is simple and extremely easy to implement, it neither uses any sophisticated mathematical programming software nor needs any matrix operations. It can be applied to a variety of real-world problems like identifying marker genes and building a classifier in the context of cancer diagnosis using microarray data.'),
(70924, 2003, 'bio', 'Normality of oligonucleotide microarray data and implications for parametric statistical analyses', 'Giles, Peter J|Kipling, David', 'Department of Pathology, University of Wales College of Medicine, Heath Park, Cardiff CF14 4XN, UK.|Department of Pathology, University of Wales College of Medicine, Heath Park, Cardiff CF14 4XN, UK.', 'United Kingdom|United Kingdom', 46, 'Algorithms|Data Interpretation, Statistical|Gene Expression Profiling|Genetic Variation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Software|Software Validation', 'Comparative Study', '10.1093/bioinformatics/btg311', '14630654', 'Experimental limitations have resulted in the popularity of parametric statistical tests as a method for identifying differentially regulated genes in microarray data sets. However, these tests assume that the data follow a normal distribution. To date, the assumption that replicate expression values for any gene are normally distributed, has not been critically addressed for Affymetrix GeneChip data.'),
(70925, 2003, 'bio', 'Towards the in silico identification of class II restricted T-cell epitopes: a partial least squares iterative self-consistent algorithm for affinity prediction', 'Doytchinova, I A|Flower, D R', 'Edward Jenner Institute for Vaccine Research, Compton, Berkshire RG20 7NN, UK.|Edward Jenner Institute for Vaccine Research, Compton, Berkshire RG20 7NN, UK.', 'United Kingdom|United Kingdom', 70, 'Algorithms|Binding Sites|Combinatorial Chemistry Techniques|Computer Simulation|Epitopes, T-Lymphocyte|Histocompatibility Antigens Class II|Immunoassay|Least-Squares Analysis|Models, Molecular|Protein Binding|Protein Interaction Mapping|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg312', '14630655', 'The immunogenicity of peptides depends on their ability to bind to MHC molecules. MHC binding affinity prediction methods can save significant amounts of experimental work. The class II MHC binding site is open at both ends, making epitope prediction difficult because of the multiple binding ability of long peptides.'),
(70926, 2003, 'bio', 'Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks', 'Husmeier, Dirk', 'Biomathematics and Statistics Scotland, JCMB, The Kings Buildings, Edinburgh, EH9 3JZ, UK. dirk@bioss.ac.uk', 'United Kingdom', 393, 'Bayes Theorem|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Signal Transduction|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/btg313', '14630656', 'Bayesian networks have been applied to infer genetic regulatory interactions from microarray gene expression data. This inference problem is particularly hard in that interactions between hundreds of genes have to be learned from very small data sets, typically containing only a few dozen time points during a cell cycle. Most previous studies have assessed the inference results on real gene expression data by comparing predicted genetic regulatory interactions with those known from the biological literature. This approach is controversial due to the absence of known gold standards, which renders the estimation of the sensitivity and specificity, that is, the true and (complementary) false detection rate, unreliable and difficult. The objective of the present study is to test the viability of the Bayesian network paradigm in a realistic simulation study. First, gene expression data are simulated from a realistic biological network involving DNAs, mRNAs, inactive protein monomers and active protein dimers. Then, interaction networks are inferred from these data in a reverse engineering approach, using Bayesian networks and Bayesian learning with Markov chain Monte Carlo.'),
(70927, 2003, 'bio', 'Metabolomics spectral formatting, alignment and conversion tools (MSFACTs)', 'Duran, Anthony L|Yang, Jian|Wang, Liangjiang|Sumner, Lloyd W', 'The Samuel Roberts Noble Foundation, Inc., Ardmore, OK 73402, USA.|The Samuel Roberts Noble Foundation, Inc., Ardmore, OK 73402, USA.|The Samuel Roberts Noble Foundation, Inc., Ardmore, OK 73402, USA.|The Samuel Roberts Noble Foundation, Inc., Ardmore, OK 73402, USA.', 'United States|United States|United States|United States', 165, 'Cluster Analysis|Databases, Protein|Gas Chromatography-Mass Spectrometry|Gene Expression Regulation, Plant|Information Storage and Retrieval|Medicago|Models, Biological|Plant Proteins|Plant Structures|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg315', '14630657', 'The amplified interest in metabolic profiling has generated the need for additional tools to assist in the rapid analysis of complex data sets.'),
(70928, 2003, 'bio', 'Efficient remote homology detection using local structure', 'Hou, Yuna|Hsu, Wynne|Lee, Mong Li|Bystroff, Christopher', 'School of Computing, National University of Singapore, Singapore 117543. houyuna@comp.nus.edu.sg|School of Computing, National University of Singapore, Singapore 117543. houyuna@comp.nus.edu.sg|School of Computing, National University of Singapore, Singapore 117543. houyuna@comp.nus.edu.sg|School of Computing, National University of Singapore, Singapore 117543. houyuna@comp.nus.edu.sg', 'Singapore|Singapore|Singapore|Singapore', 65, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Databases, Protein|Molecular Sequence Data|Pattern Recognition, Automated|Practice Patterns, Physicians|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg317', '14630658', 'The function of an unknown biological sequence can often be accurately inferred if we are able to map this unknown sequence to its corresponding homologous family. At present, discriminative methods such as SVM-Fisher and SVM-pairwise, which combine support vector machine (SVM) and sequence similarity, are recognized as the most accurate methods, with SVM-pairwise being the most accurate. However, these methods typically encode sequence information into their feature vectors and ignore the structure information. They are also computationally inefficient. Based on these observations, we present an alternative method for SVM-based protein classification. Our proposed method, SVM-I-sites, utilizes structure similarity for remote homology detection.'),
(70929, 2003, 'bio', 'Missing-value estimation using linear and non-linear regression with Bayesian gene selection', 'Zhou, Xiaobo|Wang, Xiaodong|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.', 'United States|United States|United States', 61, 'Algorithms|Artifacts|BRCA2 Protein|Bayes Theorem|Breast Neoplasms|Carrier Proteins|Gene Deletion|Gene Expression Profiling|Genetic Variation|Humans|Linear Models|Models, Genetic|Models, Statistical|Nonlinear Dynamics|Oligonucleotide Array Sequence Analysis|Regression Analysis|Ubiquitin-Protein Ligases', 'Comparative Study', '10.1093/bioinformatics/btg323', '14630659', 'Data from microarray experiments are usually in the form of large matrices of expression levels of genes under different experimental conditions. Owing to various reasons, there are frequently missing values. Estimating these missing values is important because they affect downstream analysis, such as clustering, classification and network design. Several methods of missing-value estimation are in use. The problem has two parts: (1) selection of genes for estimation and (2) design of an estimation rule.'),
(70930, 2003, 'bio', 'PDB file parser and structure class implemented in Python', 'Hamelryck, Thomas|Manderick, Bernard', 'Department of Cellular and Molecular Interactions, Vlaams Interuniversitair Instituut voor Biotechnologie and Computational Modeling Lab, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. thamelry@vub.ac.be|Department of Cellular and Molecular Interactions, Vlaams Interuniversitair Instituut voor Biotechnologie and Computational Modeling Lab, Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. thamelry@vub.ac.be', 'Belgium|Belgium', 109, 'Computer Simulation|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Macromolecular Substances|Models, Molecular|Programming Languages|Protein Conformation|Software', 'Comparative Study', '10.1093/bioinformatics/btg299', '14630660', 'The biopython project provides a set of bioinformatics tools implemented in Python. Recently, biopython was extended with a set of modules that deal with macromolecular structure. Biopython now contains a parser for PDB files that makes the atomic information available in an easy-to-use but powerful data structure. The parser and data structure deal with features that are often left out or handled inadequately by other packages, e.g. atom and residue disorder (if point mutants are present in the crystal), anisotropic B factors, multiple models and insertion codes. In addition, the parser performs some sanity checking to detect obvious errors.'),
(70931, 2003, 'bio', 'TSGDB: a database system for tumor suppressor genes', 'Yang, Yanming|Fu, Li M', 'University of Florida, Gainesville, FL, USA.|University of Florida, Gainesville, FL, USA.', 'United States|United States', 16, 'Abstracting and Indexing as Topic|Database Management Systems|Databases, Genetic|Genes, Tumor Suppressor|Hypermedia|Information Storage and Retrieval|Internet|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg300', '14630661', 'A Web-based database system was constructed and implemented that contains 174 tumor suppressor genes. The database homepage was created to accommodate these genes in a pull-down window so that each gene can be viewed individually in a separate Web page. Information displayed on each page includes gene name, aliases, source organism, chromosome location, expression cells/tissues, gene structure, protein size, gene functions and major reference sources. Queries to the database can be conducted through a user-friendly interface, and query results are returned in the HTML format on dynamically generated web pages.'),
(70932, 2003, 'bio', 'MASV--Multiple (BLAST) Annotation System Viewer', 'Carter, Kim|Bellgard, Matthew', 'Centre for Bioinformatics and Biological Computing, School of Information Technology, Murdoch University, Murdoch 6150, WA, Australia. kcarter@cbbc.murdoch.edu.au|Centre for Bioinformatics and Biological Computing, School of Information Technology, Murdoch University, Murdoch 6150, WA, Australia. kcarter@cbbc.murdoch.edu.au', 'Australia|Australia', 6, 'Abstracting and Indexing as Topic|Computer Graphics|Database Management Systems|Databases, Genetic|Hypermedia|Information Storage and Retrieval|Internet|Sequence Analysis, DNA|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg301', '14630662', 'Multiple (BLAST) Annotation System Viewer (MASV) is a tool designed to aid in the annotation of genomic sequences. MASV enables the researcher to compare and analyse differences in annotation and analysis, resulting from changes in databases, analysis program parameters and results. This provides a unique capability for the user to conduct further bioinformatics analysis from the information obtained.'),
(70933, 2003, 'bio', 'GeneHuggers: database mining and application connectivity tools for subsequence analyses of the human genome', 'Iacovoni, Jason S', 'Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA. jiaco@scripps.edu', 'United States', 2, 'Abstracting and Indexing as Topic|Algorithms|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Genome, Human|Humans|Information Storage and Retrieval|Internet|Sequence Analysis|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg304', '14630663', 'GeneHuggers is a collection of program modules that enables precise selection of subsequence regions from records of the RefSeq human genome database. Subsequence regions can be selected based on diverse criteria, including feature addresses, annotations from LocusLink and UniGene, and results obtained from analyses with homologous subsequence detection programs. GeneHuggers provides functionality to the UNIX operating system that allows customized bioinformatics program development.'),
(70934, 2003, 'bio', 'BioWareDB: the biomedical software and database search engine', 'Matthiessen, M W', 'Department of Medical Gastroenterology (54O3), Herlev University Hospital, Herlev Ringvej 75, 2730 Herlev, Denmark. biocomp@madswichmann.dk', 'Denmark', 5, 'Abstracting and Indexing as Topic|Biomedical Research|Catalogs as Topic|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btg306', '14630664', 'A wealth of bioinformatics tools and databases has been created over the last decade and most are freely available to the general public. However, these valuable resources live a shadow existence compared to experimental results and methods that are widely published in journals and relatively easily found through publication databases such as PubMed. For the general scientist as well as bioinformaticists, these tools can deliver great value to the design and analysis of biological and medical experiments, but there is no inventory presenting an up-to-date and easily searchable index of all these resources. To remedy this, the BioWareDB search engine has been created. BioWareDB is an extensive and current catalog of software and databases of relevance to researchers in the fields of biology and medicine, and presently consists of 2800 validated entries.'),
(70935, 2003, 'bio', 'Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles', 'Eichler, Gabriel S|Huang, Sui|Ingber, Donald E', 'Vascular Biology Program, Department of Pathology, Childrens Hospital/Harvard Medical School, Boston, MA 02115, USA.|Vascular Biology Program, Department of Pathology, Childrens Hospital/Harvard Medical School, Boston, MA 02115, USA.|Vascular Biology Program, Department of Pathology, Childrens Hospital/Harvard Medical School, Boston, MA 02115, USA.', 'United States|United States|United States', 148, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Software|Systems Integration|Time Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg307', '14630665', 'Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on Gestalt recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians.'),
(70936, 2003, 'bio', 'BLAST++: BLASTing queries in batches', 'Wang, Hao|Ooi, Beng Chin|Tan, Kian-Lee|Ong, Twee-Hee|Zhou, Lei', 'Department of Computer Science, National University of Singapore, 3 Science Drive 2, Singapore 117543.|Department of Computer Science, National University of Singapore, 3 Science Drive 2, Singapore 117543.|Department of Computer Science, National University of Singapore, 3 Science Drive 2, Singapore 117543.|Department of Computer Science, National University of Singapore, 3 Science Drive 2, Singapore 117543.|Department of Computer Science, National University of Singapore, 3 Science Drive 2, Singapore 117543.', 'Singapore|Singapore|Singapore|Singapore|Singapore', 11, 'Algorithms|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|National Library of Medicine (U.S.)|Sequence Alignment|Sequence Analysis, DNA|Software|United States', 'Comparative Study', '10.1093/bioinformatics/btg310', '14630666', 'BLAST++ is a tool that is integrated with NCBI BLAST, allowing multiple, say K, queries to be searched against a database concurrently. The results obtained by BLAST++ are identical to that obtained by executing BLAST on each of the K queries, but BLAST++ completes the processing in a much shorter time.'),
(70937, 2003, 'bio', 'Libsequence: a C++ class library for evolutionary genetic analysis', 'Thornton, Kevin', 'Committee on Genetics, University of Chicago, 1101 East 57th Street, Chicago, IL 66037, USA. k-thornton@uchicago.edu', 'United States', 241, 'Algorithms|Evolution, Molecular|Gene Expression Profiling|Genetic Variation|Polymorphism, Genetic|Polymorphism, Single Nucleotide|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btg316', '14630667', 'A C++ class library is available to facilitate the implementation of software for genomics and sequence polymorphism analysis. The library implements methods for data manipulation and the calculation of several statistics commonly used to analyze SNP data. The object-oriented design of the library is intended to be extensible, allowing users to design custom classes for their own needs. In addition, routines are provided to process samples generated by a widely used coalescent simulation.'),
(70938, 2003, 'bio', 'PreP: gene expression data pre-processing', 'García de la Nava, Jorge|van Hijum, Sacha|Trelles, Oswaldo', 'Computer Architecture Department, Universidad de Málaga, 29080, Málaga, Spain and Department of Molecular Genetics, University of Groningen, The Netherlands.|Computer Architecture Department, Universidad de Málaga, 29080, Málaga, Spain and Department of Molecular Genetics, University of Groningen, The Netherlands.|Computer Architecture Department, Universidad de Málaga, 29080, Málaga, Spain and Department of Molecular Genetics, University of Groningen, The Netherlands.', 'Spain|Spain|Spain', 24, 'Algorithms|Database Management Systems|Gene Expression Profiling|Information Storage and Retrieval|Programming Languages|Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg318', '14630668', 'PreP is a versatile, powerful, standalone application that aims at pre-processing gene expression data.'),
(70939, 2003, 'bio', 'NCL: a C++ class library for interpreting data files in NEXUS format', 'Lewis, Paul O', 'Department of Ecology and Evolutionary Biology, University of Connecticut, 75 North Eagleville Road, Unit 3043, Storrs, CT 06269-3043, USA. paul.lewis@uconn.edu', 'United States', 17, 'Databases, Bibliographic|Databases, Genetic|Information Storage and Retrieval|Programming Languages|Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btg319', '14630669', 'The NEXUS Class Library (NCL) is a collection of C++ classes designed to simplify interpreting data files written in the NEXUS format used by many computer programs for phylogenetic analyses. The NEXUS format allows different programs to share the same data files, even though none of the programs can interpret all of the data stored therein. Because users are not required to reformat the data file for each program, use of the NEXUS format prevents cut-and-paste errors as well as the proliferation of copies of the original data file. The purpose of making the NCL available is to encourage the use of the NEXUS format by making it relatively easy for programmers to add the ability to interpret NEXUS files in newly developed software.'),
(70940, 2003, 'bio', 'MetaGeneAlyse: analysis of integrated transcriptional and metabolite data', 'Daub, Carsten O|Kloska, Sebastian|Selbig, Joachim', 'Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany. daub@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany. daub@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany. daub@mpimp-golm.mpg.de', 'Germany|Germany|Germany', 45, 'Algorithms|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Internet|Metabolism|Signal Transduction|Software|Systems Integration|Transcription, Genetic|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg321', '14630670', 'New techniques in sample preparation allow high throughput analysis of samples on the transcriptional as well as on the metabolic level. We present a service accessible via the web that allows the analysis of integrated data sets that combine gene-expression data and metabolic data. After uploading, data sets can be normalized, clustered by various methods and results can be graphically visualized. All calculations are carried out on a server, so even time- and memory-consuming analyses can be done independently of the performance of the client.'),
(70941, 2003, 'bio', 'Combining DNA expression with positional information to detect functional silencing of chromosomal regions', 'Hüsing, Johannes|Zeschnigk, Michael|Boes, Tanja|Jöckel, Karl-Heinz', 'Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitätsklinikum Essen, Hufelandstrasse 55, D-45122 Essen, Germany. johannes.huesing@medizin.uni-essen.de|Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitätsklinikum Essen, Hufelandstrasse 55, D-45122 Essen, Germany. johannes.huesing@medizin.uni-essen.de|Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitätsklinikum Essen, Hufelandstrasse 55, D-45122 Essen, Germany. johannes.huesing@medizin.uni-essen.de|Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitätsklinikum Essen, Hufelandstrasse 55, D-45122 Essen, Germany. johannes.huesing@medizin.uni-essen.de', 'Germany|Germany|Germany|Germany', 0, 'Chromosome Mapping|Chromosomes|Chromosomes, Human, Pair 3|DNA Mutational Analysis|Databases, Nucleic Acid|Gene Expression Profiling|Gene Silencing|Humans|Melanoma|Monosomy|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Uveal Neoplasms', 'Comparative Study', '10.1093/bioinformatics/btg314', '14668216', 'Loss of chromosomal material is often observed in cancer cells. In this situation the expression of genes is related to their position on the genome. Epigenetic phenomena may also silence several genes in the same region of a chromosome. While cytogenetic or other molecular genetic methods spot changes of DNA copy number, they cannot detect other causes of silencing.'),
(70942, 2003, 'bio', 'Annotation pattern of ESTs from Spodoptera frugiperda Sf9 cells and analysis of the ribosomal protein genes reveal insect-specific features and unexpectedly low codon usage bias', 'Landais, I|Ogliastro, M|Mita, K|Nohata, J|López-Ferber, M|Duonor-Cérutti, M|Shimada, T|Fournier, P|Devauchelle, G', 'Laboratoire de Pathologie Comparée, INRA-CNRS-Université Montpellier II, UMR 5087, 30380 Saint Christol-les-Alès, France.|Laboratoire de Pathologie Comparée, INRA-CNRS-Université Montpellier II, UMR 5087, 30380 Saint Christol-les-Alès, France.|Laboratoire de Pathologie Comparée, INRA-CNRS-Université Montpellier II, UMR 5087, 30380 Saint Christol-les-Alès, France.|Laboratoire de Pathologie Comparée, INRA-CNRS-Université Montpellier II, UMR 5087, 30380 Saint Christol-les-Alès, France.|Laboratoire de Pathologie Comparée, INRA-CNRS-Université Montpellier II, UMR 5087, 30380 Saint Christol-les-Alès, France.|Laboratoire de Pathologie Comparée, INRA-CNRS-Université Montpellier II, UMR 5087, 30380 Saint Christol-les-Alès, France.|Laboratoire de Pathologie Comparée, INRA-CNRS-Université Montpellier II, UMR 5087, 30380 Saint Christol-les-Alès, France.|Laboratoire de Pathologie Comparée, INRA-CNRS-Université Montpellier II, UMR 5087, 30380 Saint Christol-les-Alès, France.|Laboratoire de Pathologie Comparée, INRA-CNRS-Université Montpellier II, UMR 5087, 30380 Saint Christol-les-Alès, France.', 'France|France|France|France|France|France|France|France|France', 31, 'Abstracting and Indexing as Topic|Animals|Bias|Cell Line|Codon|Evolution, Molecular|Expressed Sequence Tags|Gene Expression Profiling|Information Storage and Retrieval|Phylogeny|Reproducibility of Results|Ribosomal Proteins|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Spodoptera', 'Comparative Study', '10.1093/bioinformatics/btg324', '14668217', 'A whole set of Expressed Sequence Tags (ESTs) from the Sf9 cell line of Spodoptera frugiperda is presented here for the first time. By this way we want to identify both conserved and specific genes of this pest species. We also expect from this analysis to find a class of protein sequences providing a tool to explore genomic features and phylogeny of Lepidoptera.'),
(70943, 2003, 'bio', 'JXP4BIGI: a generalized, Java XML-based approach for biological information gathering and integration', 'Huang, Yihua|Ni, Tianyun|Zhou, Lei|Su, Stanley', 'Database Systems R&D Center, College of Engineering, University of Florida, USA. yhuang@mail.mcg.edu|Database Systems R&D Center, College of Engineering, University of Florida, USA. yhuang@mail.mcg.edu|Database Systems R&D Center, College of Engineering, University of Florida, USA. yhuang@mail.mcg.edu|Database Systems R&D Center, College of Engineering, University of Florida, USA. yhuang@mail.mcg.edu', 'United States|United States|United States|United States', 11, 'Database Management Systems|Databases, Factual|Hypermedia|Information Storage and Retrieval|Software|Software Design|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btg327', '14668218', 'In the post-genomic era, biologists interested in systems biology often need to import data from public databases and construct their own system-specific or subject-oriented databases to support their complex analysis and knowledge discovery. To facilitate the analysis and data processing, customized and centralized databases are often created by extracting and integrating heterogeneous data retrieved from public databases. A generalized methodology for accessing, extracting, transforming and integrating the heterogeneous data is needed.'),
(70944, 2003, 'bio', 'Efficient estimation of emission probabilities in profile hidden Markov models', 'Ahola, Virpi|Aittokallio, Tero|Uusipaikka, Esa|Vihinen, Mauno', 'Department of Statistics, FIN-20014 University of Turku, Finland. virahola@utu.fi|Department of Statistics, FIN-20014 University of Turku, Finland. virahola@utu.fi|Department of Statistics, FIN-20014 University of Turku, Finland. virahola@utu.fi|Department of Statistics, FIN-20014 University of Turku, Finland. virahola@utu.fi', 'Finland|Finland|Finland|Finland', 6, 'Algorithms|Amino Acids|Databases, Protein|Enzymes|False Positive Reactions|Markov Chains|Models, Genetic|Models, Statistical|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg328', '14668219', 'Profile hidden Markov models provide a sensitive method for performing sequence database search and aligning multiple sequences. One of the drawbacks of the hidden Markov model is that the conserved amino acids are not emphasized, but signal and noise are treated equally. For this reason, the number of estimated emission parameters is often enormous. Focusing the analysis on conserved residues only should increase the accuracy of sequence database search.'),
(70945, 2003, 'bio', 'Combining phylogenetic data with co-regulated genes to identify regulatory motifs', 'Wang, Ting|Stormo, Gary D', 'Department of Genetics, Washington University Medical School, St. Louis, MO 63110, USA.|Department of Genetics, Washington University Medical School, St. Louis, MO 63110, USA.', 'United States|United States', 201, 'Algorithms|Conserved Sequence|Gene Expression Profiling|Gene Expression Regulation|Phylogeny|Regulatory Sequences, Nucleic Acid|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg329', '14668220', 'Discovery of regulatory motifs in unaligned DNA sequences remains a fundamental problem in computational biology. Two categories of algorithms have been developed to identify common motifs from a set of DNA sequences. The first can be called a multiple genes, single species approach. It proposes that a degenerate motif is embedded in some or all of the otherwise unrelated input sequences and tries to describe a consensus motif and identify its occurrences. It is often used for co-regulated genes identified through experimental approaches. The second approach can be called single gene, multiple species. It requires orthologous input sequences and tries to identify unusually well conserved regions by phylogenetic footprinting. Both approaches perform well, but each has some limitations. It is tempting to combine the knowledge of co-regulation among different genes and conservation among orthologous genes to improve our ability to identify motifs.'),
(70946, 2003, 'bio', 'Scoring clustering solutions by their biological relevance', 'Gat-Viks, I|Sharan, R|Shamir, R', 'School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. iritg@post.tau.ac.il|School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. iritg@post.tau.ac.il|School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. iritg@post.tau.ac.il', 'Israel|Israel|Israel', 54, 'Algorithms|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Models, Genetic|Models, Statistical|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg330', '14668221', 'A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering gene expression data into homogeneous groups was shown to be instrumental in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on clustering algorithms for gene expression analysis, very few works addressed the systematic comparison and evaluation of clustering results. Typically, different clustering algorithms yield different clustering solutions on the same data, and there is no agreed upon guideline for choosing among them.'),
(70947, 2003, 'bio', 'Classification of protein quaternary structure with support vector machine', 'Zhang, Shao-Wu|Pan, Quan|Zhang, Hong-Cai|Zhang, Yun-Long|Wang, Hai-Yu', 'Department of Automatic Control, Northwestern Polytechnical University, Xian 710072, Peoples Republic of China. shaowuzhang@hotmail.com|Department of Automatic Control, Northwestern Polytechnical University, Xian 710072, Peoples Republic of China. shaowuzhang@hotmail.com|Department of Automatic Control, Northwestern Polytechnical University, Xian 710072, Peoples Republic of China. shaowuzhang@hotmail.com|Department of Automatic Control, Northwestern Polytechnical University, Xian 710072, Peoples Republic of China. shaowuzhang@hotmail.com|Department of Automatic Control, Northwestern Polytechnical University, Xian 710072, Peoples Republic of China. shaowuzhang@hotmail.com', 'China|China|China|China|China', 76, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Cluster Analysis|Computing Methodologies|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Structure, Quaternary|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Space Simulation', 'Comparative Study', '10.1093/bioinformatics/btg331', '14668222', 'Since the gap between sharply increasing known sequences and slow accumulation of known structures is becoming large, an automatic classification process based on the primary sequences and known three-dimensional structure becomes indispensable. The classification of protein quaternary structure based on the primary sequences can provide some useful information for the biologists. So a fully automatic and reliable classification system is needed. This work tries to look for the effective methods of extracting attribute and the algorithm for classifying the quaternary structure from the primary sequences.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70948, 2003, 'bio', 'Algorithms for large-scale genotyping microarrays', 'Liu, Wei-mn|Di, Xiaojun|Yang, Geoffrey|Matsuzaki, Hajime|Huang, Jing|Mei, Rui|Ryder, Thomas B|Webster, Teresa A|Dong, Shoulian|Liu, Guoying|Jones, Keith W|Kennedy, Giulia C|Kulp, David', 'Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu|Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu|Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu|Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu|Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu|Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu|Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu|Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu|Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu|Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu|Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu|Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu|Affymetrix, Inc., 3380 Central Expressway, Santa Clara, CA 95051, USA. wliu@cs.iupui.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 82, 'Algorithms|Chromosome Mapping|Chromosomes, Human, X|Gene Expression Profiling|Gene Frequency|Genotype|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg332', '14668223', 'Analysis of many thousands of single nucleotide polymorphisms (SNPs) across whole genome is crucial to efficiently map disease genes and understanding susceptibility to diseases, drug efficacy and side effects for different populations and individuals. High density oligonucleotide microarrays provide the possibility for such analysis with reasonable cost. Such analysis requires accurate, reliable methods for feature extraction, classification, statistical modeling and filtering.'),
(70949, 2003, 'bio', 'caCORE: a common infrastructure for cancer informatics', 'Covitz, Peter A|Hartel, Frank|Schaefer, Carl|De Coronado, Sherri|Fragoso, Gilberto|Sahni, Himanso|Gustafson, Scott|Buetow, Kenneth H', 'National Cancer Institute Center for Bioinformatics, National Institutes of Health, U.S. Department of Health and Human Services, 6116 Executive Boulevard, Suite 403, Rockville MD 20852, USA. covitzp@mail.nih.gov|National Cancer Institute Center for Bioinformatics, National Institutes of Health, U.S. Department of Health and Human Services, 6116 Executive Boulevard, Suite 403, Rockville MD 20852, USA. covitzp@mail.nih.gov|National Cancer Institute Center for Bioinformatics, National Institutes of Health, U.S. Department of Health and Human Services, 6116 Executive Boulevard, Suite 403, Rockville MD 20852, USA. covitzp@mail.nih.gov|National Cancer Institute Center for Bioinformatics, National Institutes of Health, U.S. Department of Health and Human Services, 6116 Executive Boulevard, Suite 403, Rockville MD 20852, USA. covitzp@mail.nih.gov|National Cancer Institute Center for Bioinformatics, National Institutes of Health, U.S. Department of Health and Human Services, 6116 Executive Boulevard, Suite 403, Rockville MD 20852, USA. covitzp@mail.nih.gov|National Cancer Institute Center for Bioinformatics, National Institutes of Health, U.S. Department of Health and Human Services, 6116 Executive Boulevard, Suite 403, Rockville MD 20852, USA. covitzp@mail.nih.gov|National Cancer Institute Center for Bioinformatics, National Institutes of Health, U.S. Department of Health and Human Services, 6116 Executive Boulevard, Suite 403, Rockville MD 20852, USA. covitzp@mail.nih.gov|National Cancer Institute Center for Bioinformatics, National Institutes of Health, U.S. Department of Health and Human Services, 6116 Executive Boulevard, Suite 403, Rockville MD 20852, USA. covitzp@mail.nih.gov', 'United States|United States|United States|United States|United States|United States|United States|United States', 121, 'Animals|Computational Biology|Databases, Factual|Dictionaries, Medical as Topic|Humans|Information Storage and Retrieval|Internet|National Institutes of Health (U.S.)|Natural Language Processing|Neoplasms|United States|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btg335', '14668224', 'Sites with substantive bioinformatics operations are challenged to build data processing and delivery infrastructure that provides reliable access and enables data integration. Locally generated data must be processed and stored such that relationships to external data sources can be presented. Consistency and comparability across data sets requires annotation with controlled vocabularies and, further, metadata standards for data representation. Programmatic access to the processed data should be supported to ensure the maximum possible value is extracted. Confronted with these challenges at the National Cancer Institute Center for Bioinformatics, we decided to develop a robust infrastructure for data management and integration that supports advanced biomedical applications.'),
(70950, 2003, 'bio', 'Global snapshot of a protein interaction network-a percolation based approach', 'Chin, Chen-Shan|Samanta, Manoj Pratim', 'Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94143, USA. cschin@genome.ucsf.edu|Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94143, USA. cschin@genome.ucsf.edu', 'United States|United States', 32, 'Algorithms|Fungal Proteins|Metabolism|Models, Biological|Models, Chemical|Models, Statistical|Protein Binding|Protein Interaction Mapping|Proteins|Reproducibility of Results|Sensitivity and Specificity|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/btg339', '14668225', 'Biologically significant information can be revealed by modeling large-scale protein interaction data using graph theory based network analysis techniques. However, the methods that are currently being used draw conclusions about the global features of the network from local connectivity data. A more systematic approach would be to define global quantities that measure (1) how strongly a protein ties with the other parts of the network and (2) how significantly an interaction contributes to the integrity of the network, and connect them with phenotype data from other sources. In this paper, we introduce such global connectivity measures and develop a stochastic algorithm based upon percolation in random graphs to compute them.'),
(70951, 2003, 'bio', 'SEMEDA: ontology based semantic integration of biological databases', 'Köhler, Jacob|Philippi, Stephan|Lange, Matthias', 'AG Bioinformatics, Technical Faculty, Bielefeld University, Germany. jacob.koehler@uni-bielefeld.de|AG Bioinformatics, Technical Faculty, Bielefeld University, Germany. jacob.koehler@uni-bielefeld.de|AG Bioinformatics, Technical Faculty, Bielefeld University, Germany. jacob.koehler@uni-bielefeld.de', 'Germany|Germany|Germany', 91, 'Computational Biology|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Natural Language Processing|Semantics|Systems Integration|Terminology as Topic|User-Computer Interface|Vocabulary, Controlled', 'Comparative Study', '10.1093/bioinformatics/btg340', '14668226', 'Many molecular biological databases are implemented on relational Database Management Systems, which provide standard interfaces like JDBC and ODBC for data and metadata exchange. By using these interfaces, many technical problems of database integration vanish and issues related to semantics remain, e.g. the use of different terms for the same things, different names for equivalent database attributes and missing links between relevant entries in different databases.'),
(70952, 2003, 'bio', 'Susceptibility of non-linear systems as an approach to metabolic responses', 'Torralba, Antonio S', 'Departamento de Bioquímica y Biología Molecular I, Facultad de Ciencias Químicas, Universidad Complutense, 28040, Madrid, Spain. torralba@bbm1.ucm.es', 'Spain', 3, 'Algorithms|Catalysis|Feedback|Fructose|Homeostasis|Metabolism|Models, Biological|Multienzyme Complexes|Nonlinear Dynamics|Reproducibility of Results|Sensitivity and Specificity|Signal Transduction|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/btg341', '14668227', 'Recent developments of several analytical techniques and fast sampling procedures are making it possible to study non-linear dynamics on an automated basis. Approaches that suggest experimental setups and fully exploit the data are needed. To prevent unreliable fits of parameters to experimental data, model-independent methods would be advantageous. One such method consists in representing the response of a system by means of a transformation or functional, of an excitation, i.e. a flux of a metabolite.'),
(70953, 2003, 'bio', 'Metabolic pathways in three dimensions', 'Rojdestvenski, Igor', 'Department of Plant Physiology, Umeå University, Umeå 90187, Sweden. igor.rojdestvenski@plantphys.umu.se', 'Sweden', 12, 'Computer Graphics|Environment|Imaging, Three-Dimensional|Information Storage and Retrieval|Metabolism|Programming Languages|Signal Transduction|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg342', '14668228', 'Currently a substantial research effort is devoted to automated representation of metabolic and gene networks. Automatic visualization plays a significant role in such efforts, and becomes an important problem on its own. Graphical visualization of metabolic pathways has to be information dense and not overloaded, recognizable and unified, close to traditional and algebraically consistent. The use of three-dimensional virtual reality visualizations may help to understand better the intricate topology of metabolic and regulatory networks.'),
(70954, 2003, 'bio', 'Accelerating screening of 3D protein data with a graph theoretical approach', 'Frömmel, Cornelius|Gille, Christoph|Goede, Andrean|Gröpl, Clemens|Hougardy, Stefan|Nierhoff, Till|Preissner, Robert|Thimm, Martin', 'Institut für Biochemie, Charité, Monbijoustr. 2, Berlin, D-10117, Germany.|Institut für Biochemie, Charité, Monbijoustr. 2, Berlin, D-10117, Germany.|Institut für Biochemie, Charité, Monbijoustr. 2, Berlin, D-10117, Germany.|Institut für Biochemie, Charité, Monbijoustr. 2, Berlin, D-10117, Germany.|Institut für Biochemie, Charité, Monbijoustr. 2, Berlin, D-10117, Germany.|Institut für Biochemie, Charité, Monbijoustr. 2, Berlin, D-10117, Germany.|Institut für Biochemie, Charité, Monbijoustr. 2, Berlin, D-10117, Germany.|Institut für Biochemie, Charité, Monbijoustr. 2, Berlin, D-10117, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 9, 'Algorithms|Databases, Protein|Information Storage and Retrieval|Protein Conformation|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg343', '14668229', 'The Dictionary of Interfaces in Proteins (DIP) is a database collecting the 3D structure of interacting parts of proteins that are called patches. It serves as a repository, in which patches similar to given query patches can be found. The computation of the similarity of two patches is time consuming and traversing the entire DIP requires some hours. In this work we address the question of how the patches similar to a given query can be identified by scanning only a small part of DIP. The answer to this question requires the investigation of the distribution of the similarity of patches.'),
(70955, 2003, 'bio', 'A random variance model for detection of differential gene expression in small microarray experiments', 'Wright, George W|Simon, Richard M', 'National Cancer Institute Biometric Research Branch, National Institutes of Health, 6130 Executive Blvd., MSC 7434, Bethesda, MD 20892-7434, USA. wrightge@mail.nih.gov|National Cancer Institute Biometric Research Branch, National Institutes of Health, 6130 Executive Blvd., MSC 7434, Bethesda, MD 20892-7434, USA. wrightge@mail.nih.gov', 'United States|United States', 548, 'Algorithms|Analysis of Variance|False Positive Reactions|Gene Expression Profiling|Genetic Variation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg345', '14668230', 'Microarray techniques provide a valuable way of characterizing the molecular nature of disease. Unfortunately expense and limited specimen availability often lead to studies with small sample sizes. This makes accurate estimation of variability difficult, since variance estimates made on a gene by gene basis will have few degrees of freedom, and the assumption that all genes share equal variance is unlikely to be true.'),
(70956, 2003, 'bio', 'Assessing sequence comparison methods with the average precision criterion', 'Chen, Zhuoran', 'Department of Computer Science and Technology, Beijing University, Beijing 100871, Peoples Republic of China. cray@pku.edu.cn', 'China', 15, 'Algorithms|Databases, Protein|Information Storage and Retrieval|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg349', '14668231', 'Comprehensive performance assessment is important for improving sequence database search methods. Sensitivity, selectivity and speed are three major yet usually conflicting evaluation criteria. The average precision (AP) measure aims to combine the sensitivity and selectivity features of a search algorithm. It can be easily visualized and extended to analyze results from a set of queries. Finally, the time-AP plot can clearly show the overall performance of different search methods.'),
(70957, 2003, 'bio', 'Using credibility intervals instead of hypothesis tests in SAGE analysis', 'Vêncio, Ricardo Z N|Brentani, Helena|Pereira, Carlos A B', 'Departamento de Estatística, Instituto de Matemática e Estatística da Universidade de São Paulo, São Paulo 04601-003, Brazil, Fundação Antônio Prudente, São Paulo 01509-900, Brazil. rvencio@ime.usp.br|Departamento de Estatística, Instituto de Matemática e Estatística da Universidade de São Paulo, São Paulo 04601-003, Brazil, Fundação Antônio Prudente, São Paulo 01509-900, Brazil. rvencio@ime.usp.br|Departamento de Estatística, Instituto de Matemática e Estatística da Universidade de São Paulo, São Paulo 04601-003, Brazil, Fundação Antônio Prudente, São Paulo 01509-900, Brazil. rvencio@ime.usp.br', 'Brazil|Brazil|Brazil', 28, 'Algorithms|Breast Neoplasms|Expressed Sequence Tags|Gene Expression Profiling|Humans|Models, Genetic|Models, Statistical|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg357', '14668232', 'Statistical methods usually used to perform Serial Analysis of Gene Expression (SAGE) analysis are based on hypothesis testing. They answer the biologists question: what are the genes with differential expression greater than r with P-value smaller than P?. Another useful and not yet explored question is: what is the uncertainty in differential expression ratio of a gene?.'),
(70958, 2003, 'bio', 'A CART-based approach to discover emerging patterns in microarray data', 'Boulesteix, Anne-Laure|Tutz, Gerhard|Strimmer, Korbinian', 'Seminar for Applied Stochastics, Department of Statistics, University of Munich, Akademiestrasse 1, D-80799 Munich, Germany. boulesteix@stat.uni-muenchen.de|Seminar for Applied Stochastics, Department of Statistics, University of Munich, Akademiestrasse 1, D-80799 Munich, Germany. boulesteix@stat.uni-muenchen.de|Seminar for Applied Stochastics, Department of Statistics, University of Munich, Akademiestrasse 1, D-80799 Munich, Germany. boulesteix@stat.uni-muenchen.de', 'Germany|Germany|Germany', 60, 'Algorithms|Artificial Intelligence|Colonic Neoplasms|Gene Expression Profiling|Genetic Testing|Humans|Leukemia|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg361', '14668233', 'Cancer diagnosis using gene expression profiles requires supervised learning and gene selection methods. Of the many suggested approaches, the method of emerging patterns (EPs) has the particular advantage of explicitly modeling interactions among genes, which improves classification accuracy. However, finding useful (i.e. short and statistically significant) EP is typically very hard.'),
(70959, 2003, 'bio', 'The MUSC DNA Microarray Database', 'Argraves, Gary L|Barth, Jeremy L|Argraves, W Scott', 'Array Genetics, Inc., 59 Great Quarter Road, Newtown, CT 06482, USA.|Array Genetics, Inc., 59 Great Quarter Road, Newtown, CT 06482, USA.|Array Genetics, Inc., 59 Great Quarter Road, Newtown, CT 06482, USA.', 'United States|United States|United States', 0, 'Academic Medical Centers|Database Management Systems|Databases, Nucleic Acid|Information Dissemination|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|South Carolina', 'Journal Article', '10.1093/bioinformatics/btg325', '14668234', 'The Medical University of South Carolina (MUSC) DNA Microarray Database is a web-accessible archive of DNA microarray data. The database was developed using the DNA microarray project/data management system, micro ArrayDB. Annotations for each DNA microarray project and associated cRNA target information are stored in a MySQL relational database and linked to array hybridization data (raw and normalized). At the discretion of investigators, data are placed into the public domain where they can be interrogated and downloaded through a web browser. In addition to serving as an online resource of gene expression data, the MUSC DNA Microarray Database is a model for other academic DNA microarray data repositories.'),
(70960, 2003, 'bio', 'MREPATT: detection and analysis of exact consecutive repeats in genomic sequences', 'Roset, Roman|Subirana, Juan A|Messeguer, Xavier', 'Cepba-IBM Research Institute, Universitat Politècnica de Catalunya. C/Jordi Girona, 1-3, C6, 08034 Barcelona, Spain.|Cepba-IBM Research Institute, Universitat Politècnica de Catalunya. C/Jordi Girona, 1-3, C6, 08034 Barcelona, Spain.|Cepba-IBM Research Institute, Universitat Politècnica de Catalunya. C/Jordi Girona, 1-3, C6, 08034 Barcelona, Spain.', 'Spain|Spain|Spain', 0, 'Algorithms|Chromosome Mapping|Gene Expression Profiling|Genomics|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Software Design', 'Journal Article', '10.1093/bioinformatics/btg326', '14668235', 'We have developed a program to determine the number, length and position of exact consecutive repeats of short sequences in DNA fragments or whole genomes. The program also gives the statistical significance of results by comparing them with those expected for a random sequence generated according to a Markovian model.'),
(70961, 2003, 'bio', 'gff2aplot: Plotting sequence comparisons', 'Abril, Josep F|Guigó, Roderic|Wiehe, Thomas', 'Grup de Recerca en Informàtica Biomèdica, Institut Municipal dInvestigació Mèdica, Universitat Pompeu Fabra -Centre de Regulació Genòmica, Passeig Marítim de la Barceloneta 37-49, 08003 Barcelona, Catalonia, Spain. jabril@imim.es|Grup de Recerca en Informàtica Biomèdica, Institut Municipal dInvestigació Mèdica, Universitat Pompeu Fabra -Centre de Regulació Genòmica, Passeig Marítim de la Barceloneta 37-49, 08003 Barcelona, Catalonia, Spain. jabril@imim.es|Grup de Recerca en Informàtica Biomèdica, Institut Municipal dInvestigació Mèdica, Universitat Pompeu Fabra -Centre de Regulació Genòmica, Passeig Marítim de la Barceloneta 37-49, 08003 Barcelona, Catalonia, Spain. jabril@imim.es', 'Spain|Spain|Spain', 9, 'Animals|Computer Graphics|Database Management Systems|Genes, MHC Class II|Humans|Information Storage and Retrieval|Mice|Sequence Alignment|Sequence Analysis|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg334', '14668236', 'gff2aplot is a program to visualize the alignment of two sequences together with their annotations. Input for the program consists of single or multiple files in GFF-format which specify the alignment coordinates and annotation features of both sequences. Output is in PostScript format of any size. The features to be displayed are highly customizable to meet user specific needs. The program serves to generate print-quality images for comparative genome sequence analysis.'),
(70962, 2003, 'bio', 'MUTAGEN: multi-user tool for annotating genomes', 'Brügger, Kim|Redder, Peter|Skovgaard, Marie', 'Danish Archaea Centre, Institute of Molecular Biology, University of Copenhagen, Sølvgade 83H, DK-1307 Copenhagen K, Denmark. brugger@mermaid.molbio.ku.dk|Danish Archaea Centre, Institute of Molecular Biology, University of Copenhagen, Sølvgade 83H, DK-1307 Copenhagen K, Denmark. brugger@mermaid.molbio.ku.dk|Danish Archaea Centre, Institute of Molecular Biology, University of Copenhagen, Sølvgade 83H, DK-1307 Copenhagen K, Denmark. brugger@mermaid.molbio.ku.dk', 'Denmark|Denmark|Denmark', 0, 'Database Management Systems|Databases, Nucleic Acid|Documentation|Genomics|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg336', '14668237', 'MUTAGEN is a free prokaryotic annotation system. It offers the advantages of genome comparison, graphical sequence browsers, search facilities and open-source for user-specific adjustments. The web-interface allows several users to access the system from standard desktop computers. The Sulfolobus acidocaldarius genome, and several plasmids and viruses have so far been analysed and annotated using MUTAGEN.'),
(70963, 2003, 'bio', 'LOX-DB-- database on lipoxygenases', 'Lütteke, T|Krieg, P|Fürstenberger, G|von der Lieth, C-W', 'Central Spectroscopic Department, German Cancer Research Center, Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany. t.luettke@dkfz.de|Central Spectroscopic Department, German Cancer Research Center, Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany. t.luettke@dkfz.de|Central Spectroscopic Department, German Cancer Research Center, Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany. t.luettke@dkfz.de|Central Spectroscopic Department, German Cancer Research Center, Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany. t.luettke@dkfz.de', 'Germany|Germany|Germany|Germany', 0, 'Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Lipoxygenase|Models, Molecular|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg337', '14668238', 'Lipoxygenases are a family of enzymes involved in a variety of human diseases like inflammation, asthma, artherosclerosis and cancer. The lipoxygenases database (LOX-DB) aims to be a web accessible compendium of information in particular on the mammalian members of this multigene family. This resource includes molecular structures, reference data, tools for structural and computational analysis as well as links to related information maintained by others. The data can be retrieved by the use of various search options and analyzed applying publicly available visualization tools.'),
(70964, 2003, 'bio', 'GoFigure: automated Gene Ontology annotation', 'Khan, Salim|Situ, Gang|Decker, Keith|Schmidt, Carl J', 'Department of Computer and Information Sciences, University of Delaware, Newark, DE 19717, USA.|Department of Computer and Information Sciences, University of Delaware, Newark, DE 19717, USA.|Department of Computer and Information Sciences, University of Delaware, Newark, DE 19717, USA.|Department of Computer and Information Sciences, University of Delaware, Newark, DE 19717, USA.', 'United States|United States|United States|United States', 0, 'Documentation|Information Storage and Retrieval|Internet|Proteins|Sequence Alignment|Sequence Analysis|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg338', '14668239', 'We have developed a web tool to predict Gene Ontology (GO) terms. The tool accepts an input DNA or protein sequence, and uses BLAST to identify homologous sequences in GO annotated databases. A graph is returned to the user via email.'),
(70965, 2003, 'bio', 'PRIMEX: rapid identification of oligonucleotide matches in whole genomes', 'Lexa, Matej|Valle, Giorgio', 'Laboratory of Functional Genomics and Proteomics, Masaryk University Brno, Kotlarska 2, 61137 Brno, Czech Republic. m-lexa@sci.muni.cz|Laboratory of Functional Genomics and Proteomics, Masaryk University Brno, Kotlarska 2, 61137 Brno, Czech Republic. m-lexa@sci.muni.cz', '-|-', 0, 'Algorithms|Genome|Oligonucleotides|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg350', '14668240', 'PRIMEX (PRImer Match EXtractor) can detect oligonucleotide sequences in whole genomes, allowing for mismatches. Using a word lookup table and server functionality, PRIMEX accepts queries from client software and returns matches rapidly. We find it faster and more sensitive than currently available tools.'),
(70966, 2003, 'bio', 'KISS for STRAP: user extensions for a protein alignment editor', 'Gille, Christoph|Lorenzen, Stephan|Michalsky, Elke|Frömmel, Cornelius', 'Institut für Biochemie, Charité, Monbijoustr. 2, Berlin 10117, Germany. christoph.gille@charite.de|Institut für Biochemie, Charité, Monbijoustr. 2, Berlin 10117, Germany. christoph.gille@charite.de|Institut für Biochemie, Charité, Monbijoustr. 2, Berlin 10117, Germany. christoph.gille@charite.de|Institut für Biochemie, Charité, Monbijoustr. 2, Berlin 10117, Germany. christoph.gille@charite.de', 'Germany|Germany|Germany|Germany', 0, 'Computer Graphics|Databases, Protein|Models, Molecular|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg354', '14668241', 'The Structural Alignment Program STRAP is a comfortable comprehensive editor and analyzing tool for protein alignments. A wide range of functions related to protein sequences and protein structures are accessible with an intuitive graphical interface. Recent features include mapping of mutations and polymorphisms onto structures and production of high quality figures for publication. Here we address the general problem of multi-purpose program packages to keep up with the rapid development of bioinformatical methods and the demand for specific program functions. STRAP was remade implementing a novel design which aims at Keeping Interfaces in STRAP Simple (KISS). KISS renders STRAP extendable to bio-scientists as well as to bio-informaticians. Scientists with basic computer skills are capable of implementing statistical methods or embedding existing bioinformatical tools in STRAP themselves. For bio-informaticians STRAP may serve as an environment for rapid prototyping and testing of complex algorithms such as automatic alignment algorithms or phylogenetic methods. Further, STRAP can be applied as an interactive web applet to present data related to a particular protein family and as a teaching tool.'),
(70967, 2003, 'bio', 'SNOW: standard nomenclature wizard to help searching for (bio) chemical standardized names', 'Aguilar, Daniel|Oliva, Baldomero|Aviles, Francesc X|Querol, Enrique', 'Institut de Biotecnologia i de Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain.|Institut de Biotecnologia i de Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain.|Institut de Biotecnologia i de Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain.|Institut de Biotecnologia i de Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain.', 'Spain|Spain|Spain|Spain', 1, 'Algorithms|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Natural Language Processing|Reference Standards|Software|Terminology as Topic|Vocabulary, Controlled', 'Comparative Study', '10.1093/bioinformatics/btg355', '14668242', 'When developing bioinformatical tools dealing with enzymatic activity, metabolism or enzymatic networks, the problem of the lack of a clear nomenclature for biochemical compounds often arises. This problem leads us to develop a small web-based tool (SNOW, Standard NOmenclature Wizard) which may help to find recommended and trivial names or the correct closest spelling for a query compound name, if it exists.'),
(70968, 2003, 'bio', 'Machaon CVE: cluster validation for gene expression data', 'Bolshakova, Nadia|Azuaje, Francisco', 'Department of Computer Science, Trinity College Dublin, Dublin 2, Ireland. Nadia.Bolshakova@cs.tcd.ie|Department of Computer Science, Trinity College Dublin, Dublin 2, Ireland. Nadia.Bolshakova@cs.tcd.ie', 'Ireland|Ireland', 6, 'Algorithms|Cluster Analysis|Computer Graphics|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Sensitivity and Specificity|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg356', '14668243', 'This paper presents a cluster validation tool for gene expression data. Machaon CVE (Clustering and Validation Environment) system aims to partition samples or genes into groups characterized by similar expression patterns, and to evaluate the quality of the clusters obtained.'),
(70969, 2003, 'bio', 'DnaSP, DNA polymorphism analyses by the coalescent and other methods', 'Rozas, Julio|Sánchez-DelBarrio, Juan C|Messeguer, Xavier|Rozas, Ricardo', 'Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Diagonal 645, 08071 Barcelona, Spain. jrozas@ub.edu.es|Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Diagonal 645, 08071 Barcelona, Spain. jrozas@ub.edu.es|Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Diagonal 645, 08071 Barcelona, Spain. jrozas@ub.edu.es|Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Diagonal 645, 08071 Barcelona, Spain. jrozas@ub.edu.es', 'Spain|Spain|Spain|Spain', 4962, 'Algorithms|Gene Expression Profiling|Polymorphism, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg359', '14668244', 'DnaSP is a software package for the analysis of DNA polymorphism data. Present version introduces several new modules and features which, among other options allow: (1) handling big data sets (approximately 5 Mb per sequence), (2) conducting a large number of coalescent-based tests by Monte Carlo computer simulations, (3) extensive analyses of the genetic differentiation and gene flow among populations, (4) analysing the evolutionary pattern of preferred and unpreferred codons, (5) generating graphical outputs for an easy visualization of results.'),
(70970, 2003, 'bio', 'SPEPlip: the detection of signal peptide and lipoprotein cleavage sites', 'Fariselli, Piero|Finocchiaro, Giacomo|Casadio, Rita', 'Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. piero@biocomp.unibo.it|Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. piero@biocomp.unibo.it|Laboratory of Biocomputing, CIRB/Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. piero@biocomp.unibo.it', 'Italy|Italy|Italy', 56, 'Algorithms|Artificial Intelligence|Lipoproteins|Neural Networks (Computer)|Pattern Recognition, Automated|Protein Sorting Signals|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/btg360', '14668245', 'SPEPlip is a neural network-based method, trained and tested on a set of experimentally derived signal peptides from eukaryotes and prokaryotes. SPEPlip identifies the presence of sorting signals and predicts their cleavage sites. The accuracy in cross-validation is similar to that of other available programs: the rate of false positives is 4 and 6%, for prokaryotes and eukaryotes respectively and that of false negatives is 3% in both cases. When a set of 409 prokaryotic lipoproteins is predicted, SPEPlip predicts 97% of the chains in the signal peptide class. However, by integrating SPEPlip with a regular expression search utility based on the PROSITE pattern, we can successfully discriminate signal peptide-containing chains from lipoproteins. We propose the method for detecting and discriminating signal peptides containing chains and lipoproteins.'),
(70971, 2003, 'bio', 'ModLoop: automated modeling of loops in protein structures', 'Fiser, András|Sali, Andrej', 'Department of Biochemistry and Seaver Foundation Center for Bioinformatics, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461, USA. andras@fiserlab.org|Department of Biochemistry and Seaver Foundation Center for Bioinformatics, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461, USA. andras@fiserlab.org', 'United States|United States', 0, 'Amino Acid Sequence|Computer Simulation|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Structure, Secondary|Proteins|Reproducibility of Results|Sensitivity and Specificity|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg362', '14668246', 'ModLoop is a web server for automated modeling of loops in protein structures. The input is the atomic coordinates of the protein structure in the Protein Data Bank format, and the specification of the starting and ending residues of one or more segments to be modeled, containing no more than 20 residues in total. The output is the coordinates of the non-hydrogen atoms in the modeled segments. A user provides the input to the server via a simple web interface, and receives the output by e-mail. The server relies on the loop modeling routine in MODELLER that predicts the loop conformations by satisfaction of spatial restraints, without relying on a database of known protein structures. For a rapid response, ModLoop runs on a cluster of Linux PC computers.'),
(70972, 2003, 'bio', 'Characterizing gene sets with FuncAssociate', 'Berriz, Gabriel F|King, Oliver D|Bryant, Barbara|Sander, Chris|Roth, Frederick P', 'Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology, 250 Longwood Avenue, Boston, MA 02115, USA.|Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology, 250 Longwood Avenue, Boston, MA 02115, USA.|Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology, 250 Longwood Avenue, Boston, MA 02115, USA.|Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology, 250 Longwood Avenue, Boston, MA 02115, USA.|Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology, 250 Longwood Avenue, Boston, MA 02115, USA.', 'United States|United States|United States|United States|United States', 346, 'Algorithms|Animals|Database Management Systems|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Natural Language Processing|Proteins|Rats|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein|Software|Terminology as Topic', 'Comparative Study', '10.1093/bioinformatics/btg363', '14668247', 'FuncAssociate is a web-based tool to help researchers use Gene Ontology attributes to characterize large sets of genes derived from experiment. Distinguishing features of FuncAssociate include the ability to handle ranked input lists, and a Monte Carlo simulation approach that is more appropriate to determine significance than other methods, such as Bonferroni or idák p-value correction. FuncAssociate currently supports 10 organisms (Vibrio cholerae, Shewanella oneidensis, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Caenorhaebditis elegans, Drosophila melanogaster, Mus musculus, Rattus norvegicus and Homo sapiens).'),
(70973, 2004, 'bio', 'Twelve C2H2 zinc-finger genes on human chromosome 19 can be each translated into the same type of protein after frameshifts', 'Meng, Shao-Wu|Zhang, Zhuo|Li, Jinyan', 'Decision Systems Lab, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. swmeng@i2r.a-star.edu.sg|Decision Systems Lab, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. swmeng@i2r.a-star.edu.sg|Decision Systems Lab, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. swmeng@i2r.a-star.edu.sg', 'Singapore|Singapore|Singapore', 0, 'Base Sequence|Chromosomes, Human, Pair 19|DNA-Binding Proteins|Frameshift Mutation|Frameshifting, Ribosomal|Gene Expression Profiling|Humans|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology|Zinc Fingers', 'Evaluation Studies', '10.1093/bioinformatics/btg381', '14693802', 'We report a discovery that, of the 226 C2H2 zinc-finger (C2H2-ZNF) genes on human chromosome 19, 12 genes each have two open reading frames (ORFs) that are in different reading frames but that can be translated into the same type of C2H2-ZNF proteins. We came to this observation after using standard tools in an original manner. First, we found that the both ORFs of such a gene contained the same type of significant C2H2-ZNF domain with e-values of e-2 or better. Second, the both ORFs had a promoter, a transcription start site, a start codon, a Kozak pattern and a poly(A) site, hence, each of them can be viewed as a gene in terms of a genes primary structure. Third, both the ORFs matched not only human C2H2-ZNF expressed sequence tags (ESTs) but also human C2H2-ZNF proteins with e-values of e-50 or better. This indicates that the both ORFs can be transcribed and translated into the same zinc-finger proteins. More importantly, we observed that the phenomenon-a DNA can be translated into the same type of proteins after a frameshift-also occurred in a set of 160 human C2H2-ZNF ESTs and in a set of nine cDNAs of human C2H2-ZNF proteins. This observation based on the two sets of wet-experimental data much strengthened our confidence on the discovery. Our discovery is useful in the deeper understanding of a genes regulatory mechanism to maintain its function.'),
(70974, 2004, 'bio', 'Identifying periodically expressed transcripts in microarray time series data', 'Wichert, Sofia|Fokianos, Konstantinos|Strimmer, Korbinian', 'Department of Statistics, University of Munich, Ludwigstrasse 33, D-80539 Munich, Germany.|Department of Statistics, University of Munich, Ludwigstrasse 33, D-80539 Munich, Germany.|Department of Statistics, University of Munich, Ludwigstrasse 33, D-80539 Munich, Germany.', 'Germany|Germany|Germany', 228, 'Algorithms|Caulobacter crescentus|Cell Cycle|Gene Expression Profiling|Gene Expression Regulation|HeLa Cells|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Periodicity|Reproducibility of Results|Saccharomyces|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Time Factors|Transcription, Genetic', 'Comparative Study', '10.1093/bioinformatics/btg364', '14693803', 'Microarray experiments are now routinely used to collect large-scale time series data, for example to monitor gene expression during the cell cycle. Statistical analysis of this data poses many challenges, one being that it is hard to identify correctly the subset of genes with a clear periodic signature. This has lead to a controversial argument with regard to the suitability of both available methods and current microarray data.'),
(70975, 2004, 'bio', 'Prediction of protein subcellular locations using fuzzy k-NN method', 'Huang, Ying|Li, Yanda', 'State Key Laboratory of Intelligent Technology and Systems, Department of Automation, Institute of Bioinformatics, Tsinghua University, Beijing 100084, Peoples Republic of China. hying99@mails.tsinghua.edu.cn|State Key Laboratory of Intelligent Technology and Systems, Department of Automation, Institute of Bioinformatics, Tsinghua University, Beijing 100084, Peoples Republic of China. hying99@mails.tsinghua.edu.cn', 'China|China', 216, 'Algorithms|Animals|Cellular Structures|Databases, Protein|Fuzzy Logic|Gene Expression Profiling|Gene Expression Regulation|Humans|Proteome|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Species Specificity|Subcellular Fractions|Tissue Distribution', 'Comparative Study', '10.1093/bioinformatics/btg366', '14693804', 'Protein localization data are a valuable information resource helpful in elucidating protein functions. It is highly desirable to predict a proteins subcellular locations automatically from its sequence.'),
(70976, 2004, 'bio', 'Efficient filtering methods for clustering cDNAs with spliced sequence alignment', 'Shibuya, Tetsuo|Kashima, Hisashi|Konagaya, Akihiko', 'IBM Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, Kanagawa 242-8502, Japan. tshibuya@jp.ibm.com|IBM Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, Kanagawa 242-8502, Japan. tshibuya@jp.ibm.com|IBM Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, Kanagawa 242-8502, Japan. tshibuya@jp.ibm.com', 'Japan|Japan|Japan', 1, 'Algorithms|Animals|Base Sequence|Cluster Analysis|DNA, Complementary|DNA, Recombinant|Databases, Nucleic Acid|Gene Expression Profiling|Gene Library|Genome|Mice|Molecular Sequence Data|Pattern Recognition, Automated|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/btg367', '14693805', 'Clustering sequences of a full-length cDNA library into alternative splice form candidates is a very important problem.'),
(70977, 2004, 'bio', 'Protein beta-turn prediction using nearest-neighbor method', 'Kim, Saejoon', 'School of Computational Sciences, Korea Institute for Advanced Study, Seoul 130-722, Korea. saejoon@kias.re.kr', '-', 42, 'Algorithms|Amino Acid Sequence|Databases, Protein|Models, Molecular|Molecular Sequence Data|Protein Structure, Secondary|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/btg368', '14693806', 'With the emerging success of protein secondary structure prediction through the applications of various statistical and machine learning techniques, similar techniques have been applied to protein beta-turn prediction. In this study, we perform protein beta-turn prediction using a k-nearest neighbor method, which is combined with a filter that uses predicted protein secondary structure information. Traditional beta-turn prediction from k-nearest neighbor method is modified to account for the unbalanced ratio of the natural occurrence of beta-turns and non-beta-turns.'),
(70978, 2004, 'bio', 'ClusPro: an automated docking and discrimination method for the prediction of protein complexes', 'Comeau, Stephen R|Gatchell, David W|Vajda, Sandor|Camacho, Carlos J', 'Bioinformatics Graduate Program and Department, Boston University, 44 Cummington St, Boston, MA 02215, USA.|Bioinformatics Graduate Program and Department, Boston University, 44 Cummington St, Boston, MA 02215, USA.|Bioinformatics Graduate Program and Department, Boston University, 44 Cummington St, Boston, MA 02215, USA.|Bioinformatics Graduate Program and Department, Boston University, 44 Cummington St, Boston, MA 02215, USA.', 'United States|United States|United States|United States', 669, 'Algorithms|Binding Sites|Cluster Analysis|Discriminant Analysis|Energy Transfer|Models, Chemical|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Reproducibility of Results|Sensitivity and Specificity|Software', 'Comparative Study', '10.1093/bioinformatics/btg371', '14693807', 'Predicting protein interactions is one of the most challenging problems in functional genomics. Given two proteins known to interact, current docking methods evaluate billions of docked conformations by simple scoring functions, and in addition to near-native structures yield many false positives, i.e. structures with good surface complementarity but far from the native.'),
(70979, 2004, 'bio', 'Light-weight integration of molecular biological databases', 'Philippi, Stephan', 'Department of Computer Science, University of Koblenz, P.O. Box 201 106, 56016 Koblenz, Germany. philippi@uni-koblenz.de', 'Germany', 25, 'Computational Biology|Database Management Systems|Databases, Factual|Hypermedia|Information Storage and Retrieval|Pilot Projects|Software|Systems Integration|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg372', '14693808', 'Due to the increasing number of molecular biological databases and the exponential growth of their contents, database integration is an important topic of research in bioinformatics. Existing approaches in this area have in common that considerable efforts are needed to provide integrated access to heterogeneous data sources.'),
(70980, 2004, 'bio', 'An iterated loop matching approach to the prediction of RNA secondary structures with pseudoknots', 'Ruan, Jianhua|Stormo, Gary D|Zhang, Weixiong', 'Department of Computer Science, Washington University in St. Louis, St. Louis, MO 63130, USA. jruan@cse.wustl.edu|Department of Computer Science, Washington University in St. Louis, St. Louis, MO 63130, USA. jruan@cse.wustl.edu|Department of Computer Science, Washington University in St. Louis, St. Louis, MO 63130, USA. jruan@cse.wustl.edu', 'United States|United States|United States', 177, 'Algorithms|Base Pairing|Base Sequence|Feedback|Models, Molecular|Molecular Sequence Data|Nucleic Acid Conformation|RNA|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/btg373', '14693809', 'Pseudoknots have generally been excluded from the prediction of RNA secondary structures due to its difficulty in modeling. Although, several dynamic programming algorithms exist for the prediction of pseudoknots using thermodynamic approaches, they are neither reliable nor efficient. On the other hand, comparative methods are more reliable, but are often done in an ad hoc manner and require expert intervention. Maximum weighted matching, an algorithm for pseudoknot prediction with comparative analysis, suffers from low-prediction accuracy in many cases.'),
(70981, 2004, 'bio', 'Distribution of words with a predefined range of mismatches to a DNA probe in bacterial genomes', 'Melko, O Michael|Mushegian, Arcady R', 'Stowers Institute for Medical Research, Kansas City, MO 64110, USA. omm@stowers-institute.org|Stowers Institute for Medical Research, Kansas City, MO 64110, USA. omm@stowers-institute.org', 'United States|United States', 4, 'Base Pair Mismatch|Base Sequence|Computer-Aided Design|DNA Probes|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Genome, Bacterial|Models, Genetic|Models, Statistical|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/btg374', '14693810', 'Hybridization of oligonucleotides with longer nucleotide sequences is an essential step in nucleic acid biosynthesis in vitro and in vivo, in oligonucleotide-based diagnostics, and in therapeutic applications of oligonucleotides. A major factor determining sensitivity and selectivity of hybridization is the number of base pair mismatches that occur in an ungapped alignment of the oligonucleotide (probe) and a longer sequence (target).');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(70982, 2004, 'bio', 'MedBlast: searching articles related to a biological sequence', 'Tu, Qiang|Tang, Haixu|Ding, Dafu', 'Key Laboratory of Proteomics, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, Peoples Republic of China.|Key Laboratory of Proteomics, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, Peoples Republic of China.|Key Laboratory of Proteomics, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, Peoples Republic of China.', 'China|China|China', 14, 'Algorithms|Amino Acid Sequence|Base Sequence|Database Management Systems|Databases, Bibliographic|Databases, Genetic|Information Storage and Retrieval|MEDLINE|National Library of Medicine (U.S.)|Natural Language Processing|Periodicals as Topic|Sequence Alignment|Sequence Analysis|Software|United States|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/btg375', '14693811', 'In the genomic era, researchers often want to know more information about a biological sequence by retrieving its related articles. However, there is no available tool yet to achieve conveniently this goal. Here we developed a new literature-mining tool MedBlast, which uses natural language processing techniques, to retrieve the related articles of a given sequence. An online server of this program is also provided.'),
(70983, 2004, 'bio', 'Adaptive stochastic-deterministic chemical kinetic simulations', 'Vasudeva, Karan|Bhalla, Upinder S', 'National Centre for Biological Sciences, TIFR, GKVK Campus, Bangalore 560065, India.|National Centre for Biological Sciences, TIFR, GKVK Campus, Bangalore 560065, India.', 'India|India', 50, 'Algorithms|Combinatorial Chemistry Techniques|Feedback|Kinetics|Metabolism|Models, Biological|Models, Chemical|Models, Statistical|Multienzyme Complexes|Reproducibility of Results|Sensitivity and Specificity|Signal Transduction|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/btg376', '14693812', 'Biochemical signaling pathways and genetic circuits often involve very small numbers of key signaling molecules. Computationally expensive stochastic methods are necessary to simulate such chemical situations. Single-molecule chemical events often co-exist with much larger numbers of signaling molecules where mass-action kinetics is a reasonable approximation. Here, we describe an adaptive stochastic method that dynamically chooses between deterministic and stochastic calculations depending on molecular count and propensity of forward reactions. The method is fixed timestep and has first order accuracy. We compare the efficiency of this method with exact stochastic methods.'),
(70984, 2004, 'bio', 'VizStruct: exploratory visualization for gene expression profiling', 'Zhang, Li|Zhang, Aidong|Ramanathan, Murali', 'Department of Computer Science and Engineering, State University of New York at Buffalo, Buffalo, NY 14260, USA. lizhang@cse.buffalo.edu|Department of Computer Science and Engineering, State University of New York at Buffalo, Buffalo, NY 14260, USA. lizhang@cse.buffalo.edu|Department of Computer Science and Engineering, State University of New York at Buffalo, Buffalo, NY 14260, USA. lizhang@cse.buffalo.edu', 'United States|United States|United States', 17, 'Algorithms|Cluster Analysis|Computer Graphics|Female|Gene Expression|Genetic Testing|Humans|Male|Multiple Sclerosis|Neoplasms|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Signal Processing, Computer-Assisted|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg377', '14693813', 'DNA arrays provide a broad snapshot of the state of the cell by measuring the expression levels of thousands of genes simultaneously. Visualization techniques can enable the exploration and detection of patterns and relationships in a complex data set by presenting the data in a graphical format in which the key characteristics become more apparent. The dimensionality and size of array data sets however present significant challenges to visualization. The purpose of this study is to present an interactive approach for visualizing variations in gene expression profiles and to assess its usefulness for classifying samples.'),
(70985, 2004, 'bio', 'A global test for groups of genes: testing association with a clinical outcome', 'Goeman, Jelle J|van de Geer, Sara A|de Kort, Floor|van Houwelingen, Hans C', 'Department of Medical Statistics, Leiden University Medical Center, P.O. Box 9604, 2300 RC Leiden, The Netherlands. j.j.goeman@lumc.nl|Department of Medical Statistics, Leiden University Medical Center, P.O. Box 9604, 2300 RC Leiden, The Netherlands. j.j.goeman@lumc.nl|Department of Medical Statistics, Leiden University Medical Center, P.O. Box 9604, 2300 RC Leiden, The Netherlands. j.j.goeman@lumc.nl|Department of Medical Statistics, Leiden University Medical Center, P.O. Box 9604, 2300 RC Leiden, The Netherlands. j.j.goeman@lumc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands', 711, 'Algorithms|Cluster Analysis|Diagnosis, Computer-Assisted|Feasibility Studies|Gene Expression Profiling|Genetic Predisposition to Disease|Genetic Testing|Humans|Leukemia|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/btg382', '14693814', 'This paper presents a global test to be used for the analysis of microarray data. Using this test it can be determined whether the global expression pattern of a group of genes is significantly related to some clinical outcome of interest. Groups of genes may be any size from a single gene to all genes on the chip (e.g. known pathways, specific areas of the genome or clusters from a cluster analysis).'),
(70986, 2004, 'bio', 'A generalized likelihood ratio test to identify differentially expressed genes from microarray data', 'Wang, Song|Ethier, Stewart', 'Department of Mathematics, University of Utah, Salt Lake City, UT 84112, USA. song.wang@m.cc.utah.edu|Department of Mathematics, University of Utah, Salt Lake City, UT 84112, USA. song.wang@m.cc.utah.edu', 'United States|United States', 18, 'Algorithms|Gene Expression Profiling|Likelihood Functions|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg384', '14693815', 'Microarray technology emerges as a powerful tool in life science. One major application of microarray technology is to identify differentially expressed genes under various conditions. Currently, the statistical methods to analyze microarray data are generally unsatisfactory, mainly due to the lack of understanding of the distribution and error structure of microarray data.'),
(70987, 2004, 'bio', 'Adjustment of systematic microarray data biases', 'Benito, Monica|Parker, Joel|Du, Quan|Wu, Junyuan|Xiang, Dong|Perou, Charles M|Marron, J S', 'Department of Statistics and Econometrics, University of Carlos III, Madrid, Spain.|Department of Statistics and Econometrics, University of Carlos III, Madrid, Spain.|Department of Statistics and Econometrics, University of Carlos III, Madrid, Spain.|Department of Statistics and Econometrics, University of Carlos III, Madrid, Spain.|Department of Statistics and Econometrics, University of Carlos III, Madrid, Spain.|Department of Statistics and Econometrics, University of Carlos III, Madrid, Spain.|Department of Statistics and Econometrics, University of Carlos III, Madrid, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain', 270, 'Algorithms|Cluster Analysis|Discriminant Analysis|Gene Expression Profiling|Genetic Variation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Quality Control|Reproducibility of Results|Selection Bias|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg385', '14693816', 'Systematic differences due to experimental features of microarray experiments are present in most large microarray data sets. Many different experimental features can cause biases including different sources of RNA, different production lots of microarrays or different microarray platforms. These systematic effects present a substantial hurdle to the analysis of microarray data.'),
(70988, 2004, 'bio', 'Essentiality and damage in metabolic networks', 'Lemke, Ney|Herédia, Fabiana|Barcellos, Cláudia K|Dos Reis, Adriana N|Mombach, José C M', 'Laboratório de Bioinformática e Biologia Computacional, Centro de Ciências Exatas e Tecnológicas, Universidade do Vale do Rio dos Sinos, 93022-000 São Leopoldo, RS, Brazil.|Laboratório de Bioinformática e Biologia Computacional, Centro de Ciências Exatas e Tecnológicas, Universidade do Vale do Rio dos Sinos, 93022-000 São Leopoldo, RS, Brazil.|Laboratório de Bioinformática e Biologia Computacional, Centro de Ciências Exatas e Tecnológicas, Universidade do Vale do Rio dos Sinos, 93022-000 São Leopoldo, RS, Brazil.|Laboratório de Bioinformática e Biologia Computacional, Centro de Ciências Exatas e Tecnológicas, Universidade do Vale do Rio dos Sinos, 93022-000 São Leopoldo, RS, Brazil.|Laboratório de Bioinformática e Biologia Computacional, Centro de Ciências Exatas e Tecnológicas, Universidade do Vale do Rio dos Sinos, 93022-000 São Leopoldo, RS, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil', 73, 'Computer Simulation|Enzyme Activation|Enzyme Stability|Enzymes|Escherichia coli|Metabolism|Models, Biological|Multienzyme Complexes|Mutation|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/btg386', '14693817', 'Understanding the architecture of physiological functions from annotated genome sequences is a major task for postgenomic biology. From the annotated genome sequence of the microbe Escherichia coli, we propose a general quantitative definition of enzyme importance in a metabolic network. Using a graph analysis of its metabolism, we relate the extent of the topological damage generated in the metabolic network by the deletion of an enzyme to the experimentally determined viability of the organism in the absence of that enzyme. We show that the network is robust and that the extent of the damage relates to enzyme importance. We predict that a large fraction (91%) of enzymes causes little damage when removed, while a small group (9%) can cause serious damage. Experimental results confirm that this group contains the majority of essential enzymes. The results may reveal a universal property of metabolic networks.'),
(70989, 2004, 'bio', 'GIS: a biomedical text-mining system for gene information discovery', 'Chiang, Jung-Hsien|Yu, Hsu-Chun|Hsu, Huai-Jen', 'Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan, ROC. jchiang@mail.ncku.edu.tw|Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan, ROC. jchiang@mail.ncku.edu.tw|Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan, ROC. jchiang@mail.ncku.edu.tw', '-|-|-', 37, 'Abstracting and Indexing as Topic|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Natural Language Processing|PubMed|Software|Subject Headings|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btg369', '14693818', 'We present a biomedical text-mining system focused on four types of gene-related information: biological functions, associated diseases, related genes and gene-gene relations. The aim of this system is to provide researchers an easy-to-use bio-information service that will rapidly survey the rapidly burgeoning biomedical literature.'),
(70990, 2004, 'bio', 'GRIL: genome rearrangement and inversion locator', 'Darling, Aaron E|Mau, Bob|Blattner, Frederick R|Perna, Nicole T', 'Department of Computer Science, University of Wisconsin-Madison, 1656 Linden Dr, Madison, WI 53706, USA. darling@cs.wisc.edu|Department of Computer Science, University of Wisconsin-Madison, 1656 Linden Dr, Madison, WI 53706, USA. darling@cs.wisc.edu|Department of Computer Science, University of Wisconsin-Madison, 1656 Linden Dr, Madison, WI 53706, USA. darling@cs.wisc.edu|Department of Computer Science, University of Wisconsin-Madison, 1656 Linden Dr, Madison, WI 53706, USA. darling@cs.wisc.edu', 'United States|United States|United States|United States', 22, 'Chromosome Inversion|DNA Mutational Analysis|Gene Expression Profiling|Gene Rearrangement|Genome, Bacterial|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Comparative Study', '10.1093/bioinformatics/btg378', '14693819', 'GRIL is a tool to automatically identify collinear regions in a set of bacterial-size genome sequences. GRIL uses three basic steps. First, regions of high sequence identity are located. Second, some of these regions are filtered based on user-specified criteria. Finally, the remaining regions of sequence identity are used to define significant collinear regions among the sequences. By locating collinear regions of sequence, GRIL provides a basis for multiple genome alignment using current alignment systems. GRIL also provides a basis for using current inversion distance tools to infer phylogeny.'),
(70991, 2004, 'bio', 'HOMGL-comparing genelists across species and with different accession numbers', 'Blxc3xbcthgen, Nils|Kiexc5x82basa, Szymon M|Cajavec, Branka|Herzel, Hanspeter', 'Institute for Theoretical Biology, Humboldt University Berlin, Invalidenstrasse 43, Berlin, D-10115, Germany.|Institute for Theoretical Biology, Humboldt University Berlin, Invalidenstrasse 43, Berlin, D-10115, Germany.|Institute for Theoretical Biology, Humboldt University Berlin, Invalidenstrasse 43, Berlin, D-10115, Germany.|Institute for Theoretical Biology, Humboldt University Berlin, Invalidenstrasse 43, Berlin, D-10115, Germany.', 'Germany|Germany|Germany|Germany', 10, 'Algorithms|Database Management Systems|Databases, Genetic|Documentation|Gene Expression Profiling|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Software|Species Specificity|Systems Integration|Terminology as Topic|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg379', '14693820', 'Homology Gene List (HOMGL) is a web-based tool for comparing gene lists with different accession numbers and identifiers and between different organisms. UniGene, LocusLink, HomoloGene and Ensembl databases are utilized to map between these lists and to retrieve upstream or transcribed sequences for genes in these lists. We illustrate the use of HOMGL with respect to microarray studies and promoter analysis.'),
(70992, 2004, 'bio', 'WILMA-automated annotation of protein sequences', 'Prlixc4x87, Andreas|Domingues, Francisco S|Lackner, Peter|Sippl, Manfred J', 'Center of Applied Molecular Engineering, Institute for Chemistry and Biochemistry, University of Salzburg, Jakob-Haringerstr. 5, A-5020 Salzburg, Austria.|Center of Applied Molecular Engineering, Institute for Chemistry and Biochemistry, University of Salzburg, Jakob-Haringerstr. 5, A-5020 Salzburg, Austria.|Center of Applied Molecular Engineering, Institute for Chemistry and Biochemistry, University of Salzburg, Jakob-Haringerstr. 5, A-5020 Salzburg, Austria.|Center of Applied Molecular Engineering, Institute for Chemistry and Biochemistry, University of Salzburg, Jakob-Haringerstr. 5, A-5020 Salzburg, Austria.', 'Austria|Austria|Austria|Austria', 9, 'Amino Acid Sequence|Database Management Systems|Databases, Protein|Documentation|Gene Expression Profiling|Information Storage and Retrieval|Molecular Sequence Data|Proteins|Sequence Analysis, Protein|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg380', '14693821', 'Large-scale annotation of sets of proteins is a frequently occurring task in association with genome sequencing projects. Here, we present an automated platform for the functional annotation of large sets of protein sequences. Various bioinformatics tools are used to achieve a comprehensive description of protein sequences and to link these results to standard Gene Ontology descriptors for molecular function, biological processes and cellular components. Access to the annotation is provided via a web-interface and database queries. These interfaces allow to formulate proteome wide queries as well as the investigation of details of individual results. WILMA annotations of the proteomes of Homo sapiens, Mus musculus, Arabidopsis thaliana and Caenorhabditis elegans are accessible at http://www.came.sbg.ac.at/wilma/'),
(70993, 2004, 'bio', 'BugView: a browser for comparing genomes', 'Leader, David P', 'Division of Biochemistry and Molecular Biology, IBLS, Davidson Building, University of Glasgow, Glasgow G12 8QQ, UK. d.leader@bio.gla.ac.uk', 'United Kingdom', 15, 'Computer Graphics|Database Management Systems|Databases, Nucleic Acid|Documentation|Gene Expression Profiling|Genome|Genome, Bacterial|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg383', '14693822', 'BugView is a Java application for visualizing homologous genes on a pair of related genomes, and can also be used to view individual genomes. It accepts files of prokaryotic or eukaryotic genomes in GenBank format and allows users to assign homologous pairs, and make and save annotations.'),
(70994, 2004, 'bio', 'The genomic threading database', 'McGuffin, Liam J|Street, Stefano|Sørensen, Søren-Aksel|Jones, David T', 'Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK. l.mcguffin@cs.ucl.ac.uk|Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK. l.mcguffin@cs.ucl.ac.uk|Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK. l.mcguffin@cs.ucl.ac.uk|Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK. l.mcguffin@cs.ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 14, 'Database Management Systems|Databases, Protein|Documentation|Gene Expression Profiling|Genome|Information Storage and Retrieval|Proteome|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btg387', '14693823', 'The Genomic Threading Database currently contains structural annotations for the genomes of over 100 recently sequenced organisms. Annotations are carried out by using our modified GenTHREADER software and through implementing grid technology.'),
(70995, 2004, 'bio', 'PARIS: a proteomic analysis and resources indexation system', 'Wang, Juhui|Caron, Christophe|Mistou, Michel-Yves|Gitton, Christophe|Trubuil, Alain', 'INRA, Unit of Biometrics, 78352 Jouy-en-Josas, France. juhui.wang@jouy.inra.fr|INRA, Unit of Biometrics, 78352 Jouy-en-Josas, France. juhui.wang@jouy.inra.fr|INRA, Unit of Biometrics, 78352 Jouy-en-Josas, France. juhui.wang@jouy.inra.fr|INRA, Unit of Biometrics, 78352 Jouy-en-Josas, France. juhui.wang@jouy.inra.fr|INRA, Unit of Biometrics, 78352 Jouy-en-Josas, France. juhui.wang@jouy.inra.fr', 'France|France|France|France|France', 5, 'Abstracting and Indexing as Topic|Database Management Systems|Databases, Protein|Documentation|Gene Expression Profiling|Information Storage and Retrieval|Proteome|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg389', '14693824', 'We developed a system for managing data from two-dimensional electrophoresis-based proteomic experiments. Named PARIS, the system stores gel image and information about experiments and analysis procedures, allows the user to search and navigate in genomic and proteomic data, supports visual verification and validation of the analysis results, and provides tools for cross multi-experiment and multi-experimenter data validation and exploration.'),
(70996, 2004, 'bio', 'TM or not TM: transmembrane protein prediction with low false positive rate using DAS-TMfilter', 'Cserzo, Miklos|Eisenhaber, Frank|Eisenhaber, Birgit|Simon, Istvan', 'Agricultural Biotechnology Center, Szent-Gyorgyi A. 4, Gödöllö, H-2100 Hungary.|Agricultural Biotechnology Center, Szent-Gyorgyi A. 4, Gödöllö, H-2100 Hungary.|Agricultural Biotechnology Center, Szent-Gyorgyi A. 4, Gödöllö, H-2100 Hungary.|Agricultural Biotechnology Center, Szent-Gyorgyi A. 4, Gödöllö, H-2100 Hungary.', 'Hungary|Hungary|Hungary|Hungary', 80, 'Algorithms|Amino Acid Sequence|Databases, Protein|False Positive Reactions|Membrane Proteins|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg394', '14693825', 'Web-based servers implementing the DAS-TMfilter algorithm have been launched at three mirror sites and their usage is described. The underlying computer program is an upgraded and modified version of the DAS-prediction method. The new server is (approximately 1 among 100 unrelated queries) while the high efficiency of the original algorithm locating TM segments in queries is preserved (sensitivity of approximately 95% among documented proteins with helical TM regions).'),
(70997, 2004, 'bio', 'A strategy for assembling the maize (Zea mays L) genome', 'Emrich, Scott J|Aluru, Srinivas|Fu, Yan|Wen, Tsui-Jung|Narayanan, Mahesh|Guo, Ling|Ashlock, Daniel A|Schnable, Patrick S', 'Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, IA 50011, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Computing Methodologies|Database Management Systems|Databases, Nucleic Acid|Gene Expression Profiling|Genome, Plant|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Software|Software Design|Zea mays', 'Evaluation Studies', '10.1093/bioinformatics/bth017', '14734303', 'Because the bulk of the maize (Zea mays L.) genome consists of repetitive sequences, sequencing efforts are being targeted to its gene-rich fraction. Traditional assembly programs are inadequate for this approach because they are optimized for a uniform sampling of the genome and inherently lack the ability to differentiate highly similar paralogs.'),
(70998, 2004, 'bio', 'Multi-species comparative mapping in silico using the COMPASS strategy', 'Liu, Lei|Gong, George|Liu, Yong|Natarajan, Shreedhar|Larkin, Denis M|Everts-van der Wind, Annelie|Rebeiz, Mark|Beever, Jonathan E', 'The W. M. Keck Center for Comparative and Functional Genomics, University of Illinois at Urbana-Champaign, 1201 W. Gregory Drive, Urbana, IL 61801, USA. leiliu@uiuc.edu|The W. M. Keck Center for Comparative and Functional Genomics, University of Illinois at Urbana-Champaign, 1201 W. Gregory Drive, Urbana, IL 61801, USA. leiliu@uiuc.edu|The W. M. Keck Center for Comparative and Functional Genomics, University of Illinois at Urbana-Champaign, 1201 W. Gregory Drive, Urbana, IL 61801, USA. leiliu@uiuc.edu|The W. M. Keck Center for Comparative and Functional Genomics, University of Illinois at Urbana-Champaign, 1201 W. Gregory Drive, Urbana, IL 61801, USA. leiliu@uiuc.edu|The W. M. Keck Center for Comparative and Functional Genomics, University of Illinois at Urbana-Champaign, 1201 W. Gregory Drive, Urbana, IL 61801, USA. leiliu@uiuc.edu|The W. M. Keck Center for Comparative and Functional Genomics, University of Illinois at Urbana-Champaign, 1201 W. Gregory Drive, Urbana, IL 61801, USA. leiliu@uiuc.edu|The W. M. Keck Center for Comparative and Functional Genomics, University of Illinois at Urbana-Champaign, 1201 W. Gregory Drive, Urbana, IL 61801, USA. leiliu@uiuc.edu|The W. M. Keck Center for Comparative and Functional Genomics, University of Illinois at Urbana-Champaign, 1201 W. Gregory Drive, Urbana, IL 61801, USA. leiliu@uiuc.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Biological Evolution|Chromosome Mapping|Conserved Sequence|Genetic Markers|Humans|Mice|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software|Species Specificity', 'Comparative Study', '10.1093/bioinformatics/bth018', '14734304', 'The completion of human and mouse genome sequences provides a valuable resource for decoding other mammalian genomes. The comparative mapping by annotation and sequence similarity (COMPASS) strategy takes advantage of the resource and has been used in several genome-mapping projects. It uses existing comparative genome maps based on conserved regions to predict map locations of a sequence. An automated multiple-species COMPASS tool can facilitate in the genome sequencing effort and comparative genomics study of other mammalian species.'),
(70999, 2004, 'bio', 'Transposable element annotation of the rice genome', 'Juretic, Nikoleta|Bureau, Thomas E|Bruskiewich, Richard M', 'Department of Biology, McGill University, Montreal, Quebec, H3A 1B1 Canada. njuret@po-box.mcgill.ca|Department of Biology, McGill University, Montreal, Quebec, H3A 1B1 Canada. njuret@po-box.mcgill.ca|Department of Biology, McGill University, Montreal, Quebec, H3A 1B1 Canada. njuret@po-box.mcgill.ca', 'Canada|Canada|Canada', 0, 'Algorithms|DNA Transposable Elements|Databases, Nucleic Acid|Documentation|Gene Expression Profiling|Genome, Plant|Models, Genetic|Models, Statistical|Oryza|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth019', '14734305', 'The high content of repetitive sequences in the genomes of many higher eukaryotes renders the task of annotating them computationally intensive. Presently, the only widely accepted method of searching and annotating transposable elements (TEs) in large genomic sequences is the use of the RepeatMasker program, which identifies new copies of TEs by pairwise sequence comparisons with a library of known TEs. Profile hidden Markov models (HMMs) have been used successfully in discovering distant homologs of known proteins in large protein databases, but this approach has only rarely been applied to known model TE families in genomic DNA.'),
(71000, 2004, 'bio', 'Computational identification of novel chitinase-like proteins in the Drosophila melanogaster genome', 'Zhu, Qingsong|Deng, Youping|Vanka, Phaneendra|Brown, Susan J|Muthukrishnan, Subbaratnam|Kramer, Karl J', 'Department of Biochemistry, Kansas State University, Manhattan, KS 66506, USA.|Department of Biochemistry, Kansas State University, Manhattan, KS 66506, USA.|Department of Biochemistry, Kansas State University, Manhattan, KS 66506, USA.|Department of Biochemistry, Kansas State University, Manhattan, KS 66506, USA.|Department of Biochemistry, Kansas State University, Manhattan, KS 66506, USA.|Department of Biochemistry, Kansas State University, Manhattan, KS 66506, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Amino Acid Sequence|Animals|Chitinases|Databases, Protein|Drosophila melanogaster|Gene Expression Profiling|Genome|Models, Molecular|Molecular Sequence Data|Phylogeny|Protein Conformation|Protein Structure, Tertiary|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bth020', '14734306', 'Multiple chitinases as well as lectins closely related to them have been characterized previously from many insect species and the corresponding genes/cDNAs have been cloned. However, the identification of the entire assortment of genes for chitinase family proteins and their differences in biochemical properties have not been carried out in any individual insect species. The completion of the entire DNA sequence of Drosophila melanogaster (fruit fly) genome and identification of open reading frames presents an opportunity to study the structures and functions of chitinase-like proteins, and also to identify new members of this family in Drosophila. We are, therefore, interested in studying the functional genomics of chitinase-like gene families in insects.'),
(71001, 2004, 'bio', 'Phylogenomic inference of protein molecular function: advances and challenges', 'Sjölander, Kimmen', 'Berkeley Phylogenomics Group, Department of Bioengineering, University of California, 473 Evans Hall 1762, Berkeley, CA 94720-1762, USA. kimmen@uclink.berkeley.edu', 'United States', 153, 'Algorithms|Animals|Gene Expression Profiling|Humans|Models, Genetic|Phylogeny|Proteome|Proteomics|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bth021', '14734307', 'Protein families evolve a multiplicity of functions through gene duplication, speciation and other processes. As a number of studies have shown, standard methods of protein function prediction produce systematic errors on these data. Phylogenomic analysis--combining phylogenetic tree construction, integration of experimental data and differentiation of orthologs and paralogs--has been proposed to address these errors and improve the accuracy of functional classification. The explicit integration of structure prediction and analysis in this framework, which we call structural phylogenomics, provides additional insights into protein superfamily evolution.'),
(71002, 2004, 'bio', 'A comparative phylogenetic approach for dating whole genome duplication events', 'Chapman, Brad A|Bowers, John E|Schulze, Stefan R|Paterson, Andrew H', 'Department of Plant Biology, University of Georgia, Athens, GA 30602, USA. chapmanb@uga.edu|Department of Plant Biology, University of Georgia, Athens, GA 30602, USA. chapmanb@uga.edu|Department of Plant Biology, University of Georgia, Athens, GA 30602, USA. chapmanb@uga.edu|Department of Plant Biology, University of Georgia, Athens, GA 30602, USA. chapmanb@uga.edu', 'Georgia|Georgia|Georgia|Georgia', 35, 'Algorithms|Arabidopsis|DNA Mutational Analysis|Evolution, Molecular|Gene Duplication|Gene Expression Profiling|Genome|Information Storage and Retrieval|Oryza|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software|Time Factors', 'Journal Article', '10.1093/bioinformatics/bth022', '14734308', 'Whole genome duplications have played a major role in determining the structure of eukaryotic genomes. Current evidence revealing large blocks of duplicated chromatin yields new insights into the evolutionary history of species, but also presents a major challenge for researchers attempting to utilize comparative genomics techniques. Understanding the timing of duplication events relative to divergence among taxa is critical to accurate and comprehensive cross-species comparisons.'),
(71003, 2004, 'bio', 'Prediction of locally stable RNA secondary structures for genome-wide surveys', 'Hofacker, I L|Priwitzer, B|Stadler, P F', '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', 102, 'Algorithms|Animals|Base Pairing|Caenorhabditis elegans|Computer Simulation|Genome|Models, Molecular|Models, Statistical|Nucleic Acid Conformation|Nucleic Acid Denaturation|RNA|Sequence Analysis, RNA|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/btg388', '14734309', 'Recently novel classes of functional RNAs, most prominently the miRNAs have been discovered, strongly suggesting that further types of functional RNAs are still hidden in the recently completed genomic DNA sequences. Only few techniques are known, however, to survey genomes for such RNA genes. When sufficiently similar sequences are not available for comparative approaches the only known remedy is to search directly for structural features.'),
(71004, 2004, 'bio', 'Shared relationship analysis: ranking set cohesion and commonalities within a literature-derived relationship network', 'Wren, Jonathan D|Garner, Harold R', 'Advanced Center for Genome Technology, Department of Botany and Microbiology, The University of Oklahoma, 620 Parrington Oval, Rm. 106, Norman, OK 73019, USA. Jonathan.Wren@OU.edu|Advanced Center for Genome Technology, Department of Botany and Microbiology, The University of Oklahoma, 620 Parrington Oval, Rm. 106, Norman, OK 73019, USA. Jonathan.Wren@OU.edu', 'United States|United States', 68, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Terminology as Topic', 'Evaluation Studies', '10.1093/bioinformatics/btg390', '14734310', 'There is a general scientific need to be able to identify and evaluate what any given set of objects (e.g. genes, phenotypes, chemicals, diseases) has in common. Whether it is to classify, expand upon or identify commonalities and functional groupings, informational needs can be diverse and the best source to identify relationships among a potentially heterogeneous set of objects is the scientific literature.'),
(71005, 2004, 'bio', 'Limited conformational space for early-stage protein folding simulation', 'Brylixc5x84ski, M|Jurkowski, W|Konieczny, L|Roterman, I', 'Institute of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakxc3xb3w, Poland.|Institute of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakxc3xb3w, Poland.|Institute of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakxc3xb3w, Poland.|Institute of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakxc3xb3w, Poland.', 'Poland|Poland|Poland|Poland', 17, 'Algorithms|Aprotinin|Binding Sites|Computer Simulation|Energy Transfer|Models, Molecular|Motion|Protein Binding|Protein Conformation|Protein Folding|Proteins', 'Evaluation Studies', '10.1093/bioinformatics/btg391', '14734311', 'The problem of early-stage protein folding is critical for protein structure prediction. The model presented introduces a common definition of protein structures which may be treated as the possible in silico early-stage form of the polypeptide chain. Limitation of the conformational space to the ellipse path on the Ramachandran map was tested as a possible sub-space to represent the early-stage structure for simulation of protein folding. The proposed conformational sub-space was developed on the basis of the backbone conformation, with side-chain interactions excluded.'),
(71006, 2004, 'bio', 'Comparative evaluation of word composition distances for the recognition of SCOP relationships', 'Vinga, Susana|Gouveia-Oliveira, Rodrigo|Almeida, Jonas S', 'Biomathematics Group, ITQB, Universidade Nova de Lisboa, Rua da Quinta Grande, n. 6, 2780-156 Oeiras, Portugal. svinga@itqb.unl.pt|Biomathematics Group, ITQB, Universidade Nova de Lisboa, Rua da Quinta Grande, n. 6, 2780-156 Oeiras, Portugal. svinga@itqb.unl.pt|Biomathematics Group, ITQB, Universidade Nova de Lisboa, Rua da Quinta Grande, n. 6, 2780-156 Oeiras, Portugal. svinga@itqb.unl.pt', 'Portugal|Portugal|Portugal', 27, 'Algorithms|Cluster Analysis|Databases, Protein|Pattern Recognition, Automated|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg392', '14734312', 'Alignment-free metrics were recently reviewed by the authors, but have not until now been object of a comparative study. This paper compares the classification accuracy of word composition metrics therein reviewed. It also presents a new distance definition between protein sequences, the W-metric, which bridges between alignment metrics, such as scores produced by the Smith-Waterman algorithm, and methods based solely in L-tuple composition, such as Euclidean distance and Information content.'),
(71007, 2004, 'bio', 'GAPSCORE: finding gene and protein names one word at a time', 'Chang, Jeffrey T|Schütze, Hinrich|Altman, Russ B', 'Department of Genetics, Stanford Medical Center, 300 Pasteur Drive, Lane L 301, Mail Code 5120, Stanford, CA 94305-5120, USA.|Department of Genetics, Stanford Medical Center, 300 Pasteur Drive, Lane L 301, Mail Code 5120, Stanford, CA 94305-5120, USA.|Department of Genetics, Stanford Medical Center, 300 Pasteur Drive, Lane L 301, Mail Code 5120, Stanford, CA 94305-5120, USA.', 'United States|United States|United States', 57, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Database Management Systems|Dictionaries as Topic|Genes|Information Storage and Retrieval|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Proteins|Reproducibility of Results|Sensitivity and Specificity|Software|Terminology as Topic', 'Comparative Study', '10.1093/bioinformatics/btg393', '14734313', 'New high-throughput technologies have accelerated the accumulation of knowledge about genes and proteins. However, much knowledge is still stored as written natural language text. Therefore, we have developed a new method, GAPSCORE, to identify gene and protein names in text. GAPSCORE scores words based on a statistical model of gene names that quantifies their appearance, morphology and context.'),
(71008, 2004, 'bio', 'Minimal cut sets in biochemical reaction networks', 'Klamt, Steffen|Gilles, Ernst Dieter', 'Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr.1, D-39106 Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de|Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr.1, D-39106 Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de', 'Germany|Germany', 172, 'Algorithms|Biochemistry|Cell Physiological Phenomena|Computer Simulation|Escherichia coli|Metabolism|Models, Biological|Multienzyme Complexes|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/btg395', '14734314', 'Structural studies of metabolic networks yield deeper insight into topology, functionality and capabilities of the metabolisms of different organisms. Here, we address the analysis of potential failure modes in metabolic networks whose occurrence will render the network structurally incapable of performing certain functions. Such studies will help to identify crucial parts in the network structure and to find suitable targets for repressing undesired metabolic functions.'),
(71009, 2004, 'bio', 'An empirical bayes adjustment to increase the sensitivity of detecting differentially expressed genes in microarray experiments', 'Datta, Susmita|Satten, Glen A|Benos, Dale J|Xia, Jiazeng|Heslin, Martin J|Datta, Somnath', 'Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA. datta@stat.uga.edu|Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA. datta@stat.uga.edu|Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA. datta@stat.uga.edu|Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA. datta@stat.uga.edu|Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA. datta@stat.uga.edu|Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA. datta@stat.uga.edu', 'Georgia|Georgia|Georgia|Georgia|Georgia|Georgia', 20, 'Algorithms|Analysis of Variance|Bayes Theorem|Colonic Neoplasms|Gene Expression Profiling|Genetic Variation|Humans|Oligonucleotide Array Sequence Analysis|Organ Specificity|Quality Control|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg396', '14734315', 'Detection of differentially expressed genes is one of the major goals of microarray experiments. Pairwise comparison for each gene is not appropriate without controlling the overall (experimentwise) type 1 error rate. Dudoit et al. have advocated use of permutation-based step-down P-value adjustments to correct the observed significance levels for the individual (i.e. for each gene) two sample t-tests.'),
(71010, 2004, 'bio', 'Graph-based clustering for finding distant relationships in a large set of protein sequences', 'Kawaji, Hideya|Takenaka, Yoichi|Matsuda, Hideo', 'Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka 560-8531, Japan.|Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka 560-8531, Japan.|Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka 560-8531, Japan.', 'Japan|Japan|Japan', 32, 'Algorithms|Amino Acid Sequence|Cluster Analysis|Databases, Protein|Genetic Linkage|Microtubule-Associated Proteins|Molecular Sequence Data|Neuropeptides|Protein Kinases|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg397', '14734316', 'Clustering of protein sequences is widely used for the functional characterization of proteins. However, it is still not easy to cluster distantly-related proteins, which have only regional similarity among their sequences. It is therefore necessary to develop an algorithm for clustering such distantly-related proteins.'),
(71011, 2004, 'bio', 'Is cross-validation better than resubstitution for ranking genes?', 'Braga-Neto, Ulisses|Hashimoto, Ronaldo|Dougherty, Edward R|Nguyen, Danh V|Carroll, Raymond J', 'Section of Clinical Cancer Genetics, University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.|Section of Clinical Cancer Genetics, University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.|Section of Clinical Cancer Genetics, University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.|Section of Clinical Cancer Genetics, University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.|Section of Clinical Cancer Genetics, University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.', 'United States|United States|United States|United States|United States', 58, 'Algorithms|Cluster Analysis|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Genes|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg399', '14734317', 'Ranking gene feature sets is a key issue for both phenotype classification, for instance, tumor classification in a DNA microarray experiment, and prediction in the context of genetic regulatory networks. Two broad methods are available to estimate the error (misclassification rate) of a classifier. Resubstitution fits a single classifier to the data, and applies this classifier in turn to each data observation. Cross-validation (in leave-one-out form) removes each observation in turn, constructs the classifier, and then computes whether this leave-one-out classifier correctly classifies the deleted observation. Resubstitution typically underestimates classifier error, severely so in many cases. Cross-validation has the advantage of producing an effectively unbiased error estimate, but the estimate is highly variable. In many applications it is not the misclassification rate per se that is of interest, but rather the construction of gene sets that have the potential to classify or predict. Hence, one needs to rank feature sets based on their performance.'),
(71012, 2004, 'bio', 'Formalization of mouse embryo anatomy', 'Burger, Albert|Davidson, Duncan|Baldock, Richard', 'MRC Human Genetics Unit, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, Scotland, UK. Albert.Burger@hgu.mrc.ac.uk|MRC Human Genetics Unit, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, Scotland, UK. Albert.Burger@hgu.mrc.ac.uk|MRC Human Genetics Unit, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, Scotland, UK. Albert.Burger@hgu.mrc.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 29, 'Algorithms|Animals|Artificial Intelligence|Computer Simulation|Database Management Systems|Databases, Factual|Embryo, Mammalian|Gene Expression Profiling|Gene Expression Regulation, Developmental|Information Storage and Retrieval|Mice|Models, Anatomic|Models, Genetic|Software|Systems Integration|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg400', '14734318', 'The Edinburgh Mouse Atlas and Gene Expression Database project has developed a digital atlas of mouse development to provide a spatio-temporal framework for spatially mapped data such as in situ gene expression and cell lineage. As part of this database, a mouse embryo anatomy ontology has been created. A formalization of this anatomy is required to document its precise semantics and how it is used in the context of the Mouse Atlas.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71013, 2004, 'bio', 'The Helmholtz Network for Bioinformatics: an integrative web portal for bioinformatics resources', 'Crass, T|Antes, I|Basekow, R|Bork, P|Buning, C|Christensen, M|Claussen, H|Ebeling, C|Ernst, P|Gailus-Durner, V|Glatting, K-H|Gohla, R|Gössling, F|Grote, K|Heidtke, K|Herrmann, A|OKeeffe, S|Kiesslich, O|Kolibal, S|Korbel, J O|Lengauer, T|Liebich, I|van der Linden, M|Luz, H|Meissner, K|von Mering, C|Mevissen, H-T|Mewes, H-W|Michael, H|Mokrejs, M|Müller, T|Pospisil, H|Rarey, M|Reich, J G|Schneider, R|Schomburg, D|Schulze-Kremer, S|Schwarzer, K|Sommer, I|Springstubbe, S|Suhai, S|Thoppae, G|Vingron, M|Warfsmann, J|Werner, T|Wetzler, D|Wingender, E|Zimmer, R', 'Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de|Department of Bioinformatics, Medical Faculty, Georg August University Göttingen, Goldschmidtstrasse 1, 37077 Göttingen, Germany. torsten.crass@med.uni-goettingen.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 7, 'Algorithms|Computational Biology|Database Management Systems|Germany|Information Storage and Retrieval|Interinstitutional Relations|Internet|Sequence Analysis, DNA|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg398', '14734319', 'The Helmholtz Network for Bioinformatics (HNB) is a joint venture of eleven German bioinformatics research groups that offers convenient access to numerous bioinformatics resources through a single web portal. The Guided Solution Finder which is available through the HNB portal helps users to locate the appropriate resources to answer their queries by employing a detailed, tree-like questionnaire. Furthermore, automated complex tool cascades (tasks), involving resources located on different servers, have been implemented, allowing users to perform comprehensive data analyses without the requirement of further manual intervention for data transfer and re-formatting. Currently, automated cascades for the analysis of regulatory DNA segments as well as for the prediction of protein functional properties are provided.'),
(71014, 2004, 'bio', 'ROSO: optimizing oligonucleotide probes for microarrays', 'Reymond, Nancie|Charles, Hubert|Duret, Laurent|Calevro, Federica|Beslon, Guillaume|Fayard, Jean-Michel', 'Biologie Fonctionnelle, Insectes et Interactions (BF2I), UMR INRA/INSA de Lyon, 69621 Villeurbanne, France. nancie.reymond@jouy.inra.fr|Biologie Fonctionnelle, Insectes et Interactions (BF2I), UMR INRA/INSA de Lyon, 69621 Villeurbanne, France. nancie.reymond@jouy.inra.fr|Biologie Fonctionnelle, Insectes et Interactions (BF2I), UMR INRA/INSA de Lyon, 69621 Villeurbanne, France. nancie.reymond@jouy.inra.fr|Biologie Fonctionnelle, Insectes et Interactions (BF2I), UMR INRA/INSA de Lyon, 69621 Villeurbanne, France. nancie.reymond@jouy.inra.fr|Biologie Fonctionnelle, Insectes et Interactions (BF2I), UMR INRA/INSA de Lyon, 69621 Villeurbanne, France. nancie.reymond@jouy.inra.fr|Biologie Fonctionnelle, Insectes et Interactions (BF2I), UMR INRA/INSA de Lyon, 69621 Villeurbanne, France. nancie.reymond@jouy.inra.fr', 'France|France|France|France|France|France', 57, 'Algorithms|Computer-Aided Design|Equipment Design|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Oligonucleotides|Quality Control|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg401', '14734320', 'ROSO is software to design optimal oligonucleotide probe sets for microarrays. Selected probes show no significant cross-hybridization, no stable secondary structures and their Tm are chosen to minimize the Tm variability of the probe set.'),
(71015, 2004, 'bio', 'LVB: parsimony and simulated annealing in the search for phylogenetic trees', 'Barker, D', 'School of Animal and Microbial Sciences, University of Reading, Whiteknights, P.O. Box 228, Reading, Berkshire, RG6 6AJ, UK. d.barker@reading.ac.uk', 'United Kingdom', 0, 'Algorithms|Biological Evolution|Gene Expression Profiling|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btg402', '14734321', 'The program LVB seeks parsimonious phylogenies from nucleotide alignments, using the simulated annealing heuristic. LVB runs fast and gives high quality results.'),
(71016, 2004, 'bio', 'PGTdb: a database providing growth temperatures of prokaryotes', 'Huang, Shir-Ly|Wu, Li-Cheng|Liang, Han-Kuen|Pan, Kuan-Ting|Horng, Jorng-Tzong|Ko, Ming-Tat', 'Department of Life Sciences, National Central University, Taiwan. slhuang@cc.ncu.edu.tw|Department of Life Sciences, National Central University, Taiwan. slhuang@cc.ncu.edu.tw|Department of Life Sciences, National Central University, Taiwan. slhuang@cc.ncu.edu.tw|Department of Life Sciences, National Central University, Taiwan. slhuang@cc.ncu.edu.tw|Department of Life Sciences, National Central University, Taiwan. slhuang@cc.ncu.edu.tw|Department of Life Sciences, National Central University, Taiwan. slhuang@cc.ncu.edu.tw', '-|-|-|-|-|-', 20, 'Archaea|Cell Division|Database Management Systems|Databases, Factual|Databases, Protein|Information Storage and Retrieval|Prokaryotic Cells|Protein Conformation|Protein Denaturation|Proteins|Sequence Analysis, Protein|Temperature', 'Journal Article', '10.1093/bioinformatics/btg403', '14734322', 'Included in Prokaryotic Growth Temperature database (PGTdb) are a total of 1334 temperature data from 1072 prokaryotic organisms, Bacteria and Archaea: PGTdb integrates microbial growth temperature data from literature survey with their nucleotide/protein sequence and protein structure data from related databases. A direct correlation is observed between the average growth temperature of an organism and the melting temperature of proteins from the organism. Therefore, this database is useful not only for microbiologists to obtain cultivation condition, but also for biochemists and structure biologists to study the correlation between protein sequences/structures and their thermostability. In addition, the taxonomy and ribosomal RNA sequence(s) of an organism are linked through NCBI Taxonomy and the Ribosomal RNA Operon Copy Number Database umdb, respectively. PGTdb is the only integrated database on the Internet to provide the growth temperature data of the prokaryotes and the combined information of their nucleotide/protein sequences, protein structures, taxonomy and phylogeny.'),
(71017, 2004, 'bio', 'JDotter: a Java interface to multiple dotplots generated by dotter', 'Brodie, Ryan|Roper, Rachel L|Upton, Chris', 'Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC V8W 3P6, Canada.|Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC V8W 3P6, Canada.|Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC V8W 3P6, Canada.', 'Canada|Canada|Canada', 84, 'Computer Graphics|Database Management Systems|Databases, Nucleic Acid|Hypermedia|Information Storage and Retrieval|Internet|Sequence Alignment|Sequence Analysis, DNA|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg406', '14734323', 'Java-Dotter (JDotter) is a platform-independent Java interactive interface for the Linux version of Dotter, a widely used program for generating dotplots of large DNA or protein sequences. JDotter runs as a client-server application and can send new sequences to the Dotter program for alignment as well as rapidly access a repository of preprocessed dotplots. JDotter also interfaces with a sequence database or file system to display supplementary feature data. Thus, JDotter greatly simplifies access to dotplot data in laboratories that deal with large numbers of genomes and have a multi-platform organization.'),
(71018, 2004, 'bio', 'FGDP: functional genomics data pipeline for automated, multiple microarray data analyses', 'Grant, Jeffrey D|Somers, Luke A|Zhang, Yue|Manion, Frank J|Bidaut, Ghislain|Ochs, Michael F', 'Bioinformatics, Department of Information Science and Technology, Division of Basic Science, Fox Chase Cancer Center, 7701 Burholme Avenue, Philadelphia, PA 19111, USA.|Bioinformatics, Department of Information Science and Technology, Division of Basic Science, Fox Chase Cancer Center, 7701 Burholme Avenue, Philadelphia, PA 19111, USA.|Bioinformatics, Department of Information Science and Technology, Division of Basic Science, Fox Chase Cancer Center, 7701 Burholme Avenue, Philadelphia, PA 19111, USA.|Bioinformatics, Department of Information Science and Technology, Division of Basic Science, Fox Chase Cancer Center, 7701 Burholme Avenue, Philadelphia, PA 19111, USA.|Bioinformatics, Department of Information Science and Technology, Division of Basic Science, Fox Chase Cancer Center, 7701 Burholme Avenue, Philadelphia, PA 19111, USA.|Bioinformatics, Department of Information Science and Technology, Division of Basic Science, Fox Chase Cancer Center, 7701 Burholme Avenue, Philadelphia, PA 19111, USA.', 'United States|United States|United States|United States|United States|United States', 5, 'Computing Methodologies|Database Management Systems|Gene Expression Profiling|Genomics|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btg407', '14734324', 'Gene expression microarrays and oligonucleotide GeneChips have provided biologists with a means of measuring, in a single experiment, the expression levels of entire genomes under a variety of conditions. As with any nascent field, there is no single accepted method for analyzing the new data types, with new methods appearing monthly. Investigators using the new technology must constantly seek access to the latest tools and explore their data in multiple ways. The functional genomics data pipeline provides an integrated, extendable analysis environment permitting multiple, simultaneous analyses to be automatically performed and provides a web server and interface for presenting results.'),
(71019, 2004, 'bio', 'YETI: Yeast Exploration Tool Integrator', 'Orton, R J|Sellers, W I|Gerloff, D L', 'Institute of Cell and Molecular Biology, University of Edinburgh, Edinburgh, EH9 3JR, UK.|Institute of Cell and Molecular Biology, University of Edinburgh, Edinburgh, EH9 3JR, UK.|Institute of Cell and Molecular Biology, University of Edinburgh, Edinburgh, EH9 3JR, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Computer Graphics|Genome, Fungal|Information Storage and Retrieval|Protein Interaction Mapping|Proteome|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg408', '14734325', 'Yeast Exploration Tool Integrator (YETI) is a novel bioinformatics tool for the integrated visualization and analysis of functional genomic data sets from the budding yeast Saccharomyces cerevisiae.'),
(71020, 2004, 'bio', 'EST-PAGE--managing and analyzing EST data', 'Matukumalli, Lakshmi K|Grefenstette, John J|Sonstegard, Tad S|Van Tassell, Curtis P', 'US Department of Agriculture, ARS, Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, Beltsville, MD 20705, USA.|US Department of Agriculture, ARS, Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, Beltsville, MD 20705, USA.|US Department of Agriculture, ARS, Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, Beltsville, MD 20705, USA.|US Department of Agriculture, ARS, Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, Beltsville, MD 20705, USA.', 'United States|United States|United States|United States', 0, 'Database Management Systems|Databases, Nucleic Acid|Expressed Sequence Tags|Gene Expression Profiling|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btg411', '14734326', 'EST-PAGE provides a bioinformatics solution for expressed sequence tags (EST) data entry, database management, GenBank submission, process control and data retrieval from a unified web interface that can be easily customized and adapted by groups working on diverse EST sequencing projects.'),
(71021, 2004, 'bio', 'APE: Analyses of Phylogenetics and Evolution in R language', 'Paradis, Emmanuel|Claude, Julien|Strimmer, Korbinian', 'Laboratoire de Paléontologie, Paléobiologie and Phylogénie, Institut des Sciences de lEvolution, Université Montpellier II, F-34095 Montpellier cédex 05, France. paradis@isem.univ-montp2.fr|Laboratoire de Paléontologie, Paléobiologie and Phylogénie, Institut des Sciences de lEvolution, Université Montpellier II, F-34095 Montpellier cédex 05, France. paradis@isem.univ-montp2.fr|Laboratoire de Paléontologie, Paléobiologie and Phylogénie, Institut des Sciences de lEvolution, Université Montpellier II, F-34095 Montpellier cédex 05, France. paradis@isem.univ-montp2.fr', 'France|France|France', 6774, 'Biological Evolution|Computer Graphics|Evolution, Molecular|Gene Expression Profiling|Genetics, Population|Phylogeny|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg412', '14734327', 'Analysis of Phylogenetics and Evolution (APE) is a package written in the R language for use in molecular evolution and phylogenetics. APE provides both utility functions for reading and writing data and manipulating phylogenetic trees, as well as several advanced methods for phylogenetic and evolutionary analysis (e.g. comparative and population genetic methods). APE takes advantage of the many R functions for statistics and graphics, and also provides a flexible framework for developing and implementing further statistical methods for the analysis of evolutionary processes.'),
(71022, 2004, 'bio', 'AnaGram: protein function assignment', 'Pérez, A J|Thode, G|Trelles, O', 'Genetics Department and Computer Architecture Department, University of Málaga, 29071 Málaga, Spain. antoniojperez@uma.es|Genetics Department and Computer Architecture Department, University of Málaga, 29071 Málaga, Spain. antoniojperez@uma.es|Genetics Department and Computer Architecture Department, University of Málaga, 29071 Málaga, Spain. antoniojperez@uma.es', 'Spain|Spain|Spain', 0, 'Algorithms|Amino Acid Motifs|Documentation|Information Storage and Retrieval|Internet|MEDLINE|Natural Language Processing|Periodicals as Topic|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg414', '14734328', 'AnaGram is a web service for protein function assignment based on identity detection of small significant fragments (protomotifs) that can act as modular pieces in peptide construction. The system is able to assign function by finding correlations between protomotifs and functional annotations contained in SWISS-PROT and Medline databases. In addition, function ontologies are used for hierarchical organization of the predicted functions. Extensive tests have been carried out to evaluate the accuracy and performance of the system.'),
(71023, 2004, 'bio', 'Modeling the relationship between LVAD support time and gene expression changes in the human heart by penalized partial least squares', 'Huang, Xiaohong|Pan, Wei|Park, Soon|Han, Xinqiang|Miller, Leslie W|Hall, Jennifer', 'Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, Minneapolis, MN 55455-0378, USA.|Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, Minneapolis, MN 55455-0378, USA.|Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, Minneapolis, MN 55455-0378, USA.|Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, Minneapolis, MN 55455-0378, USA.|Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, Minneapolis, MN 55455-0378, USA.|Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, Minneapolis, MN 55455-0378, USA.', 'United States|United States|United States|United States|United States|United States', 34, 'Adaptation, Physiological|Gene Expression Profiling|Gene Expression Regulation|Genetic Testing|Heart Failure|Heart-Assist Devices|Humans|Least-Squares Analysis|Models, Cardiovascular|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Patient Selection|Prognosis|Reproducibility of Results|Sensitivity and Specificity|Time Factors|Treatment Outcome', 'Comparative Study', '10.1093/bioinformatics/btg499', '14751963', 'Heart failure affects more than 20 million people in the world. Heart transplantation is the most effective therapy, but the number of eligible patients far outweighs the number of available donor hearts. The left mechanical ventricular assist device (LVAD) has been developed as a successful substitution therapy that aids the failing ventricle while a patient is waiting for the donor heart. We obtained genomics data from paired human heart samples harvested at the time of LVAD implant and explant. The heart failure patients in our study were supported by the LVAD for various periods of time. The goal of this study is to model the relationship between the time of LVAD support and gene expression changes.'),
(71024, 2004, 'bio', 'Mapping Gene Ontology to proteins based on protein-protein interaction data', 'Deng, Minghua|Tu, Zhidong|Sun, Fengzhu|Chen, Ting', 'Department of Biological Sciences, Molecular and Computational Biology Program, University of Southern California, 1042 West 36th Place, Los Angeles, CA 90089-1113, USA.|Department of Biological Sciences, Molecular and Computational Biology Program, University of Southern California, 1042 West 36th Place, Los Angeles, CA 90089-1113, USA.|Department of Biological Sciences, Molecular and Computational Biology Program, University of Southern California, 1042 West 36th Place, Los Angeles, CA 90089-1113, USA.|Department of Biological Sciences, Molecular and Computational Biology Program, University of Southern California, 1042 West 36th Place, Los Angeles, CA 90089-1113, USA.', 'United States|United States|United States|United States', 0, 'Chromosome Mapping|Databases, Protein|Gene Expression Profiling|Gene Expression Regulation, Fungal|Genome, Fungal|Phylogeny|Protein Interaction Mapping|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/btg500', '14751964', 'Gene Ontology (GO) consortium provides structural description of protein function that is used as a common language for gene annotation in many organisms. Large-scale techniques have generated many valuable protein-protein interaction datasets that are useful for the study of protein function. Combining both GO and protein-protein interaction data allows the prediction of function for unknown proteins.'),
(71025, 2004, 'bio', 'Predicting the linkage sites in glycoproteins using bio-basis function neural network', 'Yang, Zheng Rong|Chou, Kuo-Chen', 'School of Engineering and Computer Science, Exeter University, Exeter EX4 4QF, UK. Z.R.Yang@exeter.ac.uk|School of Engineering and Computer Science, Exeter University, Exeter EX4 4QF, UK. Z.R.Yang@exeter.ac.uk', 'United Kingdom|United Kingdom', 23, 'Algorithms|Binding Sites|Glycoproteins|Models, Chemical|Models, Molecular|Neural Networks (Computer)|Protein Binding|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth001', '14751965', 'Although, it is known that O-glycosidically linked oligosaccharides are commonly conjugated to a serine, threonine or hydroxylysine residue of the polypeptide, the chemical nature of the anchoring monosaccharide and the size of the oligosaccharide unit varies. Among different types, O-linked or mucin-type oligosaccharides are intimately involved in the secretion of proteins, be they enzymes, hormones or structural glycoproteins. Knowledge of the linkage sites in glycoproteins is critical to the design of specific and efficient inhibitors against the enzyme to catalyse the formation of the carbohydrate-peptide linkage.'),
(71026, 2004, 'bio', 'Gene Unscrambler for detangling scrambled genes in ciliates', 'Cavalcanti, Andre R O|Landweber, Laura F', 'Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA. acavalca@princeton.edu|Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA. acavalca@princeton.edu', 'United States|United States', 0, 'Algorithms|Animals|Cell Nucleus|Chromosome Mapping|Ciliophora|Computer Graphics|DNA Mutational Analysis|Gene Expression Profiling|Linkage Disequilibrium|Micronucleus, Germline|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth003', '14751966', 'Scrambled genes are surprisingly common in some species of ciliates. Until now there was no software available to analyze automatically these genes. We present here a program that can automatically align the macronuclear and micronuclear forms of a gene, outputting the location of the macronuclear destined segments and pointer sequences.'),
(71027, 2004, 'bio', 'ReDiT: Repeat Discrepancy Tagger--a shotgun assembly finishing aid', 'Tammi, Martti T|Arner, Erik|Kindlund, Ellen|Andersson, Björn', 'Karolinska Institutet, Center for Genomics and Bioinformatics (CGB), Berzelius Väg 35, S-171 77 Stockholm, Sweden. martti.tammi@cgb.ki.se|Karolinska Institutet, Center for Genomics and Bioinformatics (CGB), Berzelius Väg 35, S-171 77 Stockholm, Sweden. martti.tammi@cgb.ki.se|Karolinska Institutet, Center for Genomics and Bioinformatics (CGB), Berzelius Väg 35, S-171 77 Stockholm, Sweden. martti.tammi@cgb.ki.se|Karolinska Institutet, Center for Genomics and Bioinformatics (CGB), Berzelius Väg 35, S-171 77 Stockholm, Sweden. martti.tammi@cgb.ki.se', 'Sweden|Sweden|Sweden|Sweden', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Computer Graphics|Documentation|Expressed Sequence Tags|Gene Expression Profiling|Genome|Molecular Sequence Data|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface|Word Processing', 'Evaluation Studies', '10.1093/bioinformatics/bth004', '14751967', 'Finishing, i.e. gap closure and editing, is the most time-consuming part of genome sequencing. Repeated sequences together with sequencing errors complicate the assembly and often result in misassemblies that are difficult to correct. Repeat Discrepancy Tagger (ReDiT) is a tool designed to aid in the finishing step. This software processes assembly results produced by any fragment assembly program that outputs ace files. The input sequences are analyzed to determine possible differences between repeated sequences. The output is written as tags in an ace file that can be viewed by, e.g. the Consed sequence editor.'),
(71028, 2004, 'bio', 'Alu repeat analysis in the complete human genome: trends and variations with respect to genomic composition', 'Grover, Deepak|Mukerji, Mitali|Bhatnagar, Pankaj|Kannan, K|Brahmachari, Samir K', 'Functional Genomics Unit, Institute of Genomics and Integrative Biology (IGIB), CSIR, Mall Road, Delhi 110007, India.|Functional Genomics Unit, Institute of Genomics and Integrative Biology (IGIB), CSIR, Mall Road, Delhi 110007, India.|Functional Genomics Unit, Institute of Genomics and Integrative Biology (IGIB), CSIR, Mall Road, Delhi 110007, India.|Functional Genomics Unit, Institute of Genomics and Integrative Biology (IGIB), CSIR, Mall Road, Delhi 110007, India.|Functional Genomics Unit, Institute of Genomics and Integrative Biology (IGIB), CSIR, Mall Road, Delhi 110007, India.', 'India|India|India|India|India', 89, 'Alu Elements|Chromosome Mapping|CpG Islands|Gene Expression Profiling|Genetic Variation|Genome, Human|Humans|Sequence Alignment|Sequence Analysis, DNA|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/bth005', '14751968', 'Transposon-derived Alu repeats are exclusively associated with primate genomes. They have gained considerable importance in the recent times with evidence of their involvement in various aspects of gene regulation, e.g. alternative splicing, nucleosome positioning, CpG methylation, binding sites for transcription factors and hormone receptors, etc. The objective of this study is to investigate the factors that influence the distribution of Alu repeat elements in the human genome. Such analysis is expected to yield insights into various aspects of gene regulation in primates.'),
(71029, 2004, 'bio', 'Modeling within-motif dependence for transcription factor binding site predictions', 'Zhou, Qing|Liu, Jun S', 'Department of Statistics, Harvard University, 1 Oxford ST, Cambridge, MA 02138, USA.|Department of Statistics, Harvard University, 1 Oxford ST, Cambridge, MA 02138, USA.', 'United States|United States', 110, 'Algorithms|Amino Acid Motifs|Binding Sites|Models, Chemical|Models, Statistical|Protein Binding|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth006', '14751969', 'The position-specific weight matrix (PWM) model, which assumes that each position in the DNA site contributes independently to the overall protein-DNA interaction, has been the primary means to describe transcription factor binding site motifs. Recent biological experiments, however, suggest that there exists interdependence among positions in the binding sites. In order to exploit this interdependence to aid motif discovery, we extend the PWM model to include pairs of correlated positions and design a Markov chain Monte Carlo algorithm to sample in the model space. We then combine the model sampling step with the Gibbs sampling framework for de novo motif discoveries.'),
(71030, 2004, 'bio', 'Gaussian mixture clustering and imputation of microarray data', 'Ouyang, Ming|Welsh, William J|Georgopoulos, Panos', 'Environmental and Occupational Health Sciences Institute, UMDNJ-Robert Wood Johnson Medical School and Rutgers, The State University of New Jersey, 170 Frelinghuysen Road, Piscataway, NJ 08854, USA. ouyang@fidelio.rutgers.edu|Environmental and Occupational Health Sciences Institute, UMDNJ-Robert Wood Johnson Medical School and Rutgers, The State University of New Jersey, 170 Frelinghuysen Road, Piscataway, NJ 08854, USA. ouyang@fidelio.rutgers.edu|Environmental and Occupational Health Sciences Institute, UMDNJ-Robert Wood Johnson Medical School and Rutgers, The State University of New Jersey, 170 Frelinghuysen Road, Piscataway, NJ 08854, USA. ouyang@fidelio.rutgers.edu', 'Jersey|Jersey|Jersey', 0, 'Algorithms|Artifacts|Benchmarking|Cell Cycle|Cluster Analysis|Gene Expression Profiling|Models, Genetic|Models, Statistical|Normal Distribution|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Yeasts', 'Comparative Study', '10.1093/bioinformatics/bth007', '14751970', 'In microarray experiments, missing entries arise from blemishes on the chips. In large-scale studies, virtually every chip contains some missing entries and more than 90% of the genes are affected. Many analysis methods require a full set of data. Either those genes with missing entries are excluded, or the missing entries are filled with estimates prior to the analyses. This study compares methods of missing value estimation.'),
(71031, 2004, 'bio', 'External control in Markovian genetic regulatory networks: the imperfect information case', 'Datta, Aniruddha|Choudhary, Ashish|Bittner, Michael L|Dougherty, Edward R', 'Department of Electrical Engineering, Texas A & M University, College Station, TX 77843-3128, USA.|Department of Electrical Engineering, Texas A & M University, College Station, TX 77843-3128, USA.|Department of Electrical Engineering, Texas A & M University, College Station, TX 77843-3128, USA.|Department of Electrical Engineering, Texas A & M University, College Station, TX 77843-3128, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Feedback|Gene Expression Profiling|Gene Expression Regulation|Humans|Markov Chains|Melanoma|Models, Genetic|Models, Statistical|Skin Neoplasms', 'Journal Article', '10.1093/bioinformatics/bth008', '14751971', 'Probabilistic Boolean Networks, which form a subclass of Markovian Genetic Regulatory Networks, have been recently introduced as a rule-based paradigm for modeling gene regulatory networks. In an earlier paper, we introduced external control into Markovian Genetic Regulatory networks. More precisely, given a Markovian genetic regulatory network whose state transition probabilities depend on an external (control) variable, a Dynamic Programming-based procedure was developed by which one could choose the sequence of control actions that minimized a given performance index over a finite number of steps. The control algorithm of that paper, however, could be implemented only when one had perfect knowledge of the states of the Markov Chain. This paper presents a control strategy that can be implemented in the imperfect information case, and makes use of the available measurements which are assumed to be probabilistically related to the states of the underlying Markov Chain.'),
(71032, 2004, 'bio', 'mdclust--exploratory microarray analysis by multidimensional clustering', 'Dugas, M|Merk, S|Breit, S|Dirschedl, P', 'Department of Medical Informatics, Marchioninistr. 15, D-81377 Munich, Germany. dug@ibe.med.uni-muenchen.de|Department of Medical Informatics, Marchioninistr. 15, D-81377 Munich, Germany. dug@ibe.med.uni-muenchen.de|Department of Medical Informatics, Marchioninistr. 15, D-81377 Munich, Germany. dug@ibe.med.uni-muenchen.de|Department of Medical Informatics, Marchioninistr. 15, D-81377 Munich, Germany. dug@ibe.med.uni-muenchen.de', 'Germany|Germany|Germany|Germany', 2, 'Cluster Analysis|Computer Graphics|Gene Expression Profiling|Humans|Leukemia|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth009', '14751972', 'Unsupervised clustering of microarray data may detect potentially important, but not obvious characteristics of samples, for instance subgroups of diagnoses with distinct gene profiles or systematic errors in experimentation.'),
(71033, 2004, 'bio', 'The Hera database and its use in the characterization of endoplasmic reticulum proteins', 'Scott, M|Lu, G|Hallett, M|Thomas, D Y', 'McGill Center for Bioinformatics, Duff Medical Building, McGill University, 3755 University Street, Montreal, Quebec, Canada H3A 2B4.|McGill Center for Bioinformatics, Duff Medical Building, McGill University, 3755 University Street, Montreal, Quebec, Canada H3A 2B4.|McGill Center for Bioinformatics, Duff Medical Building, McGill University, 3755 University Street, Montreal, Quebec, Canada H3A 2B4.|McGill Center for Bioinformatics, Duff Medical Building, McGill University, 3755 University Street, Montreal, Quebec, Canada H3A 2B4.', 'Canada|Canada|Canada|Canada', 29, 'Amino Acid Motifs|Databases, Protein|Endoplasmic Reticulum|Information Storage and Retrieval|Molecular Weight|Proteins|Sequence Analysis, Protein|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bth010', '14751973', 'Information concerning endoplasmic reticulum (ER) proteins is widely dispersed and cannot be easily and rapidly processed by the biological community. We present a comprehensive database of human ER proteins, called Human ER Aperçu (Hera). The Hera database was constructed by exhaustively searching through public databases and the scientific literature for ER proteins.'),
(71034, 2004, 'bio', 'Finding coexpressed genes in counts-based data: an improved measure with validation experiments', 'Price, Morgan N|Rieffel, Eleanor', 'FX Palo Alto Laboratory, 3400 Hillview Avenue Building 4, Palo Alto, CA 94304, USA. mprice@cs.cmu.edu|FX Palo Alto Laboratory, 3400 Hillview Avenue Building 4, Palo Alto, CA 94304, USA. mprice@cs.cmu.edu', 'United States|United States', 0, 'Algorithms|Databases, Nucleic Acid|Expressed Sequence Tags|Gene Expression Profiling|Humans|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth011', '14751974', 'Expressed sequence tag (EST) data reflects variation in gene expression, but previous methods for finding coexpressed genes in EST data are subject to bias and vastly overstate the statistical significance of putatively coexpressed genes.'),
(71035, 2004, 'bio', 'Visualization of near-optimal sequence alignments', 'Smoot, Michael E|Guerlain, Stephanie A|Pearson, William R', 'Department of Systems and Information Engineering, University of Virginia, Charlottesville, VA 22908, USA.|Department of Systems and Information Engineering, University of Virginia, Charlottesville, VA 22908, USA.|Department of Systems and Information Engineering, University of Virginia, Charlottesville, VA 22908, USA.', 'United States|United States|United States', 0, 'Algorithms|Computer Graphics|Databases, Protein|Internet|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth013', '14751975', 'Mathematically optimal alignments do not always properly align active site residues or well-recognized structural elements. Most near-optimal sequence alignment algorithms display alternative alignment paths, rather than the conventional residue-by-residue pairwise alignment. Typically, these methods do not provide mechanisms for finding effectively the most biologically meaningful alignment in the potentially large set of options.'),
(71036, 2004, 'bio', 'ClusterControl: a web interface for distributing and monitoring bioinformatics applications on a Linux cluster', 'Stocker, Gernot|Rieder, Dietmar|Trajanoski, Zlatko', 'Institute of Biomedical Engineering and Christian-Doppler-Laboratory for Genomics and Bioinformatics, Graz University of Technology, Krenngasse 37, 8010 Graz, Austria.|Institute of Biomedical Engineering and Christian-Doppler-Laboratory for Genomics and Bioinformatics, Graz University of Technology, Krenngasse 37, 8010 Graz, Austria.|Institute of Biomedical Engineering and Christian-Doppler-Laboratory for Genomics and Bioinformatics, Graz University of Technology, Krenngasse 37, 8010 Graz, Austria.', 'Austria|Austria|Austria', 2, 'Computational Biology|Computer Communication Networks|Computing Methodologies|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Internet|Online Systems|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth014', '14751976', 'ClusterControl is a web interface to simplify distributing and monitoring bioinformatics applications on Linux cluster systems. We have developed a modular concept that enables integration of command line oriented program into the application framework of ClusterControl. The systems facilitate integration of different applications accessed through one interface and executed on a distributed cluster system. The package is based on freely available technologies like Apache as web server, PHP as server-side scripting language and OpenPBS as queuing system and is available free of charge for academic and non-profit institutions.'),
(71037, 2004, 'bio', 'Identification of optimal classification functions for biological sample and state discrimination from metabolic profiling data', 'Lee, Kyongbum|Hwang, Daehee|Yokoyama, Tadaaki|Stephanopoulos, George|Stephanopoulos, Gregory N|Yarmush, Martin L', 'Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA.|Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA.|Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA.|Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA.|Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA.|Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA.', 'United States|United States|United States|United States|United States|United States', 12, 'Algorithms|Amino Acids|Ammonia|Animals|Biomarkers|Diagnosis, Computer-Assisted|Galactosamine|Glucose|Ketone Bodies|Lactic Acid|Liver Failure|Male|Metabolic Clearance Rate|Models, Biological|Models, Statistical|Multivariate Analysis|Organ Specificity|Rats|Rats, Sprague-Dawley|Reproducibility of Results|Sensitivity and Specificity|Urea', 'Comparative Study', '10.1093/bioinformatics/bth015', '14751977', 'Classification of biological samples for diagnostic purposes is a difficult task because of the many decisions involved on the number, type and functional manipulations of the input variables. This study presents a generally applicable strategy for systematic formulation of optimal diagnostic indexes. To this end, we develop a novel set of computational tools by integrating regression optimization, stepwise variable selection and cross-validation algorithms.'),
(71038, 2004, 'bio', 'Effects of choice of DNA sequence model structure on gene identification accuracy', 'Azad, Rajeev K|Borodovsky, Mark', 'School of Biology, Georgia Institute of Technology, Atlanta, GA 30332-0230, USA.|School of Biology, Georgia Institute of Technology, Atlanta, GA 30332-0230, USA.', 'Georgia|Georgia', 0, 'Algorithms|Computer Simulation|DNA, Bacterial|Gene Expression Profiling|Markov Chains|Models, Genetic|Models, Statistical|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth028', '14751980', 'Markov chain models of DNA sequences have frequently been used in gene finding algorithms. Performance of the algorithm critically depends on the model structure and parameters. Still, the issue of choosing the model structure has not been studied with sufficient attention.'),
(71039, 2004, 'bio', 'Large-scale analysis of non-synonymous coding region single nucleotide polymorphisms', 'Clifford, Robert J|Edmonson, Michael N|Nguyen, Cu|Buetow, Kenneth H', 'Laboratory of Population Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.|Laboratory of Population Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.|Laboratory of Population Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.|Laboratory of Population Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.', 'United States|United States|United States|United States', 63, 'Amino Acid Motifs|Computer Simulation|Databases, Protein|Gene Expression Profiling|Models, Molecular|Open Reading Frames|Polymorphism, Single Nucleotide|Protein Conformation|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth029', '14751981', 'Single nucleotide polymorphisms (SNPs) are the most common form of genetic variant in humans. SNPs causing amino acid substitutions are of particular interest as candidates for loci affecting susceptibility to complex diseases, such as diabetes and hypertension. To efficiently screen SNPs for disease association, it is important to distinguish neutral variants from deleterious ones.');
